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6 Commits

Author SHA1 Message Date
8a8ce1cc72 0002 - Avoid passing cache around methods (so far only for StaticCache) 2024-05-19 13:11:10 +02:00
331c2550dd Add comment for 0001 2024-05-19 11:28:21 +02:00
e513b60917 0001 - Avoid cache conversion 2024-05-18 12:09:12 +02:00
68b71c85e1 Avoid slicing for DynamicCache 2024-05-18 12:08:40 +02:00
862cde4ce8 fix 2024-05-16 15:12:40 +02:00
af2e273e2d dynamic is all you need 2024-05-16 15:08:20 +02:00
3580 changed files with 98933 additions and 354516 deletions

View File

@ -13,7 +13,6 @@ jobs:
check_circleci_user:
docker:
- image: python:3.10-slim
resource_class: small
parallelism: 1
steps:
- run: echo $CIRCLE_PROJECT_USERNAME
@ -32,100 +31,92 @@ jobs:
steps:
- checkout
- run: uv pip install -U -e .
- run: echo 'export "GIT_COMMIT_MESSAGE=$(git show -s --format=%s)"' >> "$BASH_ENV" && source "$BASH_ENV"
- run: mkdir -p test_preparation
- run: python utils/tests_fetcher.py | tee tests_fetched_summary.txt
- run: python utils/tests_fetcher.py --filter_tests
- run: export "GIT_COMMIT_MESSAGE=$(git show -s --format=%s)" && echo $GIT_COMMIT_MESSAGE && python .circleci/create_circleci_config.py --fetcher_folder test_preparation
- store_artifacts:
path: ~/transformers/tests_fetched_summary.txt
- run: |
if [ ! -s test_preparation/generated_config.yml ]; then
echo "No tests to run, exiting early!"
circleci-agent step halt
if [ -f test_list.txt ]; then
cp test_list.txt test_preparation/test_list.txt
else
touch test_preparation/test_list.txt
fi
- run: |
if [ -f examples_test_list.txt ]; then
mv examples_test_list.txt test_preparation/examples_test_list.txt
else
touch test_preparation/examples_test_list.txt
fi
- run: |
if [ -f filtered_test_list_cross_tests.txt ]; then
mv filtered_test_list_cross_tests.txt test_preparation/filtered_test_list_cross_tests.txt
else
touch test_preparation/filtered_test_list_cross_tests.txt
fi
- run: |
if [ -f doctest_list.txt ]; then
cp doctest_list.txt test_preparation/doctest_list.txt
else
touch test_preparation/doctest_list.txt
fi
- run: |
if [ -f test_repo_utils.txt ]; then
mv test_repo_utils.txt test_preparation/test_repo_utils.txt
else
touch test_preparation/test_repo_utils.txt
fi
- run: python utils/tests_fetcher.py --filter_tests
- run: |
if [ -f test_list.txt ]; then
mv test_list.txt test_preparation/filtered_test_list.txt
else
touch test_preparation/filtered_test_list.txt
fi
- store_artifacts:
path: test_preparation
- run:
name: "Retrieve Artifact Paths"
# [reference] https://circleci.com/docs/api/v2/index.html#operation/getJobArtifacts
# `CIRCLE_TOKEN` is defined as an environment variables set within a context, see `https://circleci.com/docs/contexts/`
command: |
project_slug="gh/${CIRCLE_PROJECT_USERNAME}/${CIRCLE_PROJECT_REPONAME}"
job_number=${CIRCLE_BUILD_NUM}
url="https://circleci.com/api/v2/project/${project_slug}/${job_number}/artifacts"
curl -o test_preparation/artifacts.json ${url} --header "Circle-Token: $CIRCLE_TOKEN"
- run:
name: "Prepare pipeline parameters"
command: |
python utils/process_test_artifacts.py
# To avoid too long generated_config.yaml on the continuation orb, we pass the links to the artifacts as parameters.
# Otherwise the list of tests was just too big. Explicit is good but for that it was a limitation.
# We used:
# https://circleci.com/docs/api/v2/index.html#operation/getJobArtifacts : to get the job artifacts
# We could not pass a nested dict, which is why we create the test_file_... parameters for every single job
path: test_preparation/test_list.txt
- store_artifacts:
path: test_preparation/transformed_artifacts.json
path: test_preparation/doctest_list.txt
- store_artifacts:
path: test_preparation/artifacts.json
path: ~/transformers/test_preparation/filtered_test_list.txt
- store_artifacts:
path: test_preparation/examples_test_list.txt
- run: python .circleci/create_circleci_config.py --fetcher_folder test_preparation
- run: |
if [ ! -s test_preparation/generated_config.yml ]; then
echo "No tests to run, exiting early!"
circleci-agent step halt
fi
- store_artifacts:
path: test_preparation/generated_config.yml
- store_artifacts:
path: test_preparation/filtered_test_list_cross_tests.txt
- continuation/continue:
parameters: test_preparation/transformed_artifacts.json
configuration_path: test_preparation/generated_config.yml
# To run all tests for the nightly build
fetch_all_tests:
working_directory: ~/transformers
docker:
- image: huggingface/transformers-quality
- image: huggingface/transformers-consistency
parallelism: 1
steps:
- checkout
- run: uv pip install -U -e .
- run: echo 'export "GIT_COMMIT_MESSAGE=$(git show -s --format=%s)"' >> "$BASH_ENV" && source "$BASH_ENV"
- run: mkdir -p test_preparation
- run: python utils/tests_fetcher.py --fetch_all | tee tests_fetched_summary.txt
- run: python utils/tests_fetcher.py --filter_tests
- run: export "GIT_COMMIT_MESSAGE=$(git show -s --format=%s)" && echo $GIT_COMMIT_MESSAGE && python .circleci/create_circleci_config.py --fetcher_folder test_preparation
- run: uv pip install -e .
- run: |
if [ ! -s test_preparation/generated_config.yml ]; then
echo "No tests to run, exiting early!"
circleci-agent step halt
fi
mkdir test_preparation
echo -n "tests" > test_preparation/test_list.txt
echo -n "all" > test_preparation/examples_test_list.txt
echo -n "tests/repo_utils" > test_preparation/test_repo_utils.txt
- run: |
echo -n "tests" > test_list.txt
python utils/tests_fetcher.py --filter_tests
mv test_list.txt test_preparation/filtered_test_list.txt
- run: python .circleci/create_circleci_config.py --fetcher_folder test_preparation
- run: cp test_preparation/generated_config.yml test_preparation/generated_config.txt
- store_artifacts:
path: test_preparation
- run:
name: "Retrieve Artifact Paths"
env:
CIRCLE_TOKEN: ${{ secrets.CI_ARTIFACT_TOKEN }}
command: |
project_slug="gh/${CIRCLE_PROJECT_USERNAME}/${CIRCLE_PROJECT_REPONAME}"
job_number=${CIRCLE_BUILD_NUM}
url="https://circleci.com/api/v2/project/${project_slug}/${job_number}/artifacts"
curl -o test_preparation/artifacts.json ${url}
- run:
name: "Prepare pipeline parameters"
command: |
python utils/process_test_artifacts.py
# To avoid too long generated_config.yaml on the continuation orb, we pass the links to the artifacts as parameters.
# Otherwise the list of tests was just too big. Explicit is good but for that it was a limitation.
# We used:
# https://circleci.com/docs/api/v2/index.html#operation/getJobArtifacts : to get the job artifacts
# We could not pass a nested dict, which is why we create the test_file_... parameters for every single job
- store_artifacts:
path: test_preparation/transformed_artifacts.json
- store_artifacts:
path: test_preparation/artifacts.json
path: test_preparation/generated_config.txt
- continuation/continue:
parameters: test_preparation/transformed_artifacts.json
configuration_path: test_preparation/generated_config.yml
configuration_path: test_preparation/generated_config.yml
check_code_quality:
working_directory: ~/transformers
@ -138,7 +129,7 @@ jobs:
parallelism: 1
steps:
- checkout
- run: uv pip install -e ".[quality]"
- run: uv pip install -e .
- run:
name: Show installed libraries and their versions
command: pip freeze | tee installed.txt
@ -150,7 +141,6 @@ jobs:
- run: python utils/custom_init_isort.py --check_only
- run: python utils/sort_auto_mappings.py --check_only
- run: python utils/check_doc_toc.py
- run: python utils/check_docstrings.py --check_all
check_repository_consistency:
working_directory: ~/transformers
@ -163,14 +153,13 @@ jobs:
parallelism: 1
steps:
- checkout
- run: uv pip install -e ".[quality]"
- run: uv pip install -e .
- run:
name: Show installed libraries and their versions
command: pip freeze | tee installed.txt
- store_artifacts:
path: ~/transformers/installed.txt
- run: python utils/check_copies.py
- run: python utils/check_modular_conversion.py --num_workers 4
- run: python utils/check_table.py
- run: python utils/check_dummies.py
- run: python utils/check_repo.py
@ -187,32 +176,17 @@ workflows:
version: 2
setup_and_quality:
when:
and:
- equal: [<<pipeline.project.git_url>>, https://github.com/huggingface/transformers]
- not: <<pipeline.parameters.nightly>>
not: <<pipeline.parameters.nightly>>
jobs:
- check_circleci_user
- check_code_quality
- check_repository_consistency
- fetch_tests
setup_and_quality_2:
when:
not:
equal: [<<pipeline.project.git_url>>, https://github.com/huggingface/transformers]
jobs:
- check_circleci_user
- check_code_quality
- check_repository_consistency
- fetch_tests:
# [reference] https://circleci.com/docs/contexts/
context:
- TRANSFORMERS_CONTEXT
nightly:
when: <<pipeline.parameters.nightly>>
jobs:
- check_circleci_user
- check_code_quality
- check_repository_consistency
- fetch_all_tests
- fetch_all_tests

View File

@ -32,7 +32,7 @@ COMMON_ENV_VARIABLES = {
"RUN_PT_FLAX_CROSS_TESTS": False,
}
# Disable the use of {"s": None} as the output is way too long, causing the navigation on CircleCI impractical
COMMON_PYTEST_OPTIONS = {"max-worker-restart": 0, "dist": "loadfile", "vvv": None, "rsfE":None}
COMMON_PYTEST_OPTIONS = {"max-worker-restart": 0, "dist": "loadfile", "v": None}
DEFAULT_DOCKER_IMAGE = [{"image": "cimg/python:3.8.12"}]
@ -40,23 +40,9 @@ class EmptyJob:
job_name = "empty"
def to_dict(self):
steps = [{"run": 'ls -la'}]
if self.job_name == "collection_job":
steps.extend(
[
"checkout",
{"run": "pip install requests || true"},
{"run": """while [[ $(curl --location --request GET "https://circleci.com/api/v2/workflow/$CIRCLE_WORKFLOW_ID/job" --header "Circle-Token: $CCI_TOKEN"| jq -r '.items[]|select(.name != "collection_job")|.status' | grep -c "running") -gt 0 ]]; do sleep 5; done || true"""},
{"run": 'python utils/process_circleci_workflow_test_reports.py --workflow_id $CIRCLE_WORKFLOW_ID || true'},
{"store_artifacts": {"path": "outputs"}},
{"run": 'echo "All required jobs have now completed"'},
]
)
return {
"docker": copy.deepcopy(DEFAULT_DOCKER_IMAGE),
"resource_class": "small",
"steps": steps,
"steps":["checkout"],
}
@ -64,15 +50,16 @@ class EmptyJob:
class CircleCIJob:
name: str
additional_env: Dict[str, Any] = None
cache_name: str = None
cache_version: str = "0.8.2"
docker_image: List[Dict[str, str]] = None
install_steps: List[str] = None
marker: Optional[str] = None
parallelism: Optional[int] = 0
pytest_num_workers: int = 8
parallelism: Optional[int] = 1
pytest_num_workers: int = 12
pytest_options: Dict[str, Any] = None
resource_class: Optional[str] = "xlarge"
resource_class: Optional[str] = "2xlarge"
tests_to_run: Optional[List[str]] = None
num_test_files_per_worker: Optional[int] = 10
# This should be only used for doctest job!
command_timeout: Optional[int] = None
@ -80,106 +67,161 @@ class CircleCIJob:
# Deal with defaults for mutable attributes.
if self.additional_env is None:
self.additional_env = {}
if self.cache_name is None:
self.cache_name = self.name
if self.docker_image is None:
# Let's avoid changing the default list and make a copy.
self.docker_image = copy.deepcopy(DEFAULT_DOCKER_IMAGE)
else:
# BIG HACK WILL REMOVE ONCE FETCHER IS UPDATED
print(os.environ.get("GIT_COMMIT_MESSAGE"))
if "[build-ci-image]" in os.environ.get("GIT_COMMIT_MESSAGE", "") or os.environ.get("GIT_COMMIT_MESSAGE", "") == "dev-ci":
self.docker_image[0]["image"] = f"{self.docker_image[0]['image']}:dev"
print(f"Using {self.docker_image} docker image")
if self.install_steps is None:
self.install_steps = ["uv venv && uv pip install ."]
self.install_steps = []
if self.pytest_options is None:
self.pytest_options = {}
if isinstance(self.tests_to_run, str):
self.tests_to_run = [self.tests_to_run]
else:
test_file = os.path.join("test_preparation" , f"{self.job_name}_test_list.txt")
print("Looking for ", test_file)
if os.path.exists(test_file):
with open(test_file) as f:
expanded_tests = f.read().strip().split("\n")
self.tests_to_run = expanded_tests
print("Found:", expanded_tests)
else:
self.tests_to_run = []
print("not Found")
if self.parallelism is None:
self.parallelism = 1
def to_dict(self):
env = COMMON_ENV_VARIABLES.copy()
env.update(self.additional_env)
cache_branch_prefix = os.environ.get("CIRCLE_BRANCH", "pull")
if cache_branch_prefix != "main":
cache_branch_prefix = "pull"
job = {
"docker": self.docker_image,
"environment": env,
}
if self.resource_class is not None:
job["resource_class"] = self.resource_class
if self.parallelism is not None:
job["parallelism"] = self.parallelism
steps = [
"checkout",
{"attach_workspace": {"at": "test_preparation"}},
]
steps.extend([{"run": l} for l in self.install_steps])
steps.append({"run": {"name": "Show installed libraries and their size", "command": """du -h -d 1 "$(pip -V | cut -d ' ' -f 4 | sed 's/pip//g')" | grep -vE "dist-info|_distutils_hack|__pycache__" | sort -h | tee installed.txt || true"""}})
steps.append({"run": {"name": "Show installed libraries and their versions", "command": """pip list --format=freeze | tee installed.txt || true"""}})
steps.append({"run":{"name":"Show biggest libraries","command":"""dpkg-query --show --showformat='${Installed-Size}\t${Package}\n' | sort -rh | head -25 | sort -h | awk '{ package=$2; sub(".*/", "", package); printf("%.5f GB %s\n", $1/1024/1024, package)}' || true"""}})
steps.append({"store_artifacts": {"path": "installed.txt"}})
all_options = {**COMMON_PYTEST_OPTIONS, **self.pytest_options}
pytest_flags = [f"--{key}={value}" if (value is not None or key in ["doctest-modules"]) else f"-{key}" for key, value in all_options.items()]
pytest_flags.append(
f"--make-reports={self.name}" if "examples" in self.name else f"--make-reports=tests_{self.name}"
)
# Examples special case: we need to download NLTK files in advance to avoid cuncurrency issues
timeout_cmd = f"timeout {self.command_timeout} " if self.command_timeout else ""
marker_cmd = f"-m '{self.marker}'" if self.marker is not None else ""
additional_flags = f" -p no:warning -o junit_family=xunit1 --junitxml=test-results/junit.xml"
parallel = f' << pipeline.parameters.{self.job_name}_parallelism >> '
steps = [
"checkout",
{"attach_workspace": {"at": "test_preparation"}},
{"run": "apt-get update && apt-get install -y curl"},
{"run": " && ".join(self.install_steps)},
{"run": {"name": "Download NLTK files", "command": """python -c "import nltk; nltk.download('punkt', quiet=True)" """} if "example" in self.name else "echo Skipping"},
{"run": {
"name": "Show installed libraries and their size",
"command": """du -h -d 1 "$(pip -V | cut -d ' ' -f 4 | sed 's/pip//g')" | grep -vE "dist-info|_distutils_hack|__pycache__" | sort -h | tee installed.txt || true"""}
},
{"run": {
"name": "Show installed libraries and their versions",
"command": """pip list --format=freeze | tee installed.txt || true"""}
},
{"run": {
"name": "Show biggest libraries",
"command": """dpkg-query --show --showformat='${Installed-Size}\t${Package}\n' | sort -rh | head -25 | sort -h | awk '{ package=$2; sub(".*/", "", package); printf("%.5f GB %s\n", $1/1024/1024, package)}' || true"""}
},
{"run": {"name": "Create `test-results` directory", "command": "mkdir test-results"}},
{"run": {"name": "Get files to test", "command":f'curl -L -o {self.job_name}_test_list.txt <<pipeline.parameters.{self.job_name}_test_list>> --header "Circle-Token: $CIRCLE_TOKEN"' if self.name != "pr_documentation_tests" else 'echo "Skipped"'}},
{"run": {"name": "Split tests across parallel nodes: show current parallel tests",
"command": f"TESTS=$(circleci tests split --split-by=timings {self.job_name}_test_list.txt) && echo $TESTS > splitted_tests.txt && echo $TESTS | tr ' ' '\n'" if self.parallelism else f"awk '{{printf \"%s \", $0}}' {self.job_name}_test_list.txt > splitted_tests.txt"
}
},
{"run": {
"name": "Run tests",
"command": f"({timeout_cmd} python3 -m pytest {marker_cmd} -n {self.pytest_num_workers} {additional_flags} {' '.join(pytest_flags)} $(cat splitted_tests.txt) | tee tests_output.txt)"}
},
{"run": {"name": "Expand to show skipped tests", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --skip"}},
{"run": {"name": "Failed tests: show reasons", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --fail"}},
{"run": {"name": "Errors", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --errors"}},
{"store_test_results": {"path": "test-results"}},
{"store_artifacts": {"path": "test-results/junit.xml"}},
{"store_artifacts": {"path": "reports"}},
{"store_artifacts": {"path": "tests.txt"}},
{"store_artifacts": {"path": "splitted_tests.txt"}},
{"store_artifacts": {"path": "installed.txt"}},
]
if self.parallelism:
job["parallelism"] = parallel
steps.append({"run": {"name": "Create `test-results` directory", "command": "mkdir test-results"}})
test_command = ""
if self.command_timeout:
test_command = f"timeout {self.command_timeout} "
# junit familiy xunit1 is necessary to support splitting on test name or class name with circleci split
test_command += f"python3 -m pytest -rsfE -p no:warnings -o junit_family=xunit1 --tb=short --junitxml=test-results/junit.xml -n {self.pytest_num_workers} " + " ".join(pytest_flags)
if self.parallelism == 1:
if self.tests_to_run is None:
test_command += " << pipeline.parameters.tests_to_run >>"
else:
test_command += " " + " ".join(self.tests_to_run)
else:
# We need explicit list instead of `pipeline.parameters.tests_to_run` (only available at job runtime)
tests = self.tests_to_run
if tests is None:
folder = os.environ["test_preparation_dir"]
test_file = os.path.join(folder, "filtered_test_list.txt")
if os.path.exists(test_file): # We take this job's tests from the filtered test_list.txt
with open(test_file) as f:
tests = f.read().split(" ")
# expand the test list
if tests == ["tests"]:
tests = [os.path.join("tests", x) for x in os.listdir("tests")]
expanded_tests = []
for test in tests:
if test.endswith(".py"):
expanded_tests.append(test)
elif test == "tests/models":
if "tokenization" in self.name:
expanded_tests.extend(glob.glob("tests/models/**/test_tokenization*.py", recursive=True))
elif self.name in ["flax","torch","tf"]:
name = self.name if self.name != "torch" else ""
if self.name == "torch":
all_tests = glob.glob(f"tests/models/**/test_modeling_{name}*.py", recursive=True)
filtered = [k for k in all_tests if ("_tf_") not in k and "_flax_" not in k]
expanded_tests.extend(filtered)
else:
expanded_tests.extend(glob.glob(f"tests/models/**/test_modeling_{name}*.py", recursive=True))
else:
expanded_tests.extend(glob.glob("tests/models/**/test_modeling*.py", recursive=True))
elif test == "tests/pipelines":
expanded_tests.extend(glob.glob("tests/models/**/test_modeling*.py", recursive=True))
else:
expanded_tests.append(test)
tests = " ".join(expanded_tests)
# Each executor to run ~10 tests
n_executors = max(len(expanded_tests) // 10, 1)
# Avoid empty test list on some executor(s) or launching too many executors
if n_executors > self.parallelism:
n_executors = self.parallelism
job["parallelism"] = n_executors
# Need to be newline separated for the command `circleci tests split` below
command = f'echo {tests} | tr " " "\\n" >> tests.txt'
steps.append({"run": {"name": "Get tests", "command": command}})
command = 'TESTS=$(circleci tests split tests.txt) && echo $TESTS > splitted_tests.txt'
steps.append({"run": {"name": "Split tests", "command": command}})
steps.append({"store_artifacts": {"path": "tests.txt"}})
steps.append({"store_artifacts": {"path": "splitted_tests.txt"}})
test_command = ""
if self.command_timeout:
test_command = f"timeout {self.command_timeout} "
test_command += f"python3 -m pytest -rsfE -p no:warnings --tb=short -o junit_family=xunit1 --junitxml=test-results/junit.xml -n {self.pytest_num_workers} " + " ".join(pytest_flags)
test_command += " $(cat splitted_tests.txt)"
if self.marker is not None:
test_command += f" -m {self.marker}"
if self.name == "pr_documentation_tests":
# can't use ` | tee tee tests_output.txt` as usual
test_command += " > tests_output.txt"
# Save the return code, so we can check if it is timeout in the next step.
test_command += '; touch "$?".txt'
# Never fail the test step for the doctest job. We will check the results in the next step, and fail that
# step instead if the actual test failures are found. This is to avoid the timeout being reported as test
# failure.
test_command = f"({test_command}) || true"
else:
test_command = f"({test_command} | tee tests_output.txt)"
steps.append({"run": {"name": "Run tests", "command": test_command}})
steps.append({"run": {"name": "Skipped tests", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --skip"}})
steps.append({"run": {"name": "Failed tests", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --fail"}})
steps.append({"run": {"name": "Errors", "when": "always", "command": f"python3 .circleci/parse_test_outputs.py --file tests_output.txt --errors"}})
steps.append({"store_test_results": {"path": "test-results"}})
steps.append({"store_artifacts": {"path": "tests_output.txt"}})
steps.append({"store_artifacts": {"path": "test-results/junit.xml"}})
steps.append({"store_artifacts": {"path": "reports"}})
job["steps"] = steps
return job
@property
def job_name(self):
return self.name if ("examples" in self.name or "pipeline" in self.name or "pr_documentation" in self.name) else f"tests_{self.name}"
return self.name if "examples" in self.name else f"tests_{self.name}"
# JOBS
torch_and_tf_job = CircleCIJob(
"torch_and_tf",
docker_image=[{"image":"huggingface/transformers-torch-tf-light"}],
install_steps=["uv venv && uv pip install ."],
additional_env={"RUN_PT_TF_CROSS_TESTS": True},
marker="is_pt_tf_cross_test",
pytest_options={"rA": None, "durations": 0},
@ -190,6 +232,7 @@ torch_and_flax_job = CircleCIJob(
"torch_and_flax",
additional_env={"RUN_PT_FLAX_CROSS_TESTS": True},
docker_image=[{"image":"huggingface/transformers-torch-jax-light"}],
install_steps=["uv venv && uv pip install ."],
marker="is_pt_flax_cross_test",
pytest_options={"rA": None, "durations": 0},
)
@ -197,42 +240,35 @@ torch_and_flax_job = CircleCIJob(
torch_job = CircleCIJob(
"torch",
docker_image=[{"image": "huggingface/transformers-torch-light"}],
marker="not generate",
parallelism=6,
)
generate_job = CircleCIJob(
"generate",
docker_image=[{"image": "huggingface/transformers-torch-light"}],
marker="generate",
install_steps=["uv venv && uv pip install ."],
parallelism=6,
pytest_num_workers=16
)
tokenization_job = CircleCIJob(
"tokenization",
docker_image=[{"image": "huggingface/transformers-torch-light"}],
parallelism=8,
install_steps=["uv venv && uv pip install ."],
parallelism=6,
pytest_num_workers=16
)
processor_job = CircleCIJob(
"processors",
docker_image=[{"image": "huggingface/transformers-torch-light"}],
parallelism=8,
)
tf_job = CircleCIJob(
"tf",
docker_image=[{"image":"huggingface/transformers-tf-light"}],
install_steps=["uv venv", "uv pip install -e."],
parallelism=6,
pytest_num_workers=16,
)
flax_job = CircleCIJob(
"flax",
docker_image=[{"image":"huggingface/transformers-jax-light"}],
install_steps=["uv venv && uv pip install ."],
parallelism=6,
pytest_num_workers=16,
resource_class="2xlarge",
pytest_num_workers=16
)
@ -240,8 +276,8 @@ pipelines_torch_job = CircleCIJob(
"pipelines_torch",
additional_env={"RUN_PIPELINE_TESTS": True},
docker_image=[{"image":"huggingface/transformers-torch-light"}],
install_steps=["uv venv && uv pip install ."],
marker="is_pipeline_test",
parallelism=4,
)
@ -249,8 +285,8 @@ pipelines_tf_job = CircleCIJob(
"pipelines_tf",
additional_env={"RUN_PIPELINE_TESTS": True},
docker_image=[{"image":"huggingface/transformers-tf-light"}],
install_steps=["uv venv && uv pip install ."],
marker="is_pipeline_test",
parallelism=4,
)
@ -258,22 +294,34 @@ custom_tokenizers_job = CircleCIJob(
"custom_tokenizers",
additional_env={"RUN_CUSTOM_TOKENIZERS": True},
docker_image=[{"image": "huggingface/transformers-custom-tokenizers"}],
install_steps=["uv venv","uv pip install -e ."],
parallelism=None,
resource_class=None,
tests_to_run=[
"./tests/models/bert_japanese/test_tokenization_bert_japanese.py",
"./tests/models/openai/test_tokenization_openai.py",
"./tests/models/clip/test_tokenization_clip.py",
],
)
examples_torch_job = CircleCIJob(
"examples_torch",
additional_env={"OMP_NUM_THREADS": 8},
cache_name="torch_examples",
docker_image=[{"image":"huggingface/transformers-examples-torch"}],
# TODO @ArthurZucker remove this once docker is easier to build
install_steps=["uv venv && uv pip install . && uv pip install -r examples/pytorch/_tests_requirements.txt"],
pytest_num_workers=1,
)
examples_tensorflow_job = CircleCIJob(
"examples_tensorflow",
additional_env={"OMP_NUM_THREADS": 8},
cache_name="tensorflow_examples",
docker_image=[{"image":"huggingface/transformers-examples-tf"}],
install_steps=["uv venv && uv pip install ."],
parallelism=8
)
@ -282,13 +330,12 @@ hub_job = CircleCIJob(
additional_env={"HUGGINGFACE_CO_STAGING": True},
docker_image=[{"image":"huggingface/transformers-torch-light"}],
install_steps=[
'uv venv && uv pip install .',
"uv venv && uv pip install .",
'git config --global user.email "ci@dummy.com"',
'git config --global user.name "ci"',
],
marker="is_staging_test",
pytest_num_workers=2,
resource_class="medium",
pytest_num_workers=1,
)
@ -296,18 +343,27 @@ onnx_job = CircleCIJob(
"onnx",
docker_image=[{"image":"huggingface/transformers-torch-tf-light"}],
install_steps=[
"uv venv",
"uv venv && uv pip install .",
"uv pip install --upgrade eager pip",
"uv pip install .[torch,tf,testing,sentencepiece,onnxruntime,vision,rjieba]",
],
pytest_options={"k onnx": None},
pytest_num_workers=1,
resource_class="small",
)
exotic_models_job = CircleCIJob(
"exotic_models",
install_steps=["uv venv && uv pip install ."],
docker_image=[{"image":"huggingface/transformers-exotic-models"}],
tests_to_run=[
"tests/models/*layoutlmv*",
"tests/models/*nat",
"tests/models/deta",
"tests/models/udop",
"tests/models/nougat",
],
pytest_num_workers=12,
parallelism=4,
pytest_options={"durations": 100},
)
@ -316,16 +372,11 @@ exotic_models_job = CircleCIJob(
repo_utils_job = CircleCIJob(
"repo_utils",
docker_image=[{"image":"huggingface/transformers-consistency"}],
pytest_num_workers=4,
install_steps=["uv venv && uv pip install ."],
parallelism=None,
pytest_num_workers=1,
resource_class="large",
)
non_model_job = CircleCIJob(
"non_model",
docker_image=[{"image": "huggingface/transformers-torch-light"}],
marker="not generate",
parallelism=6,
tests_to_run="tests/repo_utils",
)
@ -334,18 +385,28 @@ non_model_job = CircleCIJob(
# the bash output redirection.)
py_command = 'from utils.tests_fetcher import get_doctest_files; to_test = get_doctest_files() + ["dummy.py"]; to_test = " ".join(to_test); print(to_test)'
py_command = f"$(python3 -c '{py_command}')"
command = f'echo """{py_command}""" > pr_documentation_tests_temp.txt'
command = f'echo "{py_command}" > pr_documentation_tests_temp.txt'
doc_test_job = CircleCIJob(
"pr_documentation_tests",
docker_image=[{"image":"huggingface/transformers-consistency"}],
additional_env={"TRANSFORMERS_VERBOSITY": "error", "DATASETS_VERBOSITY": "error", "SKIP_CUDA_DOCTEST": "1"},
install_steps=[
# Add an empty file to keep the test step running correctly even no file is selected to be tested.
"uv venv && pip install .",
"touch dummy.py",
command,
"cat pr_documentation_tests_temp.txt",
"tail -n1 pr_documentation_tests_temp.txt | tee pr_documentation_tests_test_list.txt"
{
"name": "Get files to test",
"command": command,
},
{
"name": "Show information in `Get files to test`",
"command":
"cat pr_documentation_tests_temp.txt"
},
{
"name": "Get the last line in `pr_documentation_tests.txt`",
"command":
"tail -n1 pr_documentation_tests_temp.txt | tee pr_documentation_tests.txt"
},
],
tests_to_run="$(cat pr_documentation_tests.txt)", # noqa
pytest_options={"-doctest-modules": None, "doctest-glob": "*.md", "dist": "loadfile", "rvsA": None},
@ -353,49 +414,121 @@ doc_test_job = CircleCIJob(
pytest_num_workers=1,
)
REGULAR_TESTS = [torch_and_tf_job, torch_and_flax_job, torch_job, tf_job, flax_job, hub_job, onnx_job, tokenization_job, processor_job, generate_job, non_model_job] # fmt: skip
EXAMPLES_TESTS = [examples_torch_job, examples_tensorflow_job]
PIPELINE_TESTS = [pipelines_torch_job, pipelines_tf_job]
REGULAR_TESTS = [
torch_and_tf_job,
torch_and_flax_job,
torch_job,
tf_job,
flax_job,
custom_tokenizers_job,
hub_job,
onnx_job,
exotic_models_job,
tokenization_job
]
EXAMPLES_TESTS = [
examples_torch_job,
examples_tensorflow_job,
]
PIPELINE_TESTS = [
pipelines_torch_job,
pipelines_tf_job,
]
REPO_UTIL_TESTS = [repo_utils_job]
DOC_TESTS = [doc_test_job]
ALL_TESTS = REGULAR_TESTS + EXAMPLES_TESTS + PIPELINE_TESTS + REPO_UTIL_TESTS + DOC_TESTS + [custom_tokenizers_job] + [exotic_models_job] # fmt: skip
def create_circleci_config(folder=None):
if folder is None:
folder = os.getcwd()
# Used in CircleCIJob.to_dict() to expand the test list (for using parallelism)
os.environ["test_preparation_dir"] = folder
jobs = [k for k in ALL_TESTS if os.path.isfile(os.path.join("test_preparation" , f"{k.job_name}_test_list.txt") )]
print("The following jobs will be run ", jobs)
jobs = []
all_test_file = os.path.join(folder, "test_list.txt")
if os.path.exists(all_test_file):
with open(all_test_file) as f:
all_test_list = f.read()
else:
all_test_list = []
if len(all_test_list) > 0:
jobs.extend(PIPELINE_TESTS)
test_file = os.path.join(folder, "filtered_test_list.txt")
if os.path.exists(test_file):
with open(test_file) as f:
test_list = f.read()
else:
test_list = []
if len(test_list) > 0:
jobs.extend(REGULAR_TESTS)
extended_tests_to_run = set(test_list.split())
# Extend the test files for cross test jobs
for job in jobs:
if job.job_name in ["tests_torch_and_tf", "tests_torch_and_flax"]:
for test_path in copy.copy(extended_tests_to_run):
dir_path, fn = os.path.split(test_path)
if fn.startswith("test_modeling_tf_"):
fn = fn.replace("test_modeling_tf_", "test_modeling_")
elif fn.startswith("test_modeling_flax_"):
fn = fn.replace("test_modeling_flax_", "test_modeling_")
else:
if job.job_name == "test_torch_and_tf":
fn = fn.replace("test_modeling_", "test_modeling_tf_")
elif job.job_name == "test_torch_and_flax":
fn = fn.replace("test_modeling_", "test_modeling_flax_")
new_test_file = str(os.path.join(dir_path, fn))
if os.path.isfile(new_test_file):
if new_test_file not in extended_tests_to_run:
extended_tests_to_run.add(new_test_file)
extended_tests_to_run = sorted(extended_tests_to_run)
for job in jobs:
if job.job_name in ["tests_torch_and_tf", "tests_torch_and_flax"]:
job.tests_to_run = extended_tests_to_run
fn = "filtered_test_list_cross_tests.txt"
f_path = os.path.join(folder, fn)
with open(f_path, "w") as fp:
fp.write(" ".join(extended_tests_to_run))
example_file = os.path.join(folder, "examples_test_list.txt")
if os.path.exists(example_file) and os.path.getsize(example_file) > 0:
with open(example_file, "r", encoding="utf-8") as f:
example_tests = f.read()
for job in EXAMPLES_TESTS:
framework = job.name.replace("examples_", "").replace("torch", "pytorch")
if example_tests == "all":
job.tests_to_run = [f"examples/{framework}"]
else:
job.tests_to_run = [f for f in example_tests.split(" ") if f.startswith(f"examples/{framework}")]
if len(job.tests_to_run) > 0:
jobs.append(job)
doctest_file = os.path.join(folder, "doctest_list.txt")
if os.path.exists(doctest_file):
with open(doctest_file) as f:
doctest_list = f.read()
else:
doctest_list = []
if len(doctest_list) > 0:
jobs.extend(DOC_TESTS)
repo_util_file = os.path.join(folder, "test_repo_utils.txt")
if os.path.exists(repo_util_file) and os.path.getsize(repo_util_file) > 0:
jobs.extend(REPO_UTIL_TESTS)
if len(jobs) == 0:
jobs = [EmptyJob()]
else:
print("Full list of job name inputs", {j.job_name + "_test_list":{"type":"string", "default":''} for j in jobs})
# Add a job waiting all the test jobs and aggregate their test summary files at the end
collection_job = EmptyJob()
collection_job.job_name = "collection_job"
jobs = [collection_job] + jobs
config = {
"version": "2.1",
"parameters": {
# Only used to accept the parameters from the trigger
"nightly": {"type": "boolean", "default": False},
"tests_to_run": {"type": "string", "default": ''},
**{j.job_name + "_test_list":{"type":"string", "default":''} for j in jobs},
**{j.job_name + "_parallelism":{"type":"integer", "default":1} for j in jobs},
},
"jobs": {j.job_name: j.to_dict() for j in jobs}
config = {"version": "2.1"}
config["parameters"] = {
# Only used to accept the parameters from the trigger
"nightly": {"type": "boolean", "default": False},
"tests_to_run": {"type": "string", "default": test_list},
}
if "CIRCLE_TOKEN" in os.environ:
# For private forked repo. (e.g. new model addition)
config["workflows"] = {"version": 2, "run_tests": {"jobs": [{j.job_name: {"context": ["TRANSFORMERS_CONTEXT"]}} for j in jobs]}}
else:
# For public repo. (e.g. `transformers`)
config["workflows"] = {"version": 2, "run_tests": {"jobs": [j.job_name for j in jobs]}}
config["jobs"] = {j.job_name: j.to_dict() for j in jobs}
config["workflows"] = {"version": 2, "run_tests": {"jobs": [j.job_name for j in jobs]}}
with open(os.path.join(folder, "generated_config.yml"), "w") as f:
f.write(yaml.dump(config, sort_keys=False, default_flow_style=False).replace("' << pipeline", " << pipeline").replace(">> '", " >>"))
f.write(yaml.dump(config, indent=2, width=1000000, sort_keys=False))
if __name__ == "__main__":

View File

@ -67,4 +67,4 @@ def main():
if __name__ == "__main__":
main()
main()

12
.coveragerc Normal file
View File

@ -0,0 +1,12 @@
[run]
source=transformers
omit =
# skip convertion scripts from testing for now
*/convert_*
*/__main__.py
[report]
exclude_lines =
pragma: no cover
raise
except
register_parameter

View File

@ -1,17 +1,6 @@
name: "\U0001F41B Bug Report"
description: Submit a bug report to help us improve transformers
labels: [ "bug" ]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report! 🤗
Before you submit your bug report:
- If it is your first time submitting, be sure to check our [bug report guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#did-you-find-a-bug)
- Try our [docs bot](https://huggingface.co/spaces/huggingchat/hf-docs-chat) -- it might be able to help you with your issue
- type: textarea
id: system-info
attributes:
@ -28,50 +17,50 @@ body:
description: |
Your issue will be replied to more quickly if you can figure out the right person to tag with @
If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
All issues are read by one of the core maintainers, so if you don't know who to tag, just leave this blank and
a core maintainer will ping the right person.
Please tag fewer than 3 people.
Models:
- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @ylacombe, @eustlb
- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier
Library:
- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker and @itazap
- trainer: @muellerzr @SunMarc
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @pacman100
Integrations:
- deepspeed: HF Trainer/Accelerate: @muellerzr
- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber
- quantization (bitsandbytes, autogpt): @SunMarc and @younesbelkada
Documentation: @stevhliu
Model hub:
- for issues with a model, report at https://discuss.huggingface.co/ and tag the model's creator.
HF projects:
- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
Maintained examples (not research project or legacy):
- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1
@ -106,18 +95,17 @@ body:
label: Reproduction
description: |
Please provide a code sample that reproduces the problem you ran into. It can be a Colab link or just a code snippet.
Please include relevant config information with your code, for example your Trainers, TRL, Peft, and DeepSpeed configs.
If you have code snippets, error messages, stack traces please provide them here as well.
Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
placeholder: |
Steps to reproduce the behavior:
1.
2.
3.
- type: textarea
id: expected-behavior

View File

@ -1,6 +1,6 @@
name: "\U0001F680 Feature request"
description: Submit a proposal/request for a new transformers feature
labels: [ "Feature request" ]
labels: [ "feature" ]
body:
- type: textarea
id: feature-request
@ -19,7 +19,7 @@ body:
label: Motivation
description: |
Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too.
- type: textarea
id: contribution

View File

@ -34,7 +34,7 @@ Some notes:
## Tutorial section
- [ ] [pipeline_tutorial.md](https://github.com/huggingface/transformers/blob/main/docs/source/en/pipeline_tutorial.md)
- [ ] [autoclass_tutorial.md](https://github.com/huggingface/transformers/blob/main/docs/source/en/autoclass_tutorial.md)
- [ ] [autoclass_tutorial.md](https://github.com/huggingface/transformers/blob/master/docs/source/autoclass_tutorial.md)
- [ ] [preprocessing.md](https://github.com/huggingface/transformers/blob/main/docs/source/en/preprocessing.md)
- [ ] [training.md](https://github.com/huggingface/transformers/blob/main/docs/source/en/training.md)
- [ ] [accelerate.md](https://github.com/huggingface/transformers/blob/main/docs/source/en/accelerate.md)

View File

@ -39,29 +39,28 @@ members/contributors who may be interested in your PR.
Models:
- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @ylacombe, @eustlb
- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier
Library:
- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1
- trainer: @muellerzr and @pacman100
Integrations:
- deepspeed: HF Trainer/Accelerate: @muellerzr
- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber
- quantization (bitsandbytes, autogpt): @SunMarc and @younesbelkada
Documentation: @stevhliu
Documentation: @stevhliu and @MKhalusova
HF projects:

View File

@ -23,7 +23,7 @@ jobs:
sudo apt -y update && sudo apt install -y libsndfile1-dev
- name: Load cached virtual environment
uses: actions/cache@v4
uses: actions/cache@v2
id: cache
with:
path: ~/venv/

View File

@ -1,75 +0,0 @@
name: Self-hosted runner (benchmark)
on:
push:
branches: [main]
pull_request:
types: [ opened, labeled, reopened, synchronize ]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
env:
HF_HOME: /mnt/cache
jobs:
benchmark:
name: Benchmark
strategy:
matrix:
# group: [aws-g5-4xlarge-cache, aws-p4d-24xlarge-plus] (A100 runner is not enabled)
group: [aws-g5-4xlarge-cache]
runs-on:
group: ${{ matrix.group }}
if: |
(github.event_name == 'pull_request' && contains( github.event.pull_request.labels.*.name, 'run-benchmark') )||
(github.event_name == 'push' && github.ref == 'refs/heads/main')
container:
image: huggingface/transformers-pytorch-gpu
options: --gpus all --privileged --ipc host
steps:
- name: Get repo
uses: actions/checkout@v4
with:
ref: ${{ github.event.pull_request.head.sha || github.sha }}
- name: Install libpq-dev & psql
run: |
apt update
apt install -y libpq-dev postgresql-client
- name: Install benchmark script dependencies
run: python3 -m pip install -r benchmark/requirements.txt
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e ".[torch]"
- name: Run database init script
run: |
psql -f benchmark/init_db.sql
env:
PGDATABASE: metrics
PGHOST: ${{ secrets.TRANSFORMERS_BENCHMARKS_PGHOST }}
PGUSER: transformers_benchmarks
PGPASSWORD: ${{ secrets.TRANSFORMERS_BENCHMARKS_PGPASSWORD }}
- name: Run benchmark
run: |
git config --global --add safe.directory /__w/transformers/transformers
if [ "$GITHUB_EVENT_NAME" = "pull_request" ]; then
commit_id=$(echo "${{ github.event.pull_request.head.sha }}")
elif [ "$GITHUB_EVENT_NAME" = "push" ]; then
commit_id=$GITHUB_SHA
fi
commit_msg=$(git show -s --format=%s | cut -c1-70)
python3 benchmark/benchmarks_entrypoint.py "${{ github.head_ref || github.ref_name }}" "$commit_id" "$commit_msg"
env:
HF_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
# Enable this to see debug logs
# HF_HUB_VERBOSITY: debug
# TRANSFORMERS_VERBOSITY: debug
PGHOST: ${{ secrets.TRANSFORMERS_BENCHMARKS_PGHOST }}
PGUSER: transformers_benchmarks
PGPASSWORD: ${{ secrets.TRANSFORMERS_BENCHMARKS_PGPASSWORD }}

View File

@ -3,7 +3,7 @@ name: Build pr ci-docker
on:
push:
branches:
- push-ci-image # for now let's only build on this branch
- change-ci # for now let's only build on this branch
repository_dispatch:
workflow_call:
inputs:
@ -22,24 +22,14 @@ jobs:
build:
runs-on: ubuntu-22.04
if: ${{ contains(github.event.head_commit.message, '[build-ci-image]') || contains(github.event.head_commit.message, '[push-ci-image]') && '!cancelled()' || github.event_name == 'schedule' }}
if: ${{ contains(github.event.head_commit.message, '[push-ci-image]') && '!cancelled()' }}
strategy:
matrix:
file: ["quality", "consistency", "custom-tokenizers", "torch-light", "tf-light", "exotic-models", "torch-tf-light", "torch-jax-light", "jax-light", "examples-torch", "examples-tf"]
continue-on-error: true
continue-on-error: true
steps:
-
name: Set tag
run: |
if ${{contains(github.event.head_commit.message, '[build-ci-image]')}}; then
echo "TAG=huggingface/transformers-${{ matrix.file }}:dev" >> "$GITHUB_ENV"
echo "setting it to DEV!"
else
echo "TAG=huggingface/transformers-${{ matrix.file }}" >> "$GITHUB_ENV"
fi
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@ -60,18 +50,5 @@ jobs:
build-args: |
REF=${{ github.sha }}
file: "./docker/${{ matrix.file }}.dockerfile"
push: ${{ contains(github.event.head_commit.message, 'ci-image]') || github.event_name == 'schedule' }}
tags: ${{ env.TAG }}
notify:
runs-on: ubuntu-22.04
if: ${{ contains(github.event.head_commit.message, '[build-ci-image]') || contains(github.event.head_commit.message, '[push-ci-image]') && '!cancelled()' || github.event_name == 'schedule' }}
steps:
- name: Post to Slack
if: ${{ contains(github.event.head_commit.message, '[push-ci-image]') && github.event_name != 'schedule' }}
uses: huggingface/hf-workflows/.github/actions/post-slack@main
with:
slack_channel: "#transformers-ci-circleci-images"
title: 🤗 New docker images for CircleCI are pushed.
status: ${{ job.status }}
slack_token: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
push: true
tags: huggingface/transformers-${{ matrix.file }}

View File

@ -3,7 +3,7 @@ name: Build docker images (scheduled)
on:
push:
branches:
- check_doc_image
- build_ci_docker_image*
repository_dispatch:
workflow_call:
inputs:
@ -18,12 +18,127 @@ concurrency:
cancel-in-progress: false
jobs:
latest-docker:
name: "Latest PyTorch + TensorFlow [dev]"
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-all-latest-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-all-latest-gpu${{ inputs.image_postfix }}
# Push CI images still need to be re-built daily
-
name: Build and push (for Push CI) in a daily basis
# This condition allows `schedule` events, or `push` events that trigger this workflow NOT via `workflow_call`.
# The later case is useful for manual image building for debugging purpose. Use another tag in this case!
if: inputs.image_postfix != '-push-ci'
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-all-latest-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-all-latest-gpu-push-ci
latest-torch-deepspeed-docker:
name: "Latest PyTorch + DeepSpeed"
runs-on: [intel-cpu, 8-cpu, ci]
steps:
- name: Cleanup disk
run: |
sudo ls -l /usr/local/lib/
sudo ls -l /usr/share/
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
sudo rm -rf /usr/local/lib/android
sudo rm -rf /usr/share/dotnet
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-deepspeed-latest-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-deepspeed-latest-gpu${{ inputs.image_postfix }}
# Can't build 2 images in a single job `latest-torch-deepspeed-docker` (for `nvcr.io/nvidia`)
latest-torch-deepspeed-docker-for-push-ci-daily-build:
name: "Latest PyTorch + DeepSpeed (Push CI - Daily Build)"
runs-on: [intel-cpu, 8-cpu, ci]
steps:
- name: Cleanup disk
run: |
sudo ls -l /usr/local/lib/
sudo ls -l /usr/share/
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
sudo rm -rf /usr/local/lib/android
sudo rm -rf /usr/share/dotnet
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
# Push CI images still need to be re-built daily
-
name: Build and push (for Push CI) in a daily basis
# This condition allows `schedule` events, or `push` events that trigger this workflow NOT via `workflow_call`.
# The later case is useful for manual image building for debugging purpose. Use another tag in this case!
if: inputs.image_postfix != '-push-ci'
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-deepspeed-latest-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-deepspeed-latest-gpu-push-ci
doc-builder:
name: "Doc builder"
# Push CI doesn't need this image
if: inputs.image_postfix != '-push-ci'
runs-on:
group: aws-general-8-plus
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
@ -45,11 +160,174 @@ jobs:
push: true
tags: huggingface/transformers-doc-builder
- name: Post to Slack
if: always()
uses: huggingface/hf-workflows/.github/actions/post-slack@main
latest-pytorch:
name: "Latest PyTorch [dev]"
# Push CI doesn't need this image
if: inputs.image_postfix != '-push-ci'
runs-on: [intel-cpu, 8-cpu, ci]
steps:
- name: Cleanup disk
run: |
sudo ls -l /usr/local/lib/
sudo ls -l /usr/share/
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
sudo rm -rf /usr/local/lib/android
sudo rm -rf /usr/share/dotnet
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
slack_channel: ${{ secrets.CI_SLACK_CHANNEL_DOCKER }}
title: 🤗 Results of the huggingface/transformers-doc-builder docker build
status: ${{ job.status }}
slack_token: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-gpu
latest-pytorch-amd:
name: "Latest PyTorch (AMD) [dev]"
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-amd-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-amd-gpu${{ inputs.image_postfix }}
# Push CI images still need to be re-built daily
-
name: Build and push (for Push CI) in a daily basis
# This condition allows `schedule` events, or `push` events that trigger this workflow NOT via `workflow_call`.
# The later case is useful for manual image building for debugging purpose. Use another tag in this case!
if: inputs.image_postfix != '-push-ci'
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-amd-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-amd-gpu-push-ci
latest-tensorflow:
name: "Latest TensorFlow [dev]"
# Push CI doesn't need this image
if: inputs.image_postfix != '-push-ci'
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-tensorflow-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-tensorflow-gpu
latest-pytorch-deepspeed-amd:
name: "PyTorch + DeepSpeed (AMD) [dev]"
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-deepspeed-amd-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-deepspeed-amd-gpu${{ inputs.image_postfix }}
# Push CI images still need to be re-built daily
-
name: Build and push (for Push CI) in a daily basis
# This condition allows `schedule` events, or `push` events that trigger this workflow NOT via `workflow_call`.
# The later case is useful for manual image building for debugging purpose. Use another tag in this case!
if: inputs.image_postfix != '-push-ci'
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-pytorch-deepspeed-amd-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-deepspeed-amd-gpu-push-ci
latest-quantization-torch-docker:
name: "Latest Pytorch + Quantization [dev]"
# Push CI doesn't need this image
if: inputs.image_postfix != '-push-ci'
runs-on: [intel-cpu, 8-cpu, ci]
steps:
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
-
name: Check out code
uses: actions/checkout@v4
-
name: Login to DockerHub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
-
name: Build and push
uses: docker/build-push-action@v5
with:
context: ./docker/transformers-quantization-latest-gpu
build-args: |
REF=main
push: true
tags: huggingface/transformers-quantization-latest-gpu${{ inputs.image_postfix }}

View File

@ -13,9 +13,18 @@ concurrency:
jobs:
latest-with-torch-nightly-docker:
name: "Nightly PyTorch + Stable TensorFlow"
runs-on:
group: aws-general-8-plus
runs-on: ubuntu-22.04
steps:
- name: Cleanup disk
run: |
sudo ls -l /usr/local/lib/
sudo ls -l /usr/share/
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
sudo rm -rf /usr/local/lib/android
sudo rm -rf /usr/share/dotnet
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
@ -41,9 +50,18 @@ jobs:
nightly-torch-deepspeed-docker:
name: "Nightly PyTorch + DeepSpeed"
runs-on:
group: aws-general-8-plus
runs-on: ubuntu-22.04
steps:
- name: Cleanup disk
run: |
sudo ls -l /usr/local/lib/
sudo ls -l /usr/share/
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
sudo rm -rf /usr/local/lib/android
sudo rm -rf /usr/share/dotnet
sudo du -sh /usr/local/lib/
sudo du -sh /usr/share/
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
@ -64,4 +82,4 @@ jobs:
build-args: |
REF=main
push: true
tags: huggingface/transformers-pytorch-deepspeed-nightly-gpu
tags: huggingface/transformers-pytorch-deepspeed-nightly-gpu

View File

@ -16,8 +16,7 @@ jobs:
fail-fast: false
matrix:
version: ["1.13", "1.12", "1.11"]
runs-on:
group: aws-general-8-plus
runs-on: ubuntu-22.04
steps:
-
name: Set up Docker Buildx
@ -61,8 +60,7 @@ jobs:
fail-fast: false
matrix:
version: ["2.11", "2.10", "2.9", "2.8", "2.7", "2.6", "2.5"]
runs-on:
group: aws-general-8-plus
runs-on: ubuntu-22.04
steps:
-
name: Set up Docker Buildx

View File

@ -1,7 +1,6 @@
name: Build documentation
on:
workflow_dispatch:
push:
branches:
- main
@ -16,7 +15,7 @@ jobs:
commit_sha: ${{ github.sha }}
package: transformers
notebook_folder: transformers_doc
languages: ar de en es fr hi it ko pt tr zh ja te
languages: de en es fr hi it ko pt tr zh ja te
custom_container: huggingface/transformers-doc-builder
secrets:
token: ${{ secrets.HUGGINGFACE_PUSH }}

View File

@ -14,5 +14,5 @@ jobs:
commit_sha: ${{ github.event.pull_request.head.sha }}
pr_number: ${{ github.event.number }}
package: transformers
languages: ar de en es fr hi it ko pt tr zh ja te
languages: de en es fr hi it ko pt tr zh ja te
custom_container: huggingface/transformers-doc-builder

View File

@ -1,129 +0,0 @@
name: Process failed tests
on:
workflow_call:
inputs:
docker:
required: true
type: string
start_sha:
required: true
type: string
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
# For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
# This token is created under the bot `hf-transformers-bot`.
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
run_models_gpu:
name: " "
runs-on:
group: aws-g4dn-2xlarge-cache
container:
image: ${{ inputs.docker }}
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- uses: actions/download-artifact@v4
with:
name: ci_results_run_models_gpu
path: /transformers/ci_results_run_models_gpu
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Get target commit
working-directory: /transformers/utils
run: |
echo "END_SHA=$(TOKEN=${{ secrets.ACCESS_REPO_INFO_TOKEN }} python3 -c 'import os; from get_previous_daily_ci import get_last_daily_ci_run_commit; commit=get_last_daily_ci_run_commit(token=os.environ["TOKEN"]); print(commit)')" >> $GITHUB_ENV
- name: Checkout to `start_sha`
working-directory: /transformers
run: git fetch && git checkout ${{ inputs.start_sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Check failed tests
working-directory: /transformers
run: python3 utils/check_bad_commit.py --start_commit ${{ inputs.start_sha }} --end_commit ${{ env.END_SHA }} --file ci_results_run_models_gpu/new_model_failures.json --output_file new_model_failures_with_bad_commit.json
- name: Show results
working-directory: /transformers
run: |
ls -l new_model_failures_with_bad_commit.json
cat new_model_failures_with_bad_commit.json
- name: Checkout back
working-directory: /transformers
run: |
git checkout ${{ inputs.start_sha }}
- name: Process report
shell: bash
working-directory: /transformers
env:
TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN: ${{ secrets.TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN }}
run: |
python3 utils/process_bad_commit_report.py
- name: Process report
shell: bash
working-directory: /transformers
env:
TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN: ${{ secrets.TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN }}
run: |
{
echo 'REPORT_TEXT<<EOF'
python3 utils/process_bad_commit_report.py
echo EOF
} >> "$GITHUB_ENV"
- name: Send processed report
if: ${{ !endsWith(env.REPORT_TEXT, '{}') }}
uses: slackapi/slack-github-action@6c661ce58804a1a20f6dc5fbee7f0381b469e001
with:
# Slack channel id, channel name, or user id to post message.
# See also: https://api.slack.com/methods/chat.postMessage#channels
channel-id: '#transformers-ci-feedback-tests'
# For posting a rich message using Block Kit
payload: |
{
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "${{ env.REPORT_TEXT }}"
}
}
]
}
env:
SLACK_BOT_TOKEN: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}

View File

@ -23,7 +23,7 @@ jobs:
- uses: actions/checkout@v4
- name: Set up Python 3.8
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
# Semantic version range syntax or exact version of a Python version
python-version: '3.8'

View File

@ -27,8 +27,7 @@ jobs:
fail-fast: false
matrix:
split_keys: ${{ fromJson(inputs.split_keys) }}
runs-on:
group: aws-g4dn-2xlarge-cache
runs-on: [single-gpu, nvidia-gpu, t4, ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/

View File

@ -14,8 +14,7 @@ env:
jobs:
setup:
name: Setup
runs-on:
group: aws-g4dn-2xlarge-cache
runs-on: [single-gpu, nvidia-gpu, t4, ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -86,4 +85,4 @@ jobs:
uses: actions/upload-artifact@v4
with:
name: doc_test_results
path: doc_test_results
path: doc_test_results

View File

@ -12,12 +12,6 @@ on:
slice_id:
required: true
type: number
runner:
required: true
type: string
docker:
required: true
type: string
env:
HF_HOME: /mnt/cache
@ -37,14 +31,12 @@ jobs:
run_models_gpu:
name: " "
strategy:
max-parallel: 8
fail-fast: false
matrix:
folders: ${{ fromJson(inputs.folder_slices)[inputs.slice_id] }}
runs-on:
group: '${{ inputs.machine_type }}'
runs-on: ['${{ inputs.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: ${{ inputs.docker }}
image: huggingface/transformers-all-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Echo input and matrix info
@ -73,18 +65,6 @@ jobs:
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update / Install some packages (for Past CI)
if: ${{ contains(inputs.docker, '-past-') }}
working-directory: /transformers
run: |
python3 -m pip install -U datasets
- name: Update / Install some packages (for Past CI)
if: ${{ contains(inputs.docker, '-past-') && contains(inputs.docker, '-pytorch-') }}
working-directory: /transformers
run: |
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: NVIDIA-SMI
run: |
nvidia-smi
@ -98,42 +78,25 @@ jobs:
working-directory: /transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ inputs.machine_type }}"
if [ "${{ inputs.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ inputs.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ inputs.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -rsfE -v --make-reports=${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
run: python3 -m pytest -rs -v --make-reports=${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
run: cat /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: Run test
shell: bash
run: |
mkdir -p /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports"
mkdir -p /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ inputs.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
name: ${{ inputs.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports

View File

@ -1,129 +0,0 @@
name: model jobs
on:
workflow_call:
inputs:
folder_slices:
required: true
type: string
machine_type:
required: true
type: string
slice_id:
required: true
type: number
runner:
required: true
type: string
docker:
required: true
type: string
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
# For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
# This token is created under the bot `hf-transformers-bot`.
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
run_models_gpu:
name: " "
strategy:
max-parallel: 1 # For now, not to parallelize. Can change later if it works well.
fail-fast: false
matrix:
folders: ${{ fromJson(inputs.folder_slices)[inputs.slice_id] }}
runs-on: ['${{ inputs.machine_type }}', self-hosted, amd-gpu, '${{ inputs.runner }}']
container:
image: ${{ inputs.docker }}
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Echo input and matrix info
shell: bash
run: |
echo "${{ inputs.folder_slices }}"
echo "${{ matrix.folders }}"
echo "${{ toJson(fromJson(inputs.folder_slices)[inputs.slice_id]) }}"
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update / Install some packages (for Past CI)
if: ${{ contains(inputs.docker, '-past-') }}
working-directory: /transformers
run: |
python3 -m pip install -U datasets
- name: Update / Install some packages (for Past CI)
if: ${{ contains(inputs.docker, '-past-') && contains(inputs.docker, '-pytorch-') }}
working-directory: /transformers
run: |
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -rsfE -v --make-reports=${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }} -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: Run test
shell: bash
run: |
mkdir -p /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ inputs.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ inputs.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ inputs.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports

View File

@ -5,6 +5,7 @@ on:
branches: [ main ]
env:
IS_GITHUB_CI: "1"
OUTPUT_SLACK_CHANNEL_ID: "C06L2SGMEEA"
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
HF_HOME: /mnt/cache
@ -52,8 +53,7 @@ jobs:
test_modified_files:
needs: get_modified_models
name: Slow & FA2 tests
runs-on:
group: aws-g5-4xlarge-cache
runs-on: [single-gpu, nvidia-gpu, a10, ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus all --privileged --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -86,7 +86,7 @@ jobs:
- name: Run FA2 tests
id: run_fa2_tests
run:
pytest -rsfE -m "flash_attn_test" --make-reports=${{ matrix.model-name }}_fa2_tests/ tests/${{ matrix.model-name }}/test_modeling_*
pytest -rs -m "flash_attn_test" --make-reports=${{ matrix.model-name }}_fa2_tests/ tests/${{ matrix.model-name }}/test_modeling_*
- name: "Test suite reports artifacts: ${{ matrix.model-name }}_fa2_tests"
if: ${{ always() }}
@ -108,7 +108,7 @@ jobs:
id: run_integration_tests
if: always()
run:
pytest -rsfE -k "IntegrationTest" --make-reports=tests_integration_${{ matrix.model-name }} tests/${{ matrix.model-name }}/test_modeling_*
pytest -rs -k "IntegrationTest" --make-reports=tests_integration_${{ matrix.model-name }} tests/${{ matrix.model-name }}/test_modeling_*
- name: "Test suite reports artifacts: tests_integration_${{ matrix.model-name }}"
if: ${{ always() }}

View File

@ -19,7 +19,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v1
- name: Install miniconda
uses: conda-incubator/setup-miniconda@v2

View File

@ -1,417 +0,0 @@
name: PR comment GitHub CI
on:
issue_comment:
types:
- created
branches-ignore:
- main
concurrency:
group: ${{ github.workflow }}-${{ github.event.issue.number }}-${{ startsWith(github.event.comment.body, 'run-slow') || startsWith(github.event.comment.body, 'run slow') || startsWith(github.event.comment.body, 'run_slow') }}
cancel-in-progress: true
permissions: read-all
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
# For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
# This token is created under the bot `hf-transformers-bot`.
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
get-pr-number:
runs-on: ubuntu-22.04
name: Get PR number
# For security: only allow team members to run
if: ${{ github.event.issue.state == 'open' && contains(fromJSON('["ydshieh", "ArthurZucker", "zucchini-nlp", "qubvel", "molbap", "gante", "LysandreJik", "Cyrilvallez", "Rocketknight1", "SunMarc", "muellerzr"]'), github.actor) && (startsWith(github.event.comment.body, 'run-slow') || startsWith(github.event.comment.body, 'run slow') || startsWith(github.event.comment.body, 'run_slow')) }}
outputs:
PR_NUMBER: ${{ steps.set_pr_number.outputs.PR_NUMBER }}
steps:
- name: Get PR number
shell: bash
run: |
if [[ "${{ github.event.issue.number }}" != "" && "${{ github.event.issue.pull_request }}" != "" ]]; then
echo "PR_NUMBER=${{ github.event.issue.number }}" >> $GITHUB_ENV
else
echo "PR_NUMBER=" >> $GITHUB_ENV
fi
- name: Check PR number
shell: bash
run: |
echo "${{ env.PR_NUMBER }}"
- name: Set PR number
id: set_pr_number
run: echo "PR_NUMBER=${{ env.PR_NUMBER }}" >> "$GITHUB_OUTPUT"
get-sha:
runs-on: ubuntu-22.04
needs: get-pr-number
if: ${{ needs.get-pr-number.outputs.PR_NUMBER != ''}}
outputs:
PR_HEAD_SHA: ${{ steps.get_sha.outputs.PR_HEAD_SHA }}
PR_MERGE_SHA: ${{ steps.get_sha.outputs.PR_MERGE_SHA }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: "0"
ref: "refs/pull/${{needs.get-pr-number.outputs.PR_NUMBER}}/merge"
- name: Get SHA (and verify timestamps against the issue comment date)
id: get_sha
env:
PR_NUMBER: ${{ needs.get-pr-number.outputs.PR_NUMBER }}
COMMENT_DATE: ${{ github.event.comment.created_at }}
run: |
git fetch origin refs/pull/$PR_NUMBER/head:refs/remotes/pull/$PR_NUMBER/head
git checkout refs/remotes/pull/$PR_NUMBER/head
echo "PR_HEAD_SHA: $(git log -1 --format=%H)"
echo "PR_HEAD_SHA=$(git log -1 --format=%H)" >> "$GITHUB_OUTPUT"
git fetch origin refs/pull/$PR_NUMBER/merge:refs/remotes/pull/$PR_NUMBER/merge
git checkout refs/remotes/pull/$PR_NUMBER/merge
echo "PR_MERGE_SHA: $(git log -1 --format=%H)"
echo "PR_MERGE_SHA=$(git log -1 --format=%H)" >> "$GITHUB_OUTPUT"
PR_MERGE_COMMIT_TIMESTAMP=$(git log -1 --date=unix --format=%cd)
echo "PR_MERGE_COMMIT_TIMESTAMP: $PR_MERGE_COMMIT_TIMESTAMP"
COMMENT_TIMESTAMP=$(date -d "${COMMENT_DATE}" +"%s")
echo "COMMENT_DATE: $COMMENT_DATE"
echo "COMMENT_TIMESTAMP: $COMMENT_TIMESTAMP"
if [ $COMMENT_TIMESTAMP -le $PR_MERGE_COMMIT_TIMESTAMP ]; then
echo "Last commit on the pull request is newer than the issue comment triggering this run! Abort!";
exit -1;
fi
# use a python script to handle this complex logic
# case 1: `run-slow` (auto. infer with limited number of models, but in particular, new model)
# case 2: `run-slow model_1, model_2`
get-tests:
runs-on: ubuntu-22.04
needs: [get-pr-number, get-sha]
if: ${{ needs.get-pr-number.outputs.PR_NUMBER != ''}}
outputs:
models: ${{ steps.models_to_run.outputs.models }}
quantizations: ${{ steps.models_to_run.outputs.quantizations }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: "0"
ref: "refs/pull/${{needs.get-pr-number.outputs.PR_NUMBER}}/merge"
- name: Verify merge commit SHA
env:
VERIFIED_PR_MERGE_SHA: ${{ needs.get-sha.outputs.PR_MERGE_SHA }}
run: |
PR_MERGE_SHA=$(git log -1 --format=%H)
if [ $PR_MERGE_SHA != $VERIFIED_PR_MERGE_SHA ]; then
echo "The merged commit SHA is not the same as the verified one! Security issue detected, abort the workflow!";
exit -1;
fi
- name: Get models to test
env:
PR_COMMENT: ${{ github.event.comment.body }}
run: |
python -m pip install GitPython
python utils/pr_slow_ci_models.py --message "$PR_COMMENT" | tee output.txt
echo "models=$(tail -n 1 output.txt)" >> $GITHUB_ENV
python utils/pr_slow_ci_models.py --message "$PR_COMMENT" --quantization | tee output2.txt
echo "quantizations=$(tail -n 1 output2.txt)" >> $GITHUB_ENV
- name: Show models to test
id: models_to_run
run: |
echo "${{ env.models }}"
echo "models=${{ env.models }}" >> $GITHUB_ENV
echo "models=${{ env.models }}" >> $GITHUB_OUTPUT
echo "${{ env.quantizations }}"
echo "quantizations=${{ env.quantizations }}" >> $GITHUB_OUTPUT
reply_to_comment:
name: Reply to the comment
if: ${{ needs.get-tests.outputs.models != '[]' || needs.get-tests.outputs.quantizations != '[]' }}
needs: [get-pr-number, get-tests]
permissions:
pull-requests: write
runs-on: ubuntu-22.04
steps:
- name: Reply to the comment
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
MODELS: ${{ needs.get-tests.outputs.models }}
BODY: "This comment contains run-slow, running the specified jobs:\n\nmodels: ${{ needs.get-tests.outputs.models }}\nquantizations: ${{ needs.get-tests.outputs.quantizations }}"
run: |
gh api \
--method POST \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
repos/${{ github.repository }}/issues/${{ needs.get-pr-number.outputs.PR_NUMBER }}/comments \
-f "body=This comment contains run-slow, running the specified jobs: ${{ env.BODY }} ..."
create_run:
name: Create run
if: ${{ needs.get-tests.outputs.models != '[]' || needs.get-tests.outputs.quantizations != '[]' }}
needs: [get-sha, get-tests, reply_to_comment]
permissions:
statuses: write
runs-on: ubuntu-22.04
steps:
- name: Create Run
id: create_run
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Create a commit status (pending) for a run of this workflow. The status has to be updated later in `update_run_status`.
# See https://docs.github.com/en/rest/commits/statuses?apiVersion=2022-11-28#create-a-commit-status
GITHUB_RUN_URL: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}
run: |
gh api \
--method POST \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
repos/${{ github.repository }}/statuses/${{ needs.get-sha.outputs.PR_HEAD_SHA }} \
-f "target_url=$GITHUB_RUN_URL" -f "state=pending" -f "description=Slow CI job" -f "context=pytest/custom-tests"
run_models_gpu:
name: Run all tests for the model
if: ${{ needs.get-tests.outputs.models != '[]' }}
needs: [get-pr-number, get-sha, get-tests, create_run]
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.get-tests.outputs.models) }}
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Echo input and matrix info
shell: bash
run: |
echo "${{ matrix.folders }}"
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Checkout to PR merge commit
working-directory: /transformers
run: |
git fetch origin refs/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge:refs/remotes/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge
git checkout refs/remotes/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge
git log -1 --format=%H
- name: Verify merge commit SHA
env:
VERIFIED_PR_MERGE_SHA: ${{ needs.get-sha.outputs.PR_MERGE_SHA }}
working-directory: /transformers
run: |
PR_MERGE_SHA=$(git log -1 --format=%H)
if [ $PR_MERGE_SHA != $VERIFIED_PR_MERGE_SHA ]; then
echo "The merged commit SHA is not the same as the verified one! Security issue detected, abort the workflow!";
exit -1;
fi
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: |
export CUDA_VISIBLE_DEVICES="$(python3 utils/set_cuda_devices_for_ci.py --test_folder ${{ matrix.folders }})"
echo $CUDA_VISIBLE_DEVICES
python3 -m pytest -v -rsfE --make-reports=${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: Make sure report directory exists
shell: bash
run: |
mkdir -p /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
run_quantization_torch_gpu:
name: Run all tests for a quantization
if: ${{ needs.get-tests.outputs.quantizations != '[]' }}
needs: [get-pr-number, get-sha, get-tests, create_run]
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.get-tests.outputs.quantizations) }}
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
container:
image: huggingface/transformers-quantization-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Echo folder ${{ matrix.folders }}
shell: bash
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'quantization/'/'quantization_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Checkout to PR merge commit
working-directory: /transformers
run: |
git fetch origin refs/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge:refs/remotes/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge
git checkout refs/remotes/pull/${{ needs.get-pr-number.outputs.PR_NUMBER }}/merge
git log -1 --format=%H
- name: Verify merge commit SHA
env:
VERIFIED_PR_MERGE_SHA: ${{ needs.get-sha.outputs.PR_MERGE_SHA }}
working-directory: /transformers
run: |
PR_MERGE_SHA=$(git log -1 --format=%H)
if [ $PR_MERGE_SHA != $VERIFIED_PR_MERGE_SHA ]; then
echo "The merged commit SHA is not the same as the verified one! Security issue detected, abort the workflow!";
exit -1;
fi
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run quantization tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -v --make-reports=${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: Make sure report directory exists
shell: bash
run: |
mkdir -p /transformers/reports/${{ env.machine_type }}_run_quantization_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ env.machine_type }}_run_quantization_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ env.machine_type }}_run_quantization_gpu_${{ matrix.folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports
update_run_status:
name: Update Check Run Status
needs: [get-sha, create_run, run_models_gpu, run_quantization_torch_gpu]
permissions:
statuses: write
if: ${{ always() && needs.create_run.result == 'success' }}
runs-on: ubuntu-22.04
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_RUN_URL: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}
STATUS_OK: ${{ contains(fromJSON('["skipped", "success"]'), needs.run_models_gpu.result) && contains(fromJSON('["skipped", "success"]'), needs.run_quantization_torch_gpu.result) }}
steps:
- name: Get `run_models_gpu` job status
run: |
echo "${{ needs.run_models_gpu.result }}"
echo "${{ needs.run_quantization_torch_gpu.result }}"
echo $STATUS_OK
if [ "$STATUS_OK" = "true" ]; then
echo "STATUS=success" >> $GITHUB_ENV
else
echo "STATUS=failure" >> $GITHUB_ENV
fi
- name: Update PR commit statuses
run: |
echo "${{ needs.run_models_gpu.result }}"
echo "${{ env.STATUS }}"
gh api \
--method POST \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
repos/${{ github.repository }}/statuses/${{ needs.get-sha.outputs.PR_HEAD_SHA }} \
-f "target_url=$GITHUB_RUN_URL" -f "state=${{ env.STATUS }}" -f "description=Slow CI job" -f "context=pytest/custom-tests"

View File

@ -1,43 +0,0 @@
name: Self-hosted runner (nightly-ci)
on:
repository_dispatch:
schedule:
- cron: "17 2 * * *"
push:
branches:
- run_nightly_ci*
jobs:
build_nightly_ci_images:
name: Build Nightly CI Docker Images
if: (github.event_name == 'schedule') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_nightly_ci'))
uses: ./.github/workflows/build-nightly-ci-docker-images.yml
secrets: inherit
model-ci:
name: Model CI
needs: [build_nightly_ci_images]
uses: ./.github/workflows/self-scheduled.yml
with:
job: run_models_gpu
slack_report_channel: "#transformers-ci-past-future"
runner: ci
docker: huggingface/transformers-all-latest-torch-nightly-gpu
ci_event: Nightly CI
secrets: inherit
deepspeed-ci:
name: DeepSpeed CI
needs: [build_nightly_ci_images]
uses: ./.github/workflows/self-scheduled.yml
with:
job: run_torch_cuda_extensions_gpu
slack_report_channel: "#transformers-ci-past-future"
runner: ci
# test deepspeed nightly build with the latest release torch
docker: huggingface/transformers-pytorch-deepspeed-latest-gpu
ci_event: Nightly CI
working-directory-prefix: /workspace
secrets: inherit

View File

@ -2,30 +2,65 @@ name: Self-hosted runner (nightly-past-ci-caller)
on:
schedule:
- cron: "17 2,14 * * *"
# 2:17 am on each Sunday and Thursday
- cron: "17 2 * * 0,4"
push:
branches:
- run_nightly_ci*
- run_past_ci*
jobs:
get_number:
name: Get number
runs-on: ubuntu-22.04
outputs:
run_number: ${{ steps.get_number.outputs.run_number }}
steps:
- name: Get number
id: get_number
run: |
echo "${{ github.run_number }}"
echo "$(python3 -c 'print(int(${{ github.run_number }}) % 10)')"
echo "run_number=$(python3 -c 'print(int(${{ github.run_number }}) % 10)')" >> $GITHUB_OUTPUT
build_nightly_ci_images:
name: Build Nightly CI Docker Images
if: (github.event_name == 'schedule') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_nightly_ci'))
uses: ./.github/workflows/build-nightly-ci-docker-images.yml
secrets: inherit
run_nightly_ci:
name: Nightly CI
needs: [build_nightly_ci_images]
uses: ./.github/workflows/self-nightly-scheduled.yml
secrets: inherit
run_past_ci_pytorch_1-13:
name: PyTorch 1.13
if: (cancelled() != true) && ((github.event_name == 'schedule') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci')))
needs: [run_nightly_ci]
uses: ./.github/workflows/self-past.yml
with:
framework: pytorch
version: "1.13"
sha: ${{ github.sha }}
secrets: inherit
run_past_ci_pytorch_1-12:
name: PyTorch 1.12
if: (cancelled() != true) && ((github.event_name == 'schedule') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci')))
needs: [run_past_ci_pytorch_1-13]
uses: ./.github/workflows/self-past.yml
with:
framework: pytorch
version: "1.12"
sha: ${{ github.sha }}
secrets: inherit
run_past_ci_pytorch_1-11:
name: PyTorch 1.11
if: (cancelled() != true) && ((github.event_name == 'schedule') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci')))
needs: [run_past_ci_pytorch_1-12]
uses: ./.github/workflows/self-past.yml
with:
framework: pytorch
version: "1.11"
sha: ${{ github.sha }}
secrets: inherit
run_past_ci_tensorflow_2-11:
name: TensorFlow 2.11
needs: get_number
if: needs.get_number.outputs.run_number == 3 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_pytorch_1-11]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.11"
@ -34,9 +69,9 @@ jobs:
run_past_ci_tensorflow_2-10:
name: TensorFlow 2.10
needs: get_number
if: needs.get_number.outputs.run_number == 4 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-11]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.10"
@ -45,9 +80,9 @@ jobs:
run_past_ci_tensorflow_2-9:
name: TensorFlow 2.9
needs: get_number
if: needs.get_number.outputs.run_number == 5 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-10]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.9"
@ -56,9 +91,9 @@ jobs:
run_past_ci_tensorflow_2-8:
name: TensorFlow 2.8
needs: get_number
if: needs.get_number.outputs.run_number == 6 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-9]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.8"
@ -67,9 +102,9 @@ jobs:
run_past_ci_tensorflow_2-7:
name: TensorFlow 2.7
needs: get_number
if: needs.get_number.outputs.run_number == 7 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-8]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.7"
@ -78,9 +113,9 @@ jobs:
run_past_ci_tensorflow_2-6:
name: TensorFlow 2.6
needs: get_number
if: needs.get_number.outputs.run_number == 8 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-7]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.6"
@ -89,9 +124,9 @@ jobs:
run_past_ci_tensorflow_2-5:
name: TensorFlow 2.5
needs: get_number
if: needs.get_number.outputs.run_number == 9 && (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
uses: ./.github/workflows/self-past-caller.yml
if: (cancelled() != true) && ((github.event_name == 'push') && startsWith(github.ref_name, 'run_past_ci'))
needs: [run_past_ci_tensorflow_2-6]
uses: ./.github/workflows/self-past.yml
with:
framework: tensorflow
version: "2.5"

View File

@ -0,0 +1,290 @@
name: Self-hosted runner (nightly-ci)
# Note that each job's dependencies go into a corresponding docker file.
#
# For example for `run_torch_cuda_extensions_gpu` the docker image is
# `huggingface/transformers-pytorch-deepspeed-latest-gpu`, which can be found at
# `docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile`
on:
repository_dispatch:
workflow_call:
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
setup:
name: Setup
strategy:
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-all-latest-torch-nightly-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: Update clone
working-directory: /transformers
run: |
git fetch && git checkout ${{ github.sha }}
- name: Cleanup
working-directory: /transformers
run: |
rm -rf tests/__pycache__
rm -rf tests/models/__pycache__
rm -rf reports
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- id: set-matrix
name: Identify models to test
working-directory: /transformers/tests
run: |
echo "matrix=$(python3 -c 'import os; tests = os.getcwd(); model_tests = os.listdir(os.path.join(tests, "models")); d1 = sorted(list(filter(os.path.isdir, os.listdir(tests)))); d2 = sorted(list(filter(os.path.isdir, [f"models/{x}" for x in model_tests]))); d1.remove("models"); d = d2 + d1; print(d)')" >> $GITHUB_OUTPUT
- name: NVIDIA-SMI
run: |
nvidia-smi
run_tests_single_gpu:
name: Model tests
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [single-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-all-latest-torch-nightly-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_nightly"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_nightly
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_tests_multi_gpu:
name: Model tests
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-all-latest-torch-nightly-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_nightly"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_nightly
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_torch_cuda_extensions_gpu:
name: Torch CUDA extension tests
strategy:
fail-fast: false
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
needs: setup
container:
image: huggingface/transformers-pytorch-deepspeed-nightly-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Update clone
working-directory: /workspace/transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /workspace/transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Remove cached torch extensions
run: rm -rf /github/home/.cache/torch_extensions/
# To avoid unknown test failures
- name: Pre build DeepSpeed *again*
working-directory: /workspace
run: |
python3 -m pip uninstall -y deepspeed
rm -rf DeepSpeed
git clone https://github.com/microsoft/DeepSpeed && cd DeepSpeed && rm -rf build
DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /workspace/transformers
run: |
python utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /workspace/transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /workspace/transformers
run: |
python -m pytest -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports_postfix_nightly"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports_postfix_nightly
path: /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
send_results:
name: Send results to webhook
runs-on: ubuntu-22.04
if: always()
needs: [
setup,
run_tests_single_gpu,
run_tests_multi_gpu,
run_torch_cuda_extensions_gpu
]
steps:
- name: Preliminary job status
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
echo "Setup status: ${{ needs.setup.result }}"
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
- name: Send message to Slack
env:
CI_SLACK_BOT_TOKEN: ${{ secrets.CI_SLACK_BOT_TOKEN }}
CI_SLACK_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID }}
CI_SLACK_CHANNEL_ID_DAILY: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY }}
CI_SLACK_CHANNEL_DUMMY_TESTS: ${{ secrets.CI_SLACK_CHANNEL_DUMMY_TESTS }}
CI_SLACK_REPORT_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID_PAST_FUTURE }}
ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
CI_EVENT: Nightly CI
SETUP_STATUS: ${{ needs.setup.result }}
# We pass `needs.setup.outputs.matrix` as the argument. A processing in `notification_service.py` to change
# `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
run: |
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ needs.setup.outputs.matrix }}"
# delete-artifact
- uses: geekyeggo/delete-artifact@v2
with:
name: |
single-*
multi-*

View File

@ -1,40 +0,0 @@
name: Self-hosted runner (past-ci)
on:
workflow_call:
inputs:
framework:
required: true
type: string
version:
required: true
type: string
# Use this to control the commit to test against
sha:
default: 'main'
required: false
type: string
jobs:
model-ci:
name: Model CI
uses: ./.github/workflows/self-scheduled.yml
with:
job: run_models_gpu
slack_report_channel: "#transformers-ci-past-future"
runner: past-ci
docker: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
ci_event: Past CI - ${{ inputs.framework }}-${{ inputs.version }}
secrets: inherit
deepspeed-ci:
name: DeepSpeed CI
uses: ./.github/workflows/self-scheduled.yml
with:
job: run_torch_cuda_extensions_gpu
slack_report_channel: "#transformers-ci-past-future"
runner: past-ci
docker: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
ci_event: Past CI - ${{ inputs.framework }}-${{ inputs.version }}
secrets: inherit

357
.github/workflows/self-past.yml vendored Normal file
View File

@ -0,0 +1,357 @@
name: Self-hosted runner (past-ci)
# Note that each job's dependencies go into a corresponding docker file.
#
# For example for `run_torch_cuda_extensions_gpu` the docker image is
# `huggingface/transformers-pytorch-deepspeed-latest-gpu`, which can be found at
# `docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile`
on:
workflow_call:
inputs:
framework:
required: true
type: string
version:
required: true
type: string
# Use this to control the commit to test against
sha:
default: 'main'
required: false
type: string
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
setup:
name: Setup
strategy:
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ inputs.sha }}
- name: Cleanup
working-directory: /transformers
run: |
rm -rf tests/__pycache__
rm -rf tests/models/__pycache__
rm -rf reports
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- id: set-matrix
working-directory: /transformers
name: Identify models to test
run: |
cd tests
echo "matrix=$(python3 -c 'import os; tests = os.getcwd(); model_tests = os.listdir(os.path.join(tests, "models")); d1 = sorted(list(filter(os.path.isdir, os.listdir(tests)))); d2 = sorted(list(filter(os.path.isdir, [f"models/{x}" for x in model_tests]))); d1.remove("models"); d = d2 + d1; print(d)')" >> $GITHUB_OUTPUT
run_tests_single_gpu:
name: Model tests
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [single-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ inputs.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update some packages
working-directory: /transformers
run: python3 -m pip install -U datasets
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Install
if: inputs.framework == 'pytorch'
working-directory: /transformers
run: |
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: Save job name
if: ${{ always() }}
shell: bash
run: |
matrix_folders=${matrix_folders/'models_'/'models/'}
job_name="Model tests ($matrix_folders, ${{ matrix.machine_type }})"
echo "$job_name"
echo "$job_name" > /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/job_name.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_tests_multi_gpu:
name: Model tests
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
container:
image: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ inputs.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update some packages
working-directory: /transformers
run: python3 -m pip install -U datasets
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Install
if: inputs.framework == 'pytorch'
working-directory: /transformers
run: |
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: Save job name
if: ${{ always() }}
shell: bash
run: |
matrix_folders=${matrix_folders/'models_'/'models/'}
job_name="Model tests ($matrix_folders, ${{ matrix.machine_type }})"
echo "$job_name"
echo "$job_name" > /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/job_name.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_torch_cuda_extensions_gpu:
name: Torch CUDA extension tests
if: inputs.framework == 'pytorch'
strategy:
fail-fast: false
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, past-ci]
needs: setup
container:
image: huggingface/transformers-${{ inputs.framework }}-past-${{ inputs.version }}-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update some packages
working-directory: /transformers
run: python3 -m pip install -U datasets
- name: Install
working-directory: /transformers
run: |
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: Remove cached torch extensions
run: rm -rf /github/home/.cache/torch_extensions/
# To avoid unknown test failures
- name: Pre build DeepSpeed *again*
working-directory: /
run: |
python3 -m pip uninstall -y deepspeed
rm -rf DeepSpeed
git clone https://github.com/microsoft/DeepSpeed && cd DeepSpeed && rm -rf build
DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports_postfix_${{ inputs.framework }}-${{ inputs.version }}
path: /transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
send_results:
name: Send results to webhook
runs-on: ubuntu-22.04
if: always()
needs: [
setup,
run_tests_single_gpu,
run_tests_multi_gpu,
run_torch_cuda_extensions_gpu
]
steps:
- name: Preliminary job status
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
echo "Setup status: ${{ needs.setup.result }}"
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
# Create a directory to store test failure tables in the next step
- name: Create directory
run: mkdir test_failure_tables
- name: Send message to Slack
env:
CI_SLACK_BOT_TOKEN: ${{ secrets.CI_SLACK_BOT_TOKEN }}
CI_SLACK_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID }}
CI_SLACK_CHANNEL_ID_DAILY: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY }}
CI_SLACK_CHANNEL_DUMMY_TESTS: ${{ secrets.CI_SLACK_CHANNEL_DUMMY_TESTS }}
CI_SLACK_REPORT_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID_PAST_FUTURE }}
ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
CI_EVENT: Past CI - ${{ inputs.framework }}-${{ inputs.version }}
SETUP_STATUS: ${{ needs.setup.result }}
# We pass `needs.setup.outputs.matrix` as the argument. A processing in `notification_service.py` to change
# `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
run: |
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ needs.setup.outputs.matrix }}"
# Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
- name: Failure table artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: test_failure_tables_${{ inputs.framework }}-${{ inputs.version }}
path: test_failure_tables
# delete-artifact
- uses: geekyeggo/delete-artifact@v2
with:
name: |
single-*
multi-*

132
.github/workflows/self-pr-slow-ci.yml vendored Normal file
View File

@ -0,0 +1,132 @@
name: PR slow CI
on:
pull_request:
paths:
- "src/transformers/models/*/modeling_*.py"
- "tests/models/*/test_*.py"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
# For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
# This token is created under the bot `hf-transformers-bot`.
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
RUN_PT_TF_CROSS_TESTS: 1
CUDA_VISIBLE_DEVICES: 0,1
jobs:
find_models_to_run:
runs-on: ubuntu-22.04
name: Find models to run slow tests
# Triggered only if the required label `run-slow` is added
if: ${{ contains(github.event.pull_request.labels.*.name, 'run-slow') }}
outputs:
models: ${{ steps.models_to_run.outputs.models }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: "0"
ref: ${{ github.event.pull_request.head.sha }}
- name: Get commit message
run: |
echo "commit_message=$(git show -s --format=%s)" >> $GITHUB_ENV
- name: Get models to run slow tests
run: |
echo "${{ env.commit_message }}"
python -m pip install GitPython
python utils/pr_slow_ci_models.py --commit_message "${{ env.commit_message }}" | tee output.txt
echo "models=$(tail -n 1 output.txt)" >> $GITHUB_ENV
- name: Models to run slow tests
id: models_to_run
run: |
echo "${{ env.models }}"
echo "models=${{ env.models }}" >> $GITHUB_OUTPUT
run_models_gpu:
name: Run all tests for the model
# Triggered only `find_models_to_run` is triggered (label `run-slow` is added) which gives the models to run
# (either a new model PR or via a commit message)
if: ${{ needs.find_models_to_run.outputs.models != '[]' }}
needs: find_models_to_run
strategy:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.find_models_to_run.outputs.models) }}
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Echo input and matrix info
shell: bash
run: |
echo "${{ matrix.folders }}"
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git fetch origin pull/${{ github.event.pull_request.number }}/head:pull/${{ github.event.pull_request.number }}/merge && git checkout pull/${{ github.event.pull_request.number }}/merge
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v -rs --make-reports=${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: Make sure report directory exists
shell: bash
run: |
mkdir -p /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
echo "hello" > /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/hello.txt
echo "${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports

View File

@ -1,25 +1,25 @@
name: Self-hosted runner (AMD mi210 CI caller)
on:
#workflow_run:
# workflows: ["Self-hosted runner (push-caller)"]
# branches: ["main"]
# types: [completed]
push:
branches:
- run_amd_push_ci_caller*
paths:
- "src/**"
- "tests/**"
- ".github/**"
- "templates/**"
- "utils/**"
jobs:
run_amd_ci:
name: AMD mi210
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_push_ci_caller')))
uses: ./.github/workflows/self-push-amd.yml
with:
gpu_flavor: mi210
secrets: inherit
name: Self-hosted runner (AMD mi210 CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (push-caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_push_ci_caller*
paths:
- "src/**"
- "tests/**"
- ".github/**"
- "templates/**"
- "utils/**"
jobs:
run_amd_ci:
name: AMD mi210
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_push_ci_caller')))
uses: ./.github/workflows/self-push-amd.yml
with:
gpu_flavor: mi210
secrets: inherit

View File

@ -1,25 +1,25 @@
name: Self-hosted runner (AMD mi250 CI caller)
on:
#workflow_run:
# workflows: ["Self-hosted runner (push-caller)"]
# branches: ["main"]
# types: [completed]
push:
branches:
- run_amd_push_ci_caller*
paths:
- "src/**"
- "tests/**"
- ".github/**"
- "templates/**"
- "utils/**"
jobs:
run_amd_ci:
name: AMD mi250
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_push_ci_caller')))
uses: ./.github/workflows/self-push-amd.yml
with:
gpu_flavor: mi250
secrets: inherit
name: Self-hosted runner (AMD mi250 CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (push-caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_push_ci_caller*
paths:
- "src/**"
- "tests/**"
- ".github/**"
- "templates/**"
- "utils/**"
jobs:
run_amd_ci:
name: AMD mi250
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_push_ci_caller')))
uses: ./.github/workflows/self-push-amd.yml
with:
gpu_flavor: mi250
secrets: inherit

View File

@ -1,10 +1,10 @@
name: Self-hosted runner (AMD mi300 CI caller)
on:
#workflow_run:
# workflows: ["Self-hosted runner (push-caller)"]
# branches: ["main"]
# types: [completed]
workflow_run:
workflows: ["Self-hosted runner (push-caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_push_ci_caller*

View File

@ -64,24 +64,23 @@ jobs:
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
test_map: ${{ steps.set-matrix.outputs.test_map }}
env:
# `CI_BRANCH_PUSH`: The branch name from the push event
# `CI_BRANCH_WORKFLOW_RUN`: The name of the branch on which this workflow is triggered by `workflow_run` event
# `CI_SHA_PUSH`: The commit SHA from the push event
# `CI_SHA_WORKFLOW_RUN`: The commit SHA that triggers this workflow by `workflow_run` event
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
- name: Prepare custom environment variables
shell: bash
# `CI_BRANCH_PUSH`: The branch name from the push event
# `CI_BRANCH_WORKFLOW_RUN`: The name of the branch on which this workflow is triggered by `workflow_run` event
# `CI_BRANCH`: The non-empty branch name from the above two (one and only one of them is empty)
# `CI_SHA_PUSH`: The commit SHA from the push event
# `CI_SHA_WORKFLOW_RUN`: The commit SHA that triggers this workflow by `workflow_run` event
# `CI_SHA`: The non-empty commit SHA from the above two (one and only one of them is empty)
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -160,12 +159,6 @@ jobs:
container:
image: huggingface/transformers-pytorch-amd-gpu-push-ci # <--- We test only for PyTorch for now
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
@ -173,7 +166,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -259,12 +256,6 @@ jobs:
# run_tests_torch_cuda_extensions_single_gpu,
# run_tests_torch_cuda_extensions_multi_gpu
]
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
- name: Preliminary job status
shell: bash
@ -280,7 +271,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -329,7 +324,6 @@ jobs:
# We pass `needs.setup_gpu.outputs.matrix` as the argument. A processing in `notification_service.py` to change
# `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
run: |
pip install huggingface_hub
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ needs.setup_gpu.outputs.matrix }}"

View File

@ -32,33 +32,31 @@ jobs:
name: Setup
strategy:
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, push-ci]
container:
image: huggingface/transformers-all-latest-gpu-push-ci
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
test_map: ${{ steps.set-matrix.outputs.test_map }}
env:
# `CI_BRANCH_PUSH`: The branch name from the push event
# `CI_BRANCH_WORKFLOW_RUN`: The name of the branch on which this workflow is triggered by `workflow_run` event
# `CI_SHA_PUSH`: The commit SHA from the push event
# `CI_SHA_WORKFLOW_RUN`: The commit SHA that triggers this workflow by `workflow_run` event
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
- name: Prepare custom environment variables
shell: bash
# `CI_BRANCH_PUSH`: The branch name from the push event
# `CI_BRANCH_WORKFLOW_RUN`: The name of the branch on which this workflow is triggered by `workflow_run` event
# `CI_BRANCH`: The non-empty branch name from the above two (one and only one of them is empty)
# `CI_SHA_PUSH`: The commit SHA from the push event
# `CI_SHA_WORKFLOW_RUN`: The commit SHA that triggers this workflow by `workflow_run` event
# `CI_SHA`: The non-empty commit SHA from the above two (one and only one of them is empty)
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -132,18 +130,11 @@ jobs:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [aws-g4dn-2xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, push-ci]
container:
image: huggingface/transformers-all-latest-gpu-push-ci
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
@ -151,7 +142,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -164,23 +159,6 @@ jobs:
echo "env.CI_BRANCH = ${{ env.CI_BRANCH }}"
echo "env.CI_SHA = ${{ env.CI_SHA }}"
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Update clone using environment variables
working-directory: /transformers
run: |
@ -222,19 +200,19 @@ jobs:
- name: Run all non-slow selected tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -n 2 --dist=loadfile -v --make-reports=${{ env.machine_type }}_tests_gpu_${{ matrix.folders }} ${{ fromJson(needs.setup.outputs.test_map)[matrix.folders] }}
python3 -m pytest -n 2 --dist=loadfile -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} ${{ fromJson(needs.setup.outputs.test_map)[matrix.folders] }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_tests_gpu_${{ matrix.folders }}
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_tests_multi_gpu:
name: Model tests
@ -245,18 +223,11 @@ jobs:
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, push-ci]
container:
image: huggingface/transformers-all-latest-gpu-push-ci
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
@ -264,7 +235,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -277,23 +252,6 @@ jobs:
echo "env.CI_BRANCH = ${{ env.CI_BRANCH }}"
echo "env.CI_SHA = ${{ env.CI_SHA }}"
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Update clone using environment variables
working-directory: /transformers
run: |
@ -337,19 +295,19 @@ jobs:
MKL_SERVICE_FORCE_INTEL: 1
working-directory: /transformers
run: |
python3 -m pytest -n 2 --dist=loadfile -v --make-reports=${{ env.machine_type }}_tests_gpu_${{ matrix.folders }} ${{ fromJson(needs.setup.outputs.test_map)[matrix.folders] }}
python3 -m pytest -n 2 --dist=loadfile -v --make-reports=${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }} ${{ fromJson(needs.setup.outputs.test_map)[matrix.folders] }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
run: cat /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_tests_gpu_${{ matrix.folders }}
name: ${{ matrix.machine_type }}_run_all_tests_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_tests_gpu_${{ matrix.folders }}
run_tests_torch_cuda_extensions_single_gpu:
name: Torch CUDA extension tests
@ -358,18 +316,11 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, push-ci]
container:
image: huggingface/transformers-pytorch-deepspeed-latest-gpu-push-ci
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
@ -377,7 +328,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -390,23 +345,6 @@ jobs:
echo "env.CI_BRANCH = ${{ env.CI_BRANCH }}"
echo "env.CI_SHA = ${{ env.CI_SHA }}"
- name: Set `machine_type` for report and artifact names
working-directory: /workspace/transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Update clone using environment variables
working-directory: /workspace/transformers
run: |
@ -447,19 +385,19 @@ jobs:
working-directory: /workspace/transformers
# TODO: Here we pass all tests in the 2 folders for simplicity. It's better to pass only the identified tests.
run: |
python -m pytest -n 1 --dist=loadfile -v --make-reports=${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
python -m pytest -n 1 --dist=loadfile -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /workspace/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
run: cat /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /workspace/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
run_tests_torch_cuda_extensions_multi_gpu:
name: Torch CUDA extension tests
@ -468,18 +406,11 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, push-ci]
container:
image: huggingface/transformers-pytorch-deepspeed-latest-gpu-push-ci
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
# Necessary to get the correct branch name and commit SHA for `workflow_run` event
# We also take into account the `push` event (we might want to test some changes in a branch)
@ -487,7 +418,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -500,23 +435,6 @@ jobs:
echo "env.CI_BRANCH = ${{ env.CI_BRANCH }}"
echo "env.CI_SHA = ${{ env.CI_SHA }}"
- name: Set `machine_type` for report and artifact names
working-directory: /workspace/transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Update clone using environment variables
working-directory: /workspace/transformers
run: |
@ -557,19 +475,19 @@ jobs:
working-directory: /workspace/transformers
# TODO: Here we pass all tests in the 2 folders for simplicity. It's better to pass only the identified tests.
run: |
python -m pytest -n 1 --dist=loadfile -v --make-reports=${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
python -m pytest -n 1 --dist=loadfile -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /workspace/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
run: cat /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /workspace/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
send_results:
name: Send results to webhook
@ -582,12 +500,6 @@ jobs:
run_tests_torch_cuda_extensions_single_gpu,
run_tests_torch_cuda_extensions_multi_gpu
]
env:
# For the meaning of these environment variables, see the job `Setup`
CI_BRANCH_PUSH: ${{ github.event.ref }}
CI_BRANCH_WORKFLOW_RUN: ${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH: ${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN: ${{ github.event.workflow_run.head_sha }}
steps:
- name: Preliminary job status
shell: bash
@ -601,7 +513,11 @@ jobs:
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
CI_BRANCH_PUSH=${{ github.event.ref }}
CI_BRANCH_PUSH=${CI_BRANCH_PUSH/'refs/heads/'/''}
CI_BRANCH_WORKFLOW_RUN=${{ github.event.workflow_run.head_branch }}
CI_SHA_PUSH=${{ github.event.head_commit.id }}
CI_SHA_WORKFLOW_RUN=${{ github.event.workflow_run.head_sha }}
echo $CI_BRANCH_PUSH
echo $CI_BRANCH_WORKFLOW_RUN
echo $CI_SHA_PUSH
@ -647,7 +563,6 @@ jobs:
# We pass `needs.setup.outputs.matrix` as the argument. A processing in `notification_service.py` to change
# `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
run: |
pip install huggingface_hub
pip install slack_sdk
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ needs.setup.outputs.matrix }}"

View File

@ -1,55 +1,20 @@
name: Self-hosted runner (AMD mi210 scheduled CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (AMD scheduled CI caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_scheduled_ci_caller*
jobs:
model-ci:
name: Model CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_models_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi210
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi210
secrets: inherit
torch-pipeline:
name: Torch pipeline CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_pipelines_torch_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi210
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi210
secrets: inherit
example-ci:
name: Example CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_examples_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi210
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi210
secrets: inherit
deepspeed-ci:
name: DeepSpeed CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_torch_cuda_extensions_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi210
docker: huggingface/transformers-pytorch-deepspeed-amd-gpu
ci_event: Scheduled CI (AMD) - mi210
secrets: inherit
name: Self-hosted runner (AMD mi210 scheduled CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (AMD scheduled CI caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_scheduled_ci_caller*
jobs:
run_amd_ci:
name: AMD mi210
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_scheduled_ci_caller')))
uses: ./.github/workflows/self-scheduled-amd.yml
with:
gpu_flavor: mi210
slack_report_channel: "#transformers-ci-daily-amd"
secrets: inherit

View File

@ -1,55 +1,20 @@
name: Self-hosted runner (AMD mi250 scheduled CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (AMD scheduled CI caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_scheduled_ci_caller*
jobs:
model-ci:
name: Model CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_models_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi250
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi250
secrets: inherit
torch-pipeline:
name: Torch pipeline CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_pipelines_torch_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi250
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi250
secrets: inherit
example-ci:
name: Example CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_examples_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi250
docker: huggingface/transformers-pytorch-amd-gpu
ci_event: Scheduled CI (AMD) - mi250
secrets: inherit
deepspeed-ci:
name: DeepSpeed CI
uses: huggingface/hf-workflows/.github/workflows/transformers_amd_ci_scheduled.yaml@main
with:
job: run_torch_cuda_extensions_gpu
slack_report_channel: "#transformers-ci-daily-amd"
runner: mi250
docker: huggingface/transformers-pytorch-deepspeed-amd-gpu
ci_event: Scheduled CI (AMD) - mi250
secrets: inherit
name: Self-hosted runner (AMD mi250 scheduled CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (AMD scheduled CI caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_scheduled_ci_caller*
jobs:
run_amd_ci:
name: AMD mi250
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && startsWith(github.ref_name, 'run_amd_scheduled_ci_caller')))
uses: ./.github/workflows/self-scheduled-amd.yml
with:
gpu_flavor: mi250
slack_report_channel: "#transformers-ci-daily-amd"
secrets: inherit

View File

@ -0,0 +1,21 @@
name: Self-hosted runner (AMD mi300 scheduled CI caller)
on:
workflow_run:
workflows: ["Self-hosted runner (AMD scheduled CI caller)"]
branches: ["main"]
types: [completed]
push:
branches:
- run_amd_scheduled_ci_caller*
jobs:
run_amd_ci:
name: AMD mi300
needs: build-docker-containers
if: (cancelled() != true) && ((github.event_name == 'workflow_run') || ((github.event_name == 'push') && (startsWith(github.ref_name, 'run_amd_push_ci_caller') || startsWith(github.ref_name, 'mi300-ci'))))
uses: ./.github/workflows/self-scheduled-amd.yml
with:
gpu_flavor: mi300
slack_report_channel: "#transformers-ci-daily-amd"
secrets: inherit

519
.github/workflows/self-scheduled-amd.yml vendored Normal file
View File

@ -0,0 +1,519 @@
name: Self-hosted runner (scheduled-amd)
# Note: For the AMD CI, we rely on a caller workflow and on the workflow_call event to trigger the
# CI in order to run it on both MI210 and MI250, without having to use matrix here which pushes
# us towards the limit of allowed jobs on GitHub Actions.
on:
workflow_call:
inputs:
gpu_flavor:
required: true
type: string
env:
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
RUN_SLOW: yes
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
# Important note: each job (run_tests_single_gpu, run_tests_multi_gpu, run_examples_gpu, run_pipelines_torch_gpu) requires all the previous jobs before running.
# This is done so that we avoid parallelizing the scheduled tests, to leave available
# runners for the push CI that is running on the same machine.
jobs:
check_runner_status:
name: Check Runner Status
runs-on: ubuntu-22.04
steps:
- name: Checkout transformers
uses: actions/checkout@v4
with:
fetch-depth: 2
- name: Check Runner Status
run: python utils/check_self_hosted_runner.py --target_runners hf-amd-mi210-ci-1gpu-1,hf-amd-mi250-ci-1gpu-1,hf-amd-mi300-ci-1gpu-1 --token ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
check_runners:
name: Check Runners
needs: check_runner_status
strategy:
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
setup:
name: Setup
needs: check_runners
strategy:
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
steps:
- name: Update clone
working-directory: /transformers
run: |
git fetch && git checkout ${{ github.sha }}
- name: Cleanup
working-directory: /transformers
run: |
rm -rf tests/__pycache__
rm -rf tests/models/__pycache__
rm -rf reports
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- id: set-matrix
name: Identify models to test
working-directory: /transformers/tests
run: |
echo "matrix=$(python3 -c 'import os; tests = os.getcwd(); model_tests = os.listdir(os.path.join(tests, "models")); d1 = sorted(list(filter(os.path.isdir, os.listdir(tests)))); d2 = sorted(list(filter(os.path.isdir, [f"models/{x}" for x in model_tests]))); d1.remove("models"); d = d2 + d1; print(d)')" >> $GITHUB_OUTPUT
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
run_models_gpu_single_gpu:
name: Single GPU tests
strategy:
max-parallel: 1 # For now, not to parallelize. Can change later if it works well.
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [single-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }} -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
run_models_gpu_multi_gpu:
name: Multi GPU tests
strategy:
max-parallel: 1
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.matrix) }}
machine_type: [multi-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Echo folder ${{ matrix.folders }}
shell: bash
# For folders like `models/bert`, set an env. var. (`matrix_folders`) to `models_bert`, which will be used to
# set the artifact folder names (because the character `/` is not allowed).
run: |
echo "${{ matrix.folders }}"
matrix_folders=${{ matrix.folders }}
matrix_folders=${matrix_folders/'models/'/'models_'}
echo "$matrix_folders"
echo "matrix_folders=$matrix_folders" >> $GITHUB_ENV
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }} -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_models_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_models_gpu_${{ matrix.folders }}_test_reports
run_examples_gpu:
name: Examples tests
strategy:
fail-fast: false
matrix:
machine_type: [single-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run examples tests on GPU
working-directory: /transformers
run: |
pip install -r examples/pytorch/_tests_requirements.txt
python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_examples_gpu_test_reports examples/pytorch -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_examples_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_examples_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_examples_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_examples_gpu_test_reports
run_pipelines_torch_gpu:
name: PyTorch pipelines tests
strategy:
fail-fast: false
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
container:
image: huggingface/transformers-pytorch-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
needs: setup
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all pipeline tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports tests/pipelines -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports
run_torch_cuda_extensions_gpu:
name: Torch ROCm deepspeed tests
strategy:
fail-fast: false
matrix:
machine_type: [single-gpu, multi-gpu]
runs-on: [self-hosted, amd-gpu, '${{ matrix.machine_type }}', '${{ inputs.gpu_flavor }}']
needs: setup
container:
image: huggingface/transformers-pytorch-deepspeed-amd-gpu
options: --device /dev/kfd --device /dev/dri --env ROCR_VISIBLE_DEVICES --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Update clone
working-directory: /transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: /transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: ROCM-SMI
run: |
rocm-smi
- name: ROCM-INFO
run: |
rocminfo | grep "Agent" -A 14
- name: Show ROCR environment
run: |
echo "ROCR: $ROCR_VISIBLE_DEVICES"
- name: Environment
working-directory: /transformers
run: |
python3 utils/print_env.py
- name: Show installed libraries and their versions
working-directory: /transformers
run: pip freeze
- name: Run all tests on GPU
working-directory: /transformers
run: python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended -m "not not_device_test"
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
run_extract_warnings:
name: Extract warnings in CI artifacts
runs-on: ubuntu-22.04
if: always()
needs: [
check_runner_status,
check_runners,
setup,
run_models_gpu_single_gpu,
run_models_gpu_multi_gpu,
run_examples_gpu,
run_pipelines_torch_gpu,
run_torch_cuda_extensions_gpu
]
steps:
- name: Checkout transformers
uses: actions/checkout@v4
with:
fetch-depth: 2
- name: Install transformers
run: pip install transformers
- name: Show installed libraries and their versions
run: pip freeze
- name: Create output directory
run: mkdir warnings_in_ci
- uses: actions/download-artifact@v4
with:
path: warnings_in_ci
- name: Show artifacts
run: echo "$(python3 -c 'import os; d = os.listdir(); print(d)')"
working-directory: warnings_in_ci
- name: Extract warnings in CI artifacts
run: |
python3 utils/extract_warnings.py --workflow_run_id ${{ github.run_id }} --output_dir warnings_in_ci --token ${{ secrets.ACCESS_REPO_INFO_TOKEN }} --from_gh
echo "$(python3 -c 'import os; import json; fp = open("warnings_in_ci/selected_warnings.json"); d = json.load(fp); d = "\n".join(d) ;print(d)')"
- name: Upload artifact
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: warnings_in_ci
path: warnings_in_ci/selected_warnings.json
send_results:
name: Send results to webhook
runs-on: ubuntu-22.04
if: always()
needs: [
check_runner_status,
check_runners,
setup,
run_models_gpu_single_gpu,
run_models_gpu_multi_gpu,
run_examples_gpu,
run_pipelines_torch_gpu,
run_torch_cuda_extensions_gpu,
run_extract_warnings
]
steps:
- name: Preliminary job status
shell: bash
# For the meaning of these environment variables, see the job `Setup`
run: |
echo "Runner availability: ${{ needs.check_runner_status.result }}"
echo "Runner status: ${{ needs.check_runners.result }}"
echo "Setup status: ${{ needs.setup.result }}"
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
- name: Send message to Slack
env:
CI_SLACK_BOT_TOKEN: ${{ secrets.CI_SLACK_BOT_TOKEN }}
CI_SLACK_CHANNEL_ID_DAILY_AMD: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY_AMD }}
CI_SLACK_CHANNEL_DUMMY_TESTS: ${{ secrets.CI_SLACK_CHANNEL_DUMMY_TESTS }}
CI_SLACK_REPORT_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY_AMD }}
ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
CI_EVENT: Scheduled CI (AMD) - ${{ inputs.gpu_flavor }}
CI_SHA: ${{ github.sha }}
CI_WORKFLOW_REF: ${{ github.workflow_ref }}
RUNNER_STATUS: ${{ needs.check_runner_status.result }}
RUNNER_ENV_STATUS: ${{ needs.check_runners.result }}
SETUP_STATUS: ${{ needs.setup.result }}
# We pass `needs.setup.outputs.matrix` as the argument. A processing in `notification_service.py` to change
# `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
run: |
sudo apt-get install -y curl
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ needs.setup.outputs.matrix }}"
# Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
- name: Failure table artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: test_failure_tables
path: test_failure_tables

View File

@ -16,9 +16,6 @@ jobs:
with:
job: run_models_gpu
slack_report_channel: "#transformers-ci-daily-models"
runner: daily-ci
docker: huggingface/transformers-all-latest-gpu
ci_event: Daily CI
secrets: inherit
torch-pipeline:
@ -27,9 +24,6 @@ jobs:
with:
job: run_pipelines_torch_gpu
slack_report_channel: "#transformers-ci-daily-pipeline-torch"
runner: daily-ci
docker: huggingface/transformers-pytorch-gpu
ci_event: Daily CI
secrets: inherit
tf-pipeline:
@ -38,9 +32,6 @@ jobs:
with:
job: run_pipelines_tf_gpu
slack_report_channel: "#transformers-ci-daily-pipeline-tf"
runner: daily-ci
docker: huggingface/transformers-tensorflow-gpu
ci_event: Daily CI
secrets: inherit
example-ci:
@ -49,9 +40,6 @@ jobs:
with:
job: run_examples_gpu
slack_report_channel: "#transformers-ci-daily-examples"
runner: daily-ci
docker: huggingface/transformers-all-latest-gpu
ci_event: Daily CI
secrets: inherit
deepspeed-ci:
@ -60,10 +48,6 @@ jobs:
with:
job: run_torch_cuda_extensions_gpu
slack_report_channel: "#transformers-ci-daily-deepspeed"
runner: daily-ci
docker: huggingface/transformers-pytorch-deepspeed-latest-gpu
ci_event: Daily CI
working-directory-prefix: /workspace
secrets: inherit
quantization-ci:
@ -72,7 +56,4 @@ jobs:
with:
job: run_quantization_torch_gpu
slack_report_channel: "#transformers-ci-daily-quantization"
runner: daily-ci
docker: huggingface/transformers-quantization-latest-gpu
ci_event: Daily CI
secrets: inherit

View File

@ -15,19 +15,6 @@ on:
slack_report_channel:
required: true
type: string
runner:
required: true
type: string
docker:
required: true
type: string
ci_event:
required: true
type: string
working-directory-prefix:
default: ''
required: false
type: string
env:
HF_HOME: /mnt/cache
@ -50,9 +37,8 @@ jobs:
name: Setup
strategy:
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -84,7 +70,7 @@ jobs:
run: |
echo "folder_slices=$(python3 ../utils/split_model_tests.py --num_splits ${{ env.NUM_SLICES }})" >> $GITHUB_OUTPUT
echo "slice_ids=$(python3 -c 'd = list(range(${{ env.NUM_SLICES }})); print(d)')" >> $GITHUB_OUTPUT
- id: set-matrix-quantization
if: ${{ inputs.job == 'run_quantization_torch_gpu' }}
name: Identify quantization method to test
@ -103,15 +89,13 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
machine_type: [single-gpu, multi-gpu]
slice_id: ${{ fromJSON(needs.setup.outputs.slice_ids) }}
uses: ./.github/workflows/model_jobs.yml
with:
folder_slices: ${{ needs.setup.outputs.folder_slices }}
machine_type: ${{ matrix.machine_type }}
slice_id: ${{ matrix.slice_id }}
runner: ${{ inputs.runner }}
docker: ${{ inputs.docker }}
secrets: inherit
run_pipelines_torch_gpu:
@ -120,9 +104,8 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: huggingface/transformers-pytorch-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -148,39 +131,22 @@ jobs:
working-directory: /transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run all pipeline tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports tests/pipelines
python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports tests/pipelines
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports/failures_short.txt
run: cat /transformers/reports/${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_pipelines_torch_gpu_test_reports
name: ${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_pipelines_torch_gpu_test_reports
run_pipelines_tf_gpu:
if: ${{ inputs.job == 'run_pipelines_tf_gpu' }}
@ -188,9 +154,8 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: huggingface/transformers-tensorflow-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -217,39 +182,22 @@ jobs:
working-directory: /transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run all pipeline tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ env.machine_type }}_run_pipelines_tf_gpu_test_reports tests/pipelines
python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ matrix.machine_type }}_run_pipelines_tf_gpu_test_reports tests/pipelines
- name: Failure short reports
if: ${{ always() }}
run: |
cat /transformers/reports/${{ env.machine_type }}_run_pipelines_tf_gpu_test_reports/failures_short.txt
cat /transformers/reports/${{ matrix.machine_type }}_run_pipelines_tf_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_pipelines_tf_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_pipelines_tf_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_pipelines_tf_gpu_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_pipelines_tf_gpu_test_reports
name: ${{ matrix.machine_type }}_run_pipelines_tf_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_pipelines_tf_gpu_test_reports
run_examples_gpu:
if: ${{ inputs.job == 'run_examples_gpu' }}
@ -257,9 +205,8 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: huggingface/transformers-all-latest-gpu
options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -285,40 +232,23 @@ jobs:
working-directory: /transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run examples tests on GPU
working-directory: /transformers
run: |
pip install -r examples/pytorch/_tests_requirements.txt
python3 -m pytest -v --make-reports=${{ env.machine_type }}_run_examples_gpu_test_reports examples/pytorch
python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_examples_gpu_test_reports examples/pytorch
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_examples_gpu_test_reports/failures_short.txt
run: cat /transformers/reports/${{ matrix.machine_type }}_run_examples_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_examples_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_examples_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_examples_gpu_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_examples_gpu_test_reports
name: ${{ matrix.machine_type }}_run_examples_gpu_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_examples_gpu_test_reports
run_torch_cuda_extensions_gpu:
if: ${{ inputs.job == 'run_torch_cuda_extensions_gpu' }}
@ -326,108 +256,70 @@ jobs:
strategy:
fail-fast: false
matrix:
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: ${{ inputs.docker }}
image: huggingface/transformers-pytorch-deepspeed-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
steps:
- name: Update clone
working-directory: ${{ inputs.working-directory-prefix }}/transformers
working-directory: /workspace/transformers
run: git fetch && git checkout ${{ github.sha }}
- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
working-directory: ${{ inputs.working-directory-prefix }}/transformers
working-directory: /workspace/transformers
run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
- name: Update / Install some packages (for Past CI)
if: ${{ contains(inputs.docker, '-past-') && contains(inputs.docker, '-pytorch-') }}
working-directory: ${{ inputs.working-directory-prefix }}/transformers
run: |
python3 -m pip install -U datasets
python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate
- name: Remove cached torch extensions
run: rm -rf /github/home/.cache/torch_extensions/
# To avoid unknown test failures
- name: Pre build DeepSpeed *again* (for daily CI)
if: ${{ contains(inputs.ci_event, 'Daily CI') }}
working-directory: ${{ inputs.working-directory-prefix }}/
- name: Pre build DeepSpeed *again*
working-directory: /workspace
run: |
python3 -m pip uninstall -y deepspeed
DS_DISABLE_NINJA=1 DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install deepspeed --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check
# To avoid unknown test failures
- name: Pre build DeepSpeed *again* (for nightly & Past CI)
if: ${{ contains(inputs.ci_event, 'Nightly CI') || contains(inputs.ci_event, 'Past CI') }}
working-directory: ${{ inputs.working-directory-prefix }}/
run: |
python3 -m pip uninstall -y deepspeed
rm -rf DeepSpeed
git clone https://github.com/deepspeedai/DeepSpeed && cd DeepSpeed && rm -rf build
DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Environment
working-directory: ${{ inputs.working-directory-prefix }}/transformers
working-directory: /workspace/transformers
run: |
python3 utils/print_env.py
python utils/print_env.py
- name: Show installed libraries and their versions
working-directory: ${{ inputs.working-directory-prefix }}/transformers
working-directory: /workspace/transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run all tests on GPU
working-directory: ${{ inputs.working-directory-prefix }}/transformers
working-directory: /workspace/transformers
run: |
python3 -m pytest -v --make-reports=${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
python -m pytest -v --make-reports=${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports tests/deepspeed tests/extended
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat ${{ inputs.working-directory-prefix }}/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
run: cat /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: ${{ inputs.working-directory-prefix }}/transformers/reports/${{ env.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
name: ${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
path: /workspace/transformers/reports/${{ matrix.machine_type }}_run_torch_cuda_extensions_gpu_test_reports
run_quantization_torch_gpu:
if: ${{ inputs.job == 'run_quantization_torch_gpu' }}
name: " "
needs: setup
strategy:
max-parallel: 4
fail-fast: false
matrix:
folders: ${{ fromJson(needs.setup.outputs.quantization_matrix) }}
machine_type: [aws-g4dn-2xlarge-cache, aws-g4dn-12xlarge-cache]
runs-on:
group: '${{ matrix.machine_type }}'
machine_type: [single-gpu, multi-gpu]
runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
container:
image: huggingface/transformers-quantization-latest-gpu
options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -462,39 +354,22 @@ jobs:
working-directory: /transformers
run: pip freeze
- name: Set `machine_type` for report and artifact names
working-directory: /transformers
shell: bash
run: |
echo "${{ matrix.machine_type }}"
if [ "${{ matrix.machine_type }}" = "aws-g4dn-2xlarge-cache" ]; then
machine_type=single-gpu
elif [ "${{ matrix.machine_type }}" = "aws-g4dn-12xlarge-cache" ]; then
machine_type=multi-gpu
else
machine_type=${{ matrix.machine_type }}
fi
echo "$machine_type"
echo "machine_type=$machine_type" >> $GITHUB_ENV
- name: Run quantization tests on GPU
working-directory: /transformers
run: |
python3 -m pytest -v --make-reports=${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports tests/${{ matrix.folders }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: cat /transformers/reports/${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
run: cat /transformers/reports/${{ matrix.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports/failures_short.txt
- name: "Test suite reports artifacts: ${{ env.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports"
- name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports"
if: ${{ always() }}
uses: actions/upload-artifact@v4
with:
name: ${{ env.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ env.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports
name: ${{ matrix.machine_type }}_run_quantization_torch_gpu_${{ env.matrix_folders }}_test_reports
path: /transformers/reports/${{ matrix.machine_type }}_run_quantization_torch_gpu_${{ matrix.folders }}_test_reports
run_extract_warnings:
# Let's only do this for the job `run_models_gpu` to simplify the (already complex) logic.
@ -559,16 +434,5 @@ jobs:
# This would be an empty string if `setup` is skipped.
folder_slices: ${{ needs.setup.outputs.folder_slices }}
quantization_matrix: ${{ needs.setup.outputs.quantization_matrix }}
ci_event: ${{ inputs.ci_event }}
secrets: inherit
check_new_model_failures:
if: ${{ always() && inputs.ci_event == 'Daily CI' && inputs.job == 'run_models_gpu' && needs.send_results.result == 'success' }}
name: Check new model failures
needs: send_results
uses: ./.github/workflows/check_failed_model_tests.yml
with:
docker: ${{ inputs.docker }}
start_sha: ${{ github.sha }}
secrets: inherit

View File

@ -18,12 +18,7 @@ on:
quantization_matrix:
required: true
type: string
ci_event:
required: true
type: string
env:
TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN: ${{ secrets.TRANSFORMERS_CI_RESULTS_UPLOAD_TOKEN }}
jobs:
send_results:
@ -48,7 +43,7 @@ jobs:
CI_SLACK_CHANNEL_DUMMY_TESTS: ${{ secrets.CI_SLACK_CHANNEL_DUMMY_TESTS }}
SLACK_REPORT_CHANNEL: ${{ inputs.slack_report_channel }}
ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
CI_EVENT: ${{ inputs.ci_event }}
CI_EVENT: scheduled
CI_SHA: ${{ github.sha }}
CI_WORKFLOW_REF: ${{ github.workflow_ref }}
CI_TEST_JOB: ${{ inputs.job }}
@ -59,7 +54,6 @@ jobs:
# empty string, and the called script still get one argument (which is the emtpy string).
run: |
sudo apt-get install -y curl
pip install huggingface_hub
pip install slack_sdk
pip show slack_sdk
python utils/notification_service.py "${{ inputs.folder_slices }}"
@ -70,7 +64,7 @@ jobs:
with:
name: ci_results_${{ inputs.job }}
path: ci_results_${{ inputs.job }}
- uses: actions/checkout@v4
- uses: actions/download-artifact@v4
- name: Send message to Slack for quantization workflow
@ -79,7 +73,7 @@ jobs:
CI_SLACK_BOT_TOKEN: ${{ secrets.CI_SLACK_BOT_TOKEN }}
ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
SLACK_REPORT_CHANNEL: ${{ inputs.slack_report_channel }}
CI_EVENT: ${{ inputs.ci_event }}
CI_EVENT: scheduled
CI_SHA: ${{ github.sha }}
CI_TEST_JOB: ${{ inputs.job }}
SETUP_STATUS: ${{ inputs.setup_status }}
@ -87,10 +81,9 @@ jobs:
# `quantization/bnb` to `quantization_bnb` is required, as the artifact names use `_` instead of `/`.
run: |
sudo apt-get install -y curl
pip install huggingface_hub
pip install slack_sdk
pip show slack_sdk
python utils/notification_service_quantization.py "${{ inputs.quantization_matrix }}"
python utils/notification_service_quantization.py "${{ inputs.quantization_matrix }}"
# Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
- name: Failure table artifacts
@ -98,4 +91,4 @@ jobs:
uses: actions/upload-artifact@v4
with:
name: ci_results_${{ inputs.job }}
path: ci_results_${{ inputs.job }}
path: ci_results_${{ inputs.job }}

View File

@ -9,11 +9,9 @@ on:
docker_image:
description: 'Name of the Docker image'
required: true
num_gpus:
description: 'Type of the number of gpus to use (`single` or `multi`)'
required: true
env:
IS_GITHUB_CI: "1"
HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
HF_HOME: /mnt/cache
TRANSFORMERS_IS_CI: yes
@ -22,42 +20,12 @@ env:
RUN_SLOW: yes # For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access. # This token is created under the bot `hf-transformers-bot`.
SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
TF_FORCE_GPU_ALLOW_GROWTH: true
CUDA_VISIBLE_DEVICES: 0,1
RUN_PT_TF_CROSS_TESTS: 1
jobs:
get_runner:
name: "Get runner to use"
runs-on: ubuntu-22.04
outputs:
RUNNER: ${{ steps.set_runner.outputs.RUNNER }}
steps:
- name: Get runner to use
shell: bash
run: |
if [[ "${{ github.event.inputs.num_gpus }}" == "single" && "${{ github.event.inputs.runner_type }}" == "t4" ]]; then
echo "RUNNER=aws-g4dn-2xlarge-cache" >> $GITHUB_ENV
elif [[ "${{ github.event.inputs.num_gpus }}" == "multi" && "${{ github.event.inputs.runner_type }}" == "t4" ]]; then
echo "RUNNER=aws-g4dn-12xlarge-cache" >> $GITHUB_ENV
elif [[ "${{ github.event.inputs.num_gpus }}" == "single" && "${{ github.event.inputs.runner_type }}" == "a10" ]]; then
echo "RUNNER=aws-g5-4xlarge-cache" >> $GITHUB_ENV
elif [[ "${{ github.event.inputs.num_gpus }}" == "multi" && "${{ github.event.inputs.runner_type }}" == "a10" ]]; then
echo "RUNNER=aws-g5-12xlarge-cache" >> $GITHUB_ENV
else
echo "RUNNER=" >> $GITHUB_ENV
fi
- name: Set runner to use
id: set_runner
run: |
echo ${{ env.RUNNER }}
echo "RUNNER=${{ env.RUNNER }}" >> $GITHUB_OUTPUT
ssh_runner:
name: "SSH"
needs: get_runner
runs-on:
group: ${{ needs.get_runner.outputs.RUNNER }}
runs-on: [single-gpu, nvidia-gpu, "${{ github.event.inputs.runner_type }}", ci]
container:
image: ${{ github.event.inputs.docker_image }}
options: --gpus all --privileged --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
@ -82,33 +50,11 @@ jobs:
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Store Slack infos
#because the SSH can be enabled dynamically if the workflow failed, so we need to store slack infos to be able to retrieve them during the waitforssh step
shell: bash
run: |
echo "${{ github.actor }}"
github_actor=${{ github.actor }}
github_actor=${github_actor/'-'/'_'}
echo "$github_actor"
echo "github_actor=$github_actor" >> $GITHUB_ENV
- name: Store Slack infos
#because the SSH can be enabled dynamically if the workflow failed, so we need to store slack infos to be able to retrieve them during the waitforssh step
shell: bash
run: |
echo "${{ env.github_actor }}"
if [ "${{ secrets[format('{0}_{1}', env.github_actor, 'SLACK_ID')] }}" != "" ]; then
echo "SLACKCHANNEL=${{ secrets[format('{0}_{1}', env.github_actor, 'SLACK_ID')] }}" >> $GITHUB_ENV
else
echo "SLACKCHANNEL=${{ secrets.SLACK_CIFEEDBACK_CHANNEL }}" >> $GITHUB_ENV
fi
- name: Tailscale # In order to be able to SSH when a test fails
uses: huggingface/tailscale-action@main
uses: huggingface/tailscale-action@v1
with:
authkey: ${{ secrets.TAILSCALE_SSH_AUTHKEY }}
slackChannel: ${{ env.SLACKCHANNEL }}
slackChannel: ${{ secrets.SLACK_CIFEEDBACK_CHANNEL }}
slackToken: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
waitForSSH: true
sshTimeout: 15m

View File

@ -9,15 +9,13 @@ jobs:
name: Close Stale Issues
if: github.repository == 'huggingface/transformers'
runs-on: ubuntu-22.04
permissions:
issues: write
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: 3.8

View File

@ -1,20 +0,0 @@
on:
push:
name: Secret Leaks
permissions:
contents: read
jobs:
trufflehog:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Secret Scanning
uses: trufflesecurity/trufflehog@main
with:
extra_args: --results=verified,unknown

View File

@ -61,10 +61,7 @@ feedback.
The 🤗 Transformers library is robust and reliable thanks to users who report the problems they encounter.
Before you report an issue, we would really appreciate it if you could **make sure the bug was not
already reported** (use the search bar on GitHub under Issues). Your issue should also be related to bugs in the library itself, and not your code. If you're unsure whether the bug is in your code or the library, please ask in the [forum](https://discuss.huggingface.co/) or on our [discord](https://discord.com/invite/hugging-face-879548962464493619) first. This helps us respond quicker to fixing issues related to the library versus general questions.
> [!TIP]
> We have a [docs bot](https://huggingface.co/spaces/huggingchat/hf-docs-chat), and we highly encourage you to ask all your questions there. There is always a chance your bug can be fixed with a simple flag 👾🔫
already reported** (use the search bar on GitHub under Issues). Your issue should also be related to bugs in the library itself, and not your code. If you're unsure whether the bug is in your code or the library, please ask in the [forum](https://discuss.huggingface.co/) first. This helps us respond quicker to fixing issues related to the library versus general questions.
Once you've confirmed the bug hasn't already been reported, please include the following information in your issue so we can quickly resolve it:
@ -132,7 +129,7 @@ You will need basic `git` proficiency to contribute to
manual. Type `git --help` in a shell and enjoy! If you prefer books, [Pro
Git](https://git-scm.com/book/en/v2) is a very good reference.
You'll need **[Python 3.9](https://github.com/huggingface/transformers/blob/main/setup.py#L449)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:
You'll need **[Python 3.8](https://github.com/huggingface/transformers/blob/main/setup.py#L426)** or above to contribute to 🤗 Transformers. Follow the steps below to start contributing:
1. Fork the [repository](https://github.com/huggingface/transformers) by
clicking on the **[Fork](https://github.com/huggingface/transformers/fork)** button on the repository's page. This creates a copy of the code
@ -163,7 +160,7 @@ You'll need **[Python 3.9](https://github.com/huggingface/transformers/blob/main
If 🤗 Transformers was already installed in the virtual environment, remove
it with `pip uninstall transformers` before reinstalling it in editable
mode with the `-e` flag.
Depending on your OS, and since the number of optional dependencies of Transformers is growing, you might get a
failure with this command. If that's the case make sure to install the Deep Learning framework you are working with
(PyTorch, TensorFlow and/or Flax) then do:
@ -222,7 +219,7 @@ You'll need **[Python 3.9](https://github.com/huggingface/transformers/blob/main
If you're modifying documents under the `docs/source` directory, make sure the documentation can still be built. This check will also run in the CI when you open a pull request. To run a local check
make sure you install the documentation builder:
```bash
pip install ".[docs]"
```
@ -341,12 +338,12 @@ RUN_SLOW=yes python -m pytest -n auto --dist=loadfile -s -v ./tests/models/my_ne
RUN_SLOW=yes python -m pytest -n auto --dist=loadfile -s -v ./examples/pytorch/text-classification
```
Like the slow tests, there are other environment variables available which are not enabled by default during testing:
Like the slow tests, there are other environment variables available which not enabled by default during testing:
- `RUN_CUSTOM_TOKENIZERS`: Enables tests for custom tokenizers.
- `RUN_PT_FLAX_CROSS_TESTS`: Enables tests for PyTorch + Flax integration.
- `RUN_PT_TF_CROSS_TESTS`: Enables tests for TensorFlow + PyTorch integration.
More environment variables and additional information can be found in the [testing_utils.py](https://github.com/huggingface/transformers/blob/main/src/transformers/testing_utils.py).
More environment variables and additional information can be found in the [testing_utils.py](src/transformers/testing_utils.py).
🤗 Transformers uses `pytest` as a test runner only. It doesn't use any
`pytest`-specific features in the test suite itself.

View File

@ -1,11 +1,11 @@
.PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples benchmark
.PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples
# make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
export PYTHONPATH = src
check_dirs := examples tests src utils
exclude_folders := ""
exclude_folders := examples/research_projects
modified_only_fixup:
$(eval modified_py_files := $(shell python utils/get_modified_files.py $(check_dirs)))
@ -36,7 +36,6 @@ autogenerate_code: deps_table_update
repo-consistency:
python utils/check_copies.py
python utils/check_modular_conversion.py
python utils/check_table.py
python utils/check_dummies.py
python utils/check_repo.py
@ -54,14 +53,15 @@ quality:
@python -c "from transformers import *" || (echo '🚨 import failed, this means you introduced unprotected imports! 🚨'; exit 1)
ruff check $(check_dirs) setup.py conftest.py
ruff format --check $(check_dirs) setup.py conftest.py
python utils/custom_init_isort.py --check_only
python utils/sort_auto_mappings.py --check_only
python utils/check_doc_toc.py
python utils/check_docstrings.py --check_all
# Format source code automatically and check is there are any problems left that need manual fixing
extra_style_checks:
python utils/custom_init_isort.py
python utils/sort_auto_mappings.py
python utils/check_doc_toc.py --fix_and_overwrite
@ -81,7 +81,6 @@ fixup: modified_only_fixup extra_style_checks autogenerate_code repo-consistency
fix-copies:
python utils/check_copies.py --fix_and_overwrite
python utils/check_modular_conversion.py --fix_and_overwrite
python utils/check_table.py --fix_and_overwrite
python utils/check_dummies.py --fix_and_overwrite
python utils/check_doctest_list.py --fix_and_overwrite
@ -97,11 +96,6 @@ test:
test-examples:
python -m pytest -n auto --dist=loadfile -s -v ./examples/pytorch/
# Run benchmark
benchmark:
python3 benchmark/benchmark.py --config-dir benchmark/config --config-name generation --commit=diff backend.model=google/gemma-2b backend.cache_implementation=null,static backend.torch_compile=false,true --multirun
# Run tests for SageMaker DLC release
test-sagemaker: # install sagemaker dependencies in advance with pip install .[sagemaker]

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<b>English</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -128,10 +136,10 @@ incredible projects built in the vicinity of transformers.
If you own or use a project that you believe should be part of the list, please open a PR to add it!
## Serious about AI in your organisation? Build faster with the Hugging Face Enterprise Hub.
## If you are looking for custom support from the Hugging Face team
<a target="_blank" href="https://huggingface.co/enterprise">
<img alt="Hugging Face Enterprise Hub" src="https://github.com/user-attachments/assets/247fb16d-d251-4583-96c4-d3d76dda4925">
<a target="_blank" href="https://huggingface.co/support">
<img alt="HuggingFace Expert Acceleration Program" src="https://cdn-media.huggingface.co/marketing/transformers/new-support-improved.png" style="max-width: 600px; border: 1px solid #eee; border-radius: 4px; box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);">
</a><br>
## Quick tour
@ -249,43 +257,23 @@ The model itself is a regular [Pytorch `nn.Module`](https://pytorch.org/docs/sta
### With pip
This repository is tested on Python 3.9+, Flax 0.4.1+, PyTorch 2.0+, and TensorFlow 2.6+.
This repository is tested on Python 3.8+, Flax 0.4.1+, PyTorch 1.11+, and TensorFlow 2.6+.
You should install 🤗 Transformers in a [virtual environment](https://docs.python.org/3/library/venv.html). If you're unfamiliar with Python virtual environments, check out the [user guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
First, create a virtual environment with the version of Python you're going to use and activate it.
**macOS/Linux**
```python -m venv env
source env/bin/activate
```
**Windows**
``` python -m venv env
env\Scripts\activate
```
To use 🤗 Transformers, you must install at least one of Flax, PyTorch, or TensorFlow. Refer to the official installation guides for platform-specific commands:
[TensorFlow installation page](https://www.tensorflow.org/install/),
[PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) and/or [Flax](https://github.com/google/flax#quick-install) and [Jax](https://github.com/google/jax#installation)
Then, you will need to install at least one of Flax, PyTorch, or TensorFlow.
Please refer to [TensorFlow installation page](https://www.tensorflow.org/install/), [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) and/or [Flax](https://github.com/google/flax#quick-install) and [Jax](https://github.com/google/jax#installation) installation pages regarding the specific installation command for your platform.
When one of those backends has been installed, 🤗 Transformers can be installed using pip as follows:
```
```bash
pip install transformers
```
If you'd like to play with the examples or need the bleeding edge of the code and can't wait for a new release, you must [install the library from source](https://huggingface.co/docs/transformers/installation#installing-from-source).
```
git clone https://github.com/huggingface/transformers.git
cd transformers
pip install .
```
### With conda
🤗 Transformers can be installed using conda as follows:

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<b>Deutsch</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -246,7 +254,7 @@ Das Modell selbst ist ein reguläres [PyTorch `nn.Module`](https://pytorch.org/d
### Mit pip
Dieses Repository wurde mit Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ und TensorFlow 2.6+ getestet.
Dieses Repository wurde mit Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ und TensorFlow 2.6+ getestet.
Sie sollten 🤗 Transformers in einer [virtuellen Umgebung](https://docs.python.org/3/library/venv.html) installieren. Wenn Sie mit virtuellen Python-Umgebungen nicht vertraut sind, schauen Sie sich den [Benutzerleitfaden](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) an.

View File

@ -20,31 +20,39 @@ limitations under the License.
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<b>Español</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -222,7 +230,7 @@ El modelo en si es un [Pytorch `nn.Module`](https://pytorch.org/docs/stable/nn.h
### Con pip
Este repositorio está probado en Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ y TensorFlow 2.6+.
Este repositorio está probado en Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ y TensorFlow 2.6+.
Deberías instalar 🤗 Transformers en un [entorno virtual](https://docs.python.org/3/library/venv.html). Si no estas familiarizado con los entornos virtuales de Python, consulta la [guía de usuario](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Construction" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="Version GitHub" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Pacte des contributeurs" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<b>Français</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -243,7 +251,7 @@ Le modèle lui-même est un module [`nn.Module` PyTorch](https://pytorch.org/doc
### Avec pip
Ce référentiel est testé sur Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ et TensorFlow 2.6+.
Ce référentiel est testé sur Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ et TensorFlow 2.6+.
Vous devriez installer 🤗 Transformers dans un [environnement virtuel](https://docs.python.org/3/library/venv.html). Si vous n'êtes pas familier avec les environnements virtuels Python, consultez le [guide utilisateur](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).

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@ -45,31 +45,39 @@ checkpoint: जाँच बिंदु
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<b>हिन्दी</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -198,7 +206,7 @@ checkpoint: जाँच बिंदु
### पिप का उपयोग करना
इस रिपॉजिटरी का परीक्षण Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ और TensorFlow 2.6+ के तहत किया गया है।
इस रिपॉजिटरी का परीक्षण Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ और TensorFlow 2.6+ के तहत किया गया है।
आप [वर्चुअल एनवायरनमेंट](https://docs.python.org/3/library/venv.html) में 🤗 ट्रांसफॉर्मर इंस्टॉल कर सकते हैं। यदि आप अभी तक पायथन के वर्चुअल एनवायरनमेंट से परिचित नहीं हैं, तो कृपया इसे [उपयोगकर्ता निर्देश](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) पढ़ें।

View File

@ -55,31 +55,39 @@ user: ユーザ
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<b>日本語</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -256,7 +264,7 @@ Hugging Faceチームによって作られた **[トランスフォーマーを
### pipにて
このリポジトリは、Python 3.9+, Flax 0.4.1+, PyTorch 2.0+, TensorFlow 2.6+ でテストされています。
このリポジトリは、Python 3.8+, Flax 0.4.1+, PyTorch 1.11+, TensorFlow 2.6+ でテストされています。
🤗Transformersは[仮想環境](https://docs.python.org/3/library/venv.html)にインストールする必要があります。Pythonの仮想環境に慣れていない場合は、[ユーザーガイド](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)を確認してください。

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@ -15,60 +15,56 @@ limitations under the License.
-->
<p align="center">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/transformers-logo-dark.svg">
<source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/transformers-logo-light.svg">
<img alt="Hugging Face Transformers Library" src="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/transformers-logo-light.svg" width="352" height="59" style="max-width: 100%;">
</picture>
<br/>
<br/>
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers_logo_name.png" width="400"/>
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<b>한국어</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
<h3 align="center">
<p> Jax, Pytorch, TensorFlow를 위한 최첨단 머신러닝</p>
<p> Jax, Pytorch, TensorFlow를 위한 최첨단 자연어처리</p>
</h3>
<h3 align="center">
<a href="https://hf.co/course"><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/course_banner.png"></a>
</h3>
🤗 Transformers는 텍스트, 비전, 오디오와 같은 다양한 분야에서 여러 과제를 수행하는 수천 개의 사전 학습된 모델을 제공합니다.
제공되는 모델을 통해 다음 과제를 수행할 수 있습니다.
- 📝 텍스트: 100개 이상의 언어들로, 텍스트 분류, 정보 추출, 질문 답변, 요약, 번역 및 문장 생성
- 🖼️ 이미지: 이미지 분류(Image Classification), 객체 탐지(Object Detection) 및 분할(Segmentation)
- 🗣️ 오디오: 음성 인식(Speech Recognition) 및 오디오 분류(Audio Classification)
Transformer의 모델은 표를 통한 질의응답(Table QA), 광학 문자 인식(Optical Character Recognition), 스캔 한 문서에서 정보 추출, 비디오 분류 및 시각적 질의응답과 같은 **여러 분야가 결합된** 과제 또한 수행할 수 있습니다.
🤗 Transformers는 분류, 정보 추출, 질문 답변, 요약, 번역, 문장 생성 등을 100개 이상의 언어로 수행할 수 있는 수천개의 사전학습된 모델을 제공합니다. 우리의 목표는 모두가 최첨단의 NLP 기술을 쉽게 사용하는 것입니다.
🤗 Transformers는 이러한 사전학습 모델을 빠르게 다운로드해 특정 텍스트에 사용하고, 원하는 데이터로 fine-tuning해 커뮤니티나 우리의 [모델 허브](https://huggingface.co/models)에 공유할 수 있도록 API를 제공합니다. 또한, 모델 구조를 정의하는 각 파이썬 모듈은 완전히 독립적이여서 연구 실험을 위해 손쉽게 수정할 수 있습니다.
@ -76,11 +72,9 @@ Transformer의 모델은 표를 통한 질의응답(Table QA), 광학 문자 인
## 온라인 데모
대부분의 모델을 [모델 허브](https://huggingface.co/models) 페이지에서 바로 테스트해 볼 수 있습니다. 공개 및 비공개 모델을 위한 [비공개 모델 호스팅, 버전 관리, 추론 API](https://huggingface.co/pricing)도 제공합니다.
대부분의 모델을 [모델 허브](https://huggingface.co/models) 페이지에서 바로 테스트해볼 수 있습니다. 공개 및 비공개 모델을 위한 [비공개 모델 호스팅, 버전 관리, 추론 API](https://huggingface.co/pricing)도 제공합니다.
아래 몇 가지 예시가 있습니다:
자연어 처리:
예시:
- [BERT로 마스킹된 단어 완성하기](https://huggingface.co/google-bert/bert-base-uncased?text=Paris+is+the+%5BMASK%5D+of+France)
- [Electra를 이용한 개체명 인식](https://huggingface.co/dbmdz/electra-large-discriminator-finetuned-conll03-english?text=My+name+is+Sarah+and+I+live+in+London+city)
- [GPT-2로 텍스트 생성하기](https://huggingface.co/openai-community/gpt2?text=A+long+time+ago%2C+)
@ -89,100 +83,45 @@ Transformer의 모델은 표를 통한 질의응답(Table QA), 광학 문자 인
- [DistilBERT를 이용한 질문 답변](https://huggingface.co/distilbert/distilbert-base-uncased-distilled-squad?text=Which+name+is+also+used+to+describe+the+Amazon+rainforest+in+English%3F&context=The+Amazon+rainforest+%28Portuguese%3A+Floresta+Amaz%C3%B4nica+or+Amaz%C3%B4nia%3B+Spanish%3A+Selva+Amaz%C3%B3nica%2C+Amazon%C3%ADa+or+usually+Amazonia%3B+French%3A+For%C3%AAt+amazonienne%3B+Dutch%3A+Amazoneregenwoud%29%2C+also+known+in+English+as+Amazonia+or+the+Amazon+Jungle%2C+is+a+moist+broadleaf+forest+that+covers+most+of+the+Amazon+basin+of+South+America.+This+basin+encompasses+7%2C000%2C000+square+kilometres+%282%2C700%2C000+sq+mi%29%2C+of+which+5%2C500%2C000+square+kilometres+%282%2C100%2C000+sq+mi%29+are+covered+by+the+rainforest.+This+region+includes+territory+belonging+to+nine+nations.+The+majority+of+the+forest+is+contained+within+Brazil%2C+with+60%25+of+the+rainforest%2C+followed+by+Peru+with+13%25%2C+Colombia+with+10%25%2C+and+with+minor+amounts+in+Venezuela%2C+Ecuador%2C+Bolivia%2C+Guyana%2C+Suriname+and+French+Guiana.+States+or+departments+in+four+nations+contain+%22Amazonas%22+in+their+names.+The+Amazon+represents+over+half+of+the+planet%27s+remaining+rainforests%2C+and+comprises+the+largest+and+most+biodiverse+tract+of+tropical+rainforest+in+the+world%2C+with+an+estimated+390+billion+individual+trees+divided+into+16%2C000+species)
- [T5로 번역하기](https://huggingface.co/google-t5/t5-base?text=My+name+is+Wolfgang+and+I+live+in+Berlin)
컴퓨터 비전:
- [ViT와 함께하는 이미지 분류](https://huggingface.co/google/vit-base-patch16-224)
- [DETR로 객체 탐지하기](https://huggingface.co/facebook/detr-resnet-50)
- [SegFormer로 의미적 분할(semantic segmentation)하기](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512)
- [Mask2Former로 판옵틱 분할(panoptic segmentation)하기](https://huggingface.co/facebook/mask2former-swin-large-coco-panoptic)
- [Depth Anything으로 깊이 추정(depth estimation)하기](https://huggingface.co/docs/transformers/main/model_doc/depth_anything)
- [VideoMAE와 함께하는 비디오 분류](https://huggingface.co/docs/transformers/model_doc/videomae)
- [OneFormer로 유니버설 분할(universal segmentation)하기](https://huggingface.co/shi-labs/oneformer_ade20k_dinat_large)
오디오:
- [Whisper와 함께하는 자동 음성 인식](https://huggingface.co/openai/whisper-large-v3)
- [Wav2Vec2로 키워드 검출(keyword spotting)하기](https://huggingface.co/superb/wav2vec2-base-superb-ks)
- [Audio Spectrogram Transformer로 오디오 분류하기](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593)
멀티 모달(Multimodal Task):
- [TAPAS로 표 안에서 질문 답변하기](https://huggingface.co/google/tapas-base-finetuned-wtq)
- [ViLT와 함께하는 시각적 질의응답](https://huggingface.co/dandelin/vilt-b32-finetuned-vqa)
- [LLaVa로 이미지에 설명 넣기](https://huggingface.co/llava-hf/llava-1.5-7b-hf)
- [SigLIP와 함께하는 제로 샷(zero-shot) 이미지 분류](https://huggingface.co/google/siglip-so400m-patch14-384)
- [LayoutLM으로 문서 안에서 질문 답변하기](https://huggingface.co/impira/layoutlm-document-qa)
- [X-CLIP과 함께하는 제로 샷(zero-shot) 비디오 분류](https://huggingface.co/docs/transformers/model_doc/xclip)
- [OWLv2로 진행하는 제로 샷(zero-shot) 객체 탐지](https://huggingface.co/docs/transformers/en/model_doc/owlv2)
- [CLIPSeg로 진행하는 제로 샷(zero-shot) 이미지 분할](https://huggingface.co/docs/transformers/model_doc/clipseg)
- [SAM과 함께하는 자동 마스크 생성](https://huggingface.co/docs/transformers/model_doc/sam)
**[Transformer와 글쓰기](https://transformer.huggingface.co)** 는 이 저장소의 텍스트 생성 능력에 관한 Hugging Face 팀의 공식 데모입니다.
## Transformers를 사용한 100개의 프로젝트
## Hugging Face 팀의 커스텀 지원을 원한다면
Transformers는 사전 학습된 모델들을 이용하는 도구를 넘어 Transformers와 함께 빌드 된 프로젝트 및 Hugging Face Hub를 위한 하나의 커뮤니티입니다. 우리는 Transformers를 통해 개발자, 연구자, 학생, 교수, 엔지니어 및 모든 이들이 꿈을 품은 프로젝트(Dream Project)를 빌드 할 수 있길 바랍니다.
Transformers에 달린 100,000개의 별을 축하하기 위해, 우리는 커뮤니티를 주목하고자 Transformers를 품고 빌드 된 100개의 어마어마한 프로젝트들을 선별하여 [awesome-transformers](https://github.com/huggingface/transformers/blob/main/awesome-transformers.md) 페이지에 나열하였습니다.
만일 소유한 혹은 사용하고 계신 프로젝트가 이 리스트에 꼭 등재되어야 한다고 믿으신다면, PR을 열고 추가하여 주세요!
## 조직 안에서 AI 사용에 대해 진지하게 고민 중이신가요? Hugging Face Enterprise Hub을 통해 더 빨리 구축해 보세요.
<a target="_blank" href="https://huggingface.co/enterprise">
<img alt="Hugging Face Enterprise Hub" src="https://github.com/user-attachments/assets/247fb16d-d251-4583-96c4-d3d76dda4925">
<a target="_blank" href="https://huggingface.co/support">
<img alt="HuggingFace Expert Acceleration Program" src="https://huggingface.co/front/thumbnails/support.png" style="max-width: 600px; border: 1px solid #eee; border-radius: 4px; box-shadow: 0 1px 2px 0 rgba(0, 0, 0, 0.05);">
</a><br>
## 퀵 투어
주어진 입력(텍스트, 이미지, 오디오, ...)에 바로 모델을 사용할 수 있도록, 우리는 `pipeline` API를 제공합니다. Pipeline은 사전학습 모델과 그 모델을 학습할 때 적용한 전처리 방식을 하나로 합칩니다. 다음은 긍정적인 텍스트와 부정적인 텍스트를 분류하기 위해 pipeline을 사용한 간단한 예시입니다:
원하는 텍스트에 바로 모델을 사용할 수 있도록, 우리는 `pipeline` API를 제공합니다. Pipeline은 사전학습 모델과 그 모델을 학습할 때 적용한 전처리 방식을 하나로 합칩니다. 다음은 긍정적인 텍스트와 부정적인 텍스트를 분류하기 위해 pipeline을 사용한 간단한 예시입니다:
```python
>>> from transformers import pipeline
# 감정 분석 파이프라인을 할당하세요
# Allocate a pipeline for sentiment-analysis
>>> classifier = pipeline('sentiment-analysis')
>>> classifier('We are very happy to introduce pipeline to the transformers repository.')
[{'label': 'POSITIVE', 'score': 0.9996980428695679}]
```
코드의 두 번째 줄은 pipeline이 사용하는 사전학습 모델을 다운로드하고 캐시로 저장합니다. 세 번째 줄에선 그 모델이 주어진 텍스트를 평가합니다. 여기서 모델은 99.97%의 확률로 텍스트가 긍정적이라고 평가했습니다.
코드의 두번째 줄은 pipeline이 사용하는 사전학습 모델을 다운로드하고 캐시로 저장합니다. 세번째 줄에선 그 모델이 주어진 텍스트를 평가합니다. 여기서 모델은 99.97%의 확률로 텍스트가 긍정적이라고 평가했습니다.
자연어 처리(NLP) 뿐만 아니라 컴퓨터 비전, 발화(Speech) 과제들을 사전 학습된 `pipeline`으로 바로 수행할 수 있습니다. 예를 들어, 사진에서 손쉽게 객체들을 탐지할 수 있습니다.:
많은 NLP 과제들을 `pipeline`으로 바로 수행할 수 있습니다. 예를 들어, 질문과 문맥이 주어지면 손쉽게 답변을 추출할 수 있습니다:
``` python
>>> import requests
>>> from PIL import Image
>>> from transformers import pipeline
# 귀여운 고양이가 있는 이미지를 다운로드하세요
>>> url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/coco_sample.png"
>>> image_data = requests.get(url, stream=True).raw
>>> image = Image.open(image_data)
# Allocate a pipeline for question-answering
>>> question_answerer = pipeline('question-answering')
>>> question_answerer({
... 'question': 'What is the name of the repository ?',
... 'context': 'Pipeline has been included in the huggingface/transformers repository'
... })
{'score': 0.30970096588134766, 'start': 34, 'end': 58, 'answer': 'huggingface/transformers'}
# 객체 감지를 위한 파이프라인을 할당하세요
>>> object_detector = pipeline('object-detection')
>>> object_detector(image)
[{'score': 0.9982201457023621,
'label': 'remote',
'box': {'xmin': 40, 'ymin': 70, 'xmax': 175, 'ymax': 117}},
{'score': 0.9960021376609802,
'label': 'remote',
'box': {'xmin': 333, 'ymin': 72, 'xmax': 368, 'ymax': 187}},
{'score': 0.9954745173454285,
'label': 'couch',
'box': {'xmin': 0, 'ymin': 1, 'xmax': 639, 'ymax': 473}},
{'score': 0.9988006353378296,
'label': 'cat',
'box': {'xmin': 13, 'ymin': 52, 'xmax': 314, 'ymax': 470}},
{'score': 0.9986783862113953,
'label': 'cat',
'box': {'xmin': 345, 'ymin': 23, 'xmax': 640, 'ymax': 368}}]
```
위와 같이, 우리는 이미지에서 탐지된 객체들에 대하여 객체를 감싸는 박스와 확률 리스트를 얻을 수 있습니다. 왼쪽이 원본 이미지이며 오른쪽은 해당 이미지에 탐지된 결과를 표시하였습니다.
<h3 align="center">
<a><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/coco_sample.png" width="400"></a>
<a><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/coco_sample_post_processed.png" width="400"></a>
</h3>
[이 튜토리얼](https://huggingface.co/docs/transformers/ko/task_summary)에서 `pipeline` API가 지원하는 다양한 과제를 확인할 수 있습니다.
답변뿐만 아니라, 여기에 사용된 사전학습 모델은 확신도와 토크나이즈된 문장 속 답변의 시작점, 끝점까지 반환합니다. [이 튜토리얼](https://huggingface.co/docs/transformers/task_summary)에서 `pipeline` API가 지원하는 다양한 과제를 확인할 수 있습니다.
코드 3줄로 원하는 과제에 맞게 사전학습 모델을 다운로드 받고 사용할 수 있습니다. 다음은 PyTorch 버전입니다:
```python
@ -207,24 +146,24 @@ Transformers에 달린 100,000개의 별을 축하하기 위해, 우리는 커
토크나이저는 사전학습 모델의 모든 전처리를 책임집니다. 그리고 (위의 예시처럼) 1개의 스트링이나 리스트도 처리할 수 있습니다. 토크나이저는 딕셔너리를 반환하는데, 이는 다운스트림 코드에 사용하거나 언패킹 연산자 ** 를 이용해 모델에 바로 전달할 수도 있습니다.
모델 자체는 일반적으로 사용되는 [Pytorch `nn.Module`](https://pytorch.org/docs/stable/nn.html#torch.nn.Module)나 [TensorFlow `tf.keras.Model`](https://www.tensorflow.org/api_docs/python/tf/keras/Model)입니다. [이 튜토리얼](https://huggingface.co/docs/transformers/ko/training)은 이러한 모델을 표준적인 PyTorch나 TensorFlow 학습 과정에서 사용하는 방법, 또는 새로운 데이터로 파인 튜닝하기 위해 `Trainer` API를 사용하는 방법을 설명해 줍니다.
모델 자체는 일반적으로 사용되는 [Pytorch `nn.Module`](https://pytorch.org/docs/stable/nn.html#torch.nn.Module)나 [TensorFlow `tf.keras.Model`](https://www.tensorflow.org/api_docs/python/tf/keras/Model)입니다. [이 튜토리얼](https://huggingface.co/transformers/training.html)은 이러한 모델을 표준적인 PyTorch나 TensorFlow 학습 과정에서 사용하는 방법, 또는 새로운 데이터로 fine-tune하기 위해 `Trainer` API를 사용하는 방법을 설명해줍니다.
## 왜 transformers를 사용해야 할까요?
1. 손쉽게 사용할 수 있는 최첨단 모델:
- 자연어 이해(NLU)생성(NLG), 컴퓨터 비전, 오디오 과제에서 뛰어난 성능을 보입니다.
- 교육자 실무자에게 진입 장벽이 낮습니다.
- NLU와 NLG 과제에서 뛰어난 성능을 보입니다.
- 교육자 실무자에게 진입 장벽이 낮습니다.
- 3개의 클래스만 배우면 바로 사용할 수 있습니다.
- 하나의 API로 모든 사전학습 모델을 사용할 수 있습니다.
1. 더 적은 계산 비용, 더 적은 탄소 발자국:
- 연구자들은 모델을 계속 다시 학습시키는 대신 학습된 모델을 공유할 수 있습니다.
- 실무자들은 학습에 필요한 시간과 비용을 절약할 수 있습니다.
- 모든 분야를 통틀어서 400,000개 이상의 사전 학습 모델이 있는 수십 개의 아키텍처.
- 수십개의 모델 구조, 2,000개 이상의 사전학습 모델, 100개 이상의 언어로 학습된 모델 등.
1. 모델의 각 생애주기에 적합한 프레임워크:
- 코드 3줄로 최첨단 모델을 학습하세요.
- 목적에 알맞게 모델을 TF2.0/Pytorch/Jax 프레임 워크 중 하나로 이동시키세요.
- 자유롭게 모델을 TF2.0PyTorch 프레임워크로 변환하세요.
- 학습, 평가, 공개 등 각 단계에 맞는 프레임워크를 원하는대로 선택하세요.
1. 필요한 대로 모델이나 예시를 커스터마이즈하세요:
@ -235,14 +174,14 @@ Transformers에 달린 100,000개의 별을 축하하기 위해, 우리는 커
## 왜 transformers를 사용하지 말아야 할까요?
- 이 라이브러리는 신경망 블록을 만들기 위한 모듈이 아닙니다. 연구자들이 여러 파일을 살펴보지 않고 바로 각 모델을 사용할 수 있도록, 모델 파일 코드의 추상화 수준을 적정하게 유지했습니다.
- 학습 API는 모든 모델에 적용할 수 있도록 만들어지진 않았지만, 라이브러리가 제공하는 모델들에 적용할 수 있도록 최적화되었습니다. 일반적인 머신 러닝을 위해선, 다른 라이브러리를 사용하세요(예를 들면, [Accelerate](https://huggingface.co/docs/accelerate/index)).
- 학습 API는 모든 모델에 적용할 수 있도록 만들어지진 않았지만, 라이브러리가 제공하는 모델들에 적용할 수 있도록 최적화되었습니다. 일반적인 머신 러닝을 위해선, 다른 라이브러리를 사용하세요.
- 가능한 많은 사용 예시를 보여드리고 싶어서, [예시 폴더](https://github.com/huggingface/transformers/tree/main/examples)의 스크립트를 준비했습니다. 이 스크립트들을 수정 없이 특정한 문제에 바로 적용하지 못할 수 있습니다. 필요에 맞게 일부 코드를 수정해야 할 수 있습니다.
## 설치
### pip로 설치하기
이 저장소는 Python 3.9+, Flax 0.4.1+, PyTorch 2.0+, TensorFlow 2.6+에서 테스트 되었습니다.
이 저장소는 Python 3.8+, Flax 0.4.1+, PyTorch 1.11+, TensorFlow 2.6+에서 테스트 되었습니다.
[가상 환경](https://docs.python.org/3/library/venv.html)에 🤗 Transformers를 설치하세요. Python 가상 환경에 익숙하지 않다면, [사용자 가이드](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)를 확인하세요.
@ -257,7 +196,7 @@ Transformers에 달린 100,000개의 별을 축하하기 위해, 우리는 커
pip install transformers
```
예시들을 체험해보고 싶거나, 최최최첨단 코드를 원하거나, 새로운 버전이 나올 때까지 기다릴 수 없다면 [라이브러리를 소스에서 바로 설치](https://huggingface.co/docs/transformers/ko/installation#install-from-source)하셔야 합니다.
예시들을 체험해보고 싶거나, 최최최첨단 코드를 원하거나, 새로운 버전이 나올 때까지 기다릴 수 없다면 [라이브러리를 소스에서 바로 설치](https://huggingface.co/docs/transformers/installation#installing-from-source)하셔야 합니다.
### conda로 설치하기
@ -271,30 +210,29 @@ conda install conda-forge::transformers
Flax, PyTorch, TensorFlow 설치 페이지에서 이들을 conda로 설치하는 방법을 확인하세요.
> **_노트:_** 윈도우 환경에서 캐싱의 이점을 위해 개발자 모드를 활성화할 수 있습니다. 만약 여러분에게 있어서 선택이 아닌 필수라면 [이 이슈](https://github.com/huggingface/huggingface_hub/issues/1062)를 통해 알려주세요.
## 모델 구조
**🤗 Transformers가 제공하는 [모든 모델 체크포인트](https://huggingface.co/models)** 는 huggingface.co [모델 허브](https://huggingface.co/models)에 완벽히 연동되어 있습니다. [개인](https://huggingface.co/users)과 [기관](https://huggingface.co/organizations)이 모델 허브에 직접 업로드할 수 있습니다.
**🤗 Transformers가 제공하는 [모든 모델 체크포인트](https://huggingface.co/models)** 는 huggingface.co [모델 허브](https://huggingface.co)에 완벽히 연동되어 있습니다. [개인](https://huggingface.co/users)과 [기관](https://huggingface.co/organizations)이 모델 허브에 직접 업로드할 수 있습니다.
현재 사용 가능한 모델 체크포인트의 개수: ![](https://img.shields.io/endpoint?url=https://huggingface.co/api/shields/models&color=brightgreen)
🤗 Transformers는 다음 모델들을 제공합니다: 각 모델의 요약은 [여기](https://huggingface.co/docs/transformers/ko/model_summary)서 확인하세요.
🤗 Transformers는 다음 모델들을 제공합니다: 각 모델의 요약은 [여기](https://huggingface.co/docs/transformers/model_summary)서 확인하세요.
각 모델이 Flax, PyTorch, TensorFlow으로 구현되었는지 또는 🤗 Tokenizers 라이브러리가 지원하는 토크나이저를 사용하는지 확인하려면, [이 표](https://huggingface.co/docs/transformers/ko/index#supported-framework)를 확인하세요.
각 모델이 Flax, PyTorch, TensorFlow으로 구현되었는지 또는 🤗 Tokenizers 라이브러리가 지원하는 토크나이저를 사용하는지 확인하려면, [이 표](https://huggingface.co/docs/transformers/index#supported-frameworks)를 확인하세요.
이 구현은 여러 데이터로 검증되었고 (예시 스크립트를 참고하세요) 오리지널 구현의 성능과 같아야 합니다. [도큐먼트](https://github.com/huggingface/transformers/tree/main/examples)의 Examples 섹션에서 성능에 대한 자세한 설명을 확인할 수 있습니다.
이 구현은 여러 데이터로 검증되었고 (예시 스크립트를 참고하세요) 오리지널 구현의 성능과 같아야 합니다. [도큐먼트](https://huggingface.co/docs/transformers/examples)의 Examples 섹션에서 성능에 대한 자세한 설명을 확인할 수 있습니다.
## 더 알아보기
| 섹션 | 설명 |
|-|-|
| [도큐먼트](https://huggingface.co/transformers/ko/) | 전체 API 도큐먼트와 튜토리얼 |
| [과제 요약](https://huggingface.co/docs/transformers/ko/task_summary) | 🤗 Transformers가 지원하는 과제들 |
| [전처리 튜토리얼](https://huggingface.co/docs/transformers/ko/preprocessing) | `Tokenizer` 클래스를 이용해 모델을 위한 데이터 준비하기 |
| [학습과 파인 튜닝](https://huggingface.co/docs/transformers/ko/training) | 🤗 Transformers가 제공하는 모델 PyTorch/TensorFlow 학습 과정과 `Trainer` API에서 사용하기 |
| [퀵 투어: 파인 튜닝/사용 스크립트](https://github.com/huggingface/transformers/tree/main/examples) | 다양한 과제에서 모델을 파인 튜닝하는 예시 스크립트 |
| [모델 공유 및 업로드](https://huggingface.co/docs/transformers/ko/model_sharing) | 커뮤니티에 파인 튜닝된 모델을 업로드 및 공유하기 |
| [도큐먼트](https://huggingface.co/transformers/) | 전체 API 도큐먼트와 튜토리얼 |
| [과제 요약](https://huggingface.co/docs/transformers/task_summary) | 🤗 Transformers가 지원하는 과제들 |
| [전처리 튜토리얼](https://huggingface.co/docs/transformers/preprocessing) | `Tokenizer` 클래스를 이용해 모델을 위한 데이터 준비하기 |
| [학습과 fine-tuning](https://huggingface.co/docs/transformers/training) | 🤗 Transformers가 제공하는 모델 PyTorch/TensorFlow 학습 과정과 `Trainer` API에서 사용하기 |
| [퀵 투어: Fine-tuning/사용 스크립트](https://github.com/huggingface/transformers/tree/main/examples) | 다양한 과제에서 모델 fine-tuning하는 예시 스크립트 |
| [모델 공유 및 업로드](https://huggingface.co/docs/transformers/model_sharing) | 커뮤니티에 fine-tune된 모델을 업로드 및 공유하기 |
| [마이그레이션](https://huggingface.co/docs/transformers/migration) | `pytorch-transformers``pytorch-pretrained-bert`에서 🤗 Transformers로 이동하기|
## 인용

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<b>Рortuguês</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -253,7 +261,7 @@ O modelo em si é um [Pytorch `nn.Module`](https://pytorch.org/docs/stable/nn.ht
### Com pip
Este repositório é testado no Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ e TensorFlow 2.6+.
Este repositório é testado no Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ e TensorFlow 2.6+.
Você deve instalar o 🤗 Transformers em um [ambiente virtual](https://docs.python.org/3/library/venv.html). Se você não está familiarizado com ambientes virtuais em Python, confira o [guia do usuário](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<b>Русский</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
<p>
</h4>
@ -77,7 +85,7 @@ limitations under the License.
## Онлайн демонстрация
Большинство наших моделей можно протестировать непосредственно на их страницах с [сайта](https://huggingface.co/models). Мы также предлагаем [приватный хостинг моделей, контроль версий и API для выводов](https://huggingface.co/pricing) для публичных и частных моделей.
Большинство наших моделей можно протестировать непосредственно на их страницах с [сайта](https://huggingface.co/models). Мы также предлагаем [привтаный хостинг моделей, контроль версий и API для выводов](https://huggingface.co/pricing) для публичных и частных моделей.
Вот несколько примеров:
@ -244,7 +252,7 @@ Hugging Face Hub. Мы хотим, чтобы Transformers позволил ра
### С помощью pip
Данный репозиторий протестирован на Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ и TensorFlow 2.6+.
Данный репозиторий протестирован на Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ и TensorFlow 2.6+.
Устанавливать 🤗 Transformers следует в [виртуальной среде](https://docs.python.org/3/library/venv.html). Если вы не знакомы с виртуальными средами Python, ознакомьтесь с [руководством пользователя](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).

View File

@ -26,11 +26,21 @@ limitations under the License.
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
@ -38,20 +48,18 @@ limitations under the License.
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<b>తెలుగు</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -246,7 +254,7 @@ limitations under the License.
### పిప్ తో
ఈ రిపోజిటరీ పైథాన్ 3.9+, ఫ్లాక్స్ 0.4.1+, PyTorch 2.0+ మరియు TensorFlow 2.6+లో పరీక్షించబడింది.
ఈ రిపోజిటరీ పైథాన్ 3.8+, ఫ్లాక్స్ 0.4.1+, PyTorch 1.11+ మరియు TensorFlow 2.6+లో పరీక్షించబడింది.
మీరు [వర్చువల్ వాతావరణం](https://docs.python.org/3/library/venv.html)లో 🤗 ట్రాన్స్‌ఫార్మర్‌లను ఇన్‌స్టాల్ చేయాలి. మీకు పైథాన్ వర్చువల్ పరిసరాల గురించి తెలియకుంటే, [యూజర్ గైడ్](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) చూడండి.

View File

@ -25,31 +25,39 @@ limitations under the License.
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<b>Tiếng việt</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
</p>
</h4>
@ -245,7 +253,7 @@ Chính mô hình là một [Pytorch `nn.Module`](https://pytorch.org/docs/stable
### Sử dụng pip
Thư viện này được kiểm tra trên Python 3.9+, Flax 0.4.1+, PyTorch 2.0+ và TensorFlow 2.6+.
Thư viện này được kiểm tra trên Python 3.8+, Flax 0.4.1+, PyTorch 1.11+ và TensorFlow 2.6+.
Bạn nên cài đặt 🤗 Transformers trong một [môi trường ảo Python](https://docs.python.org/3/library/venv.html). Nếu bạn chưa quen với môi trường ảo Python, hãy xem [hướng dẫn sử dụng](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).

View File

@ -45,11 +45,21 @@ checkpoint: 检查点
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
@ -57,19 +67,17 @@ checkpoint: 检查点
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<b>简体中文</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_vi.md">Tiếng Việt</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ar.md">العربية</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ur.md">اردو</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -198,7 +206,7 @@ checkpoint: 检查点
### 使用 pip
这个仓库已在 Python 3.9+、Flax 0.4.1+、PyTorch 2.0+ 和 TensorFlow 2.6+ 下经过测试。
这个仓库已在 Python 3.8+、Flax 0.4.1+、PyTorch 1.11+ 和 TensorFlow 2.6+ 下经过测试。
你可以在[虚拟环境](https://docs.python.org/3/library/venv.html)中安装 🤗 Transformers。如果你还不熟悉 Python 的虚拟环境,请阅此[用户说明](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)。

View File

@ -57,31 +57,39 @@ user: 使用者
<br>
</p>
<p align="center">
<a href="https://circleci.com/gh/huggingface/transformers"><img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main"></a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue"></a>
<a href="https://huggingface.co/docs/transformers/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online"></a>
<a href="https://github.com/huggingface/transformers/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg"></a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md"><img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg"></a>
<a href="https://circleci.com/gh/huggingface/transformers">
<img alt="Build" src="https://img.shields.io/circleci/build/github/huggingface/transformers/main">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/LICENSE">
<img alt="GitHub" src="https://img.shields.io/github/license/huggingface/transformers.svg?color=blue">
</a>
<a href="https://huggingface.co/docs/transformers/index">
<img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/transformers/index.svg?down_color=red&down_message=offline&up_message=online">
</a>
<a href="https://github.com/huggingface/transformers/releases">
<img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/transformers.svg">
</a>
<a href="https://github.com/huggingface/transformers/blob/main/CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg">
</a>
<a href="https://zenodo.org/badge/latestdoi/155220641"><img src="https://zenodo.org/badge/155220641.svg" alt="DOI"></a>
</p>
<h4 align="center">
<p>
<a href="https://github.com/huggingface/transformers/">English</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_zh-hans.md">简体中文</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_zh-hans.md">简体中文</a> |
<b>繁體中文</b> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_ko.md">한국어</a> |
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<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/i18n/README_te.md">తెలుగు</a> |
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<a href="https://github.com/huggingface/transformers/blob/main/README_ja.md">日本語</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_hd.md">हिन्दी</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_pt-br.md">Рortuguês</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_te.md">తెలుగు</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_fr.md">Français</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_de.md">Deutsch</a> |
<a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
</p>
</h4>
@ -210,7 +218,7 @@ Tokenizer 為所有的預訓練模型提供了預處理,並可以直接轉換
### 使用 pip
這個 Repository 已在 Python 3.9+、Flax 0.4.1+、PyTorch 2.0+ 和 TensorFlow 2.6+ 下經過測試。
這個 Repository 已在 Python 3.8+、Flax 0.4.1+、PyTorch 1.11+ 和 TensorFlow 2.6+ 下經過測試。
你可以在[虛擬環境](https://docs.python.org/3/library/venv.html)中安裝 🤗 Transformers。如果你還不熟悉 Python 的虛擬環境,請閱此[使用者指引](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)。

View File

@ -14,7 +14,7 @@ Models uploaded on the Hugging Face Hub come in different formats. We heavily re
models in the [`safetensors`](https://github.com/huggingface/safetensors) format (which is the default prioritized
by the transformers library), as developed specifically to prevent arbitrary code execution on your system.
To avoid loading models from unsafe formats(e.g. [pickle](https://docs.python.org/3/library/pickle.html), you should use the `use_safetensors` parameter. If doing so, in the event that no .safetensors file is present, transformers will error when loading the model.
To avoid loading models from unsafe formats(e.g. [pickle](https://docs.python.org/3/library/pickle.html), you should use the `use_safetenstors` parameter. If doing so, in the event that no .safetensors file is present, transformers will error when loading the model.
### Remote code
@ -36,4 +36,5 @@ Please inspect the code of the tools before passing them to the Agent to protect
## Reporting a Vulnerability
Feel free to submit vulnerability reports to [security@huggingface.co](mailto:security@huggingface.co), where someone from the HF security team will review and recommend next steps. If reporting a vulnerability specific to open source, please note [Huntr](https://huntr.com) is a vulnerability disclosure program for open source software.
🤗 Please feel free to submit vulnerability reports to our private bug bounty program at https://hackerone.com/hugging_face. You'll need to request access to the program by emailing security@huggingface.co.
Note that you'll need to be invited to our program, so send us a quick email at security@huggingface.co if you've found a vulnerability.

View File

@ -15,7 +15,7 @@ to add it.
Keywords: Open-source, LLaMa, GPT-J, instruction, assistant
## [recommenders](https://github.com/recommenders-team/recommenders)
## [recommenders](https://github.com/microsoft/recommenders)
This repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It goes over several aspects required to build efficient recommendation systems: data preparation, modeling, evaluation, model selection & optimization, as well as operationalization
@ -39,15 +39,15 @@ MindsDB is a low-code ML platform, which automates and integrates several ML fra
Keywords: Database, low-code, AI table
## [langchain](https://github.com/langchain-ai/langchain)
## [langchain](https://github.com/hwchase17/langchain)
[langchain](https://github.com/langchain-ai/langchain) is aimed at assisting in the development of apps merging both LLMs and other sources of knowledge. The library allows chaining calls to applications, creating a sequence across many tools.
[langchain](https://github.com/hwchase17/langchain) is aimed at assisting in the development of apps merging both LLMs and other sources of knowledge. The library allows chaining calls to applications, creating a sequence across many tools.
Keywords: LLMs, Large Language Models, Agents, Chains
## [LlamaIndex](https://github.com/run-llama/llama_index)
## [LlamaIndex](https://github.com/jerryjliu/llama_index)
[LlamaIndex](https://github.com/run-llama/llama_index) is a project that provides a central interface to connect your LLM's with external data. It provides various kinds of indices and retreival mechanisms to perform different LLM tasks and obtain knowledge-augmented results.
[LlamaIndex](https://github.com/jerryjliu/llama_index) is a project that provides a central interface to connect your LLM's with external data. It provides various kinds of indices and retreival mechanisms to perform different LLM tasks and obtain knowledge-augmented results.
Keywords: LLMs, Large Language Models, Data Retrieval, Indices, Knowledge Augmentation
@ -146,9 +146,9 @@ Keywords: Framework, simplicity, NLP
Keywords: LLM, Agents, HF Hub
## [transformers.js](https://github.com/huggingface/transformers.js/)
## [transformers.js](https://xenova.github.io/transformers.js/)
[transformers.js](https://github.com/huggingface/transformers.js/) is a JavaScript library targeted at running models from transformers directly within the browser.
[transformers.js](https://xenova.github.io/transformers.js/) is a JavaScript library targeted at running models from transformers directly within the browser.
Keywords: Transformers, JavaScript, browser
@ -437,7 +437,7 @@ Keywords: DALL-E, Russian
Keywords: Knowledge Extraction, Knowledge Graphs
## [Nebuly](https://github.com/nebuly-ai/optimate)
## [Nebuly](https://github.com/nebuly-ai/nebuly)
Nebuly is the next-generation platform to monitor and optimize your AI costs in one place. The platform connects to all your AI cost sources (compute, API providers, AI software licenses, etc) and centralizes them in one place to give you full visibility on a model basis. The platform also provides optimization recommendations and a co-pilot model that can guide during the optimization process. The platform builds on top of the open-source tools allowing you to optimize the different steps of your AI stack to squeeze out the best possible cost performances.
@ -596,7 +596,7 @@ Keywords: Data-Centric AI, Data Quality, Noisy Labels, Outlier Detection, Active
## [BentoML](https://github.com/bentoml/BentoML)
[BentoML](https://github.com/bentoml) is the unified framework for building, shipping, and scaling production-ready AI applications incorporating traditional ML, pre-trained AI models, Generative and Large Language Models.
[BentoML](https://github.com/bentoml) is the unified framework for for building, shipping, and scaling production-ready AI applications incorporating traditional ML, pre-trained AI models, Generative and Large Language Models.
All Hugging Face models and pipelines can be seamlessly integrated into BentoML applications, enabling the running of models on the most suitable hardware and independent scaling based on usage.
Keywords: BentoML, Framework, Deployment, AI Applications

View File

@ -1,49 +0,0 @@
# Benchmarks
You might want to add new benchmarks.
You will need to define a python function named `run_benchmark` in your python file and the file must be located in this `benchmark/` directory.
The expected function signature is the following:
```py
def run_benchmark(logger: Logger, branch: str, commit_id: str, commit_msg: str, num_tokens_to_generate=100):
```
## Writing metrics to the database
`MetricRecorder` is thread-safe, in the sense of the python [`Thread`](https://docs.python.org/3/library/threading.html#threading.Thread). This means you can start a background thread to do the readings on the device measurements while not blocking the main thread to execute the model measurements.
cf [`llama.py`](./llama.py) to see an example of this in practice.
```py
from benchmarks_entrypoint import MetricsRecorder
import psycopg2
def run_benchmark(logger: Logger, branch: str, commit_id: str, commit_msg: str, num_tokens_to_generate=100):
metrics_recorder = MetricsRecorder(psycopg2.connect("dbname=metrics"), logger, branch, commit_id, commit_msg)
benchmark_id = metrics_recorder.initialise_benchmark({"gpu_name": gpu_name, "model_id": model_id})
# To collect device measurements
metrics_recorder.collect_device_measurements(
benchmark_id, cpu_util, mem_megabytes, gpu_util, gpu_mem_megabytes
)
# To collect your model measurements
metrics_recorder.collect_model_measurements(
benchmark_id,
{
"model_load_time": model_load_time,
"first_eager_forward_pass_time_secs": first_eager_fwd_pass_time,
"second_eager_forward_pass_time_secs": second_eager_fwd_pass_time,
"first_eager_generate_time_secs": first_eager_generate_time,
"second_eager_generate_time_secs": second_eager_generate_time,
"time_to_first_token_secs": time_to_first_token,
"time_to_second_token_secs": time_to_second_token,
"time_to_third_token_secs": time_to_third_token,
"time_to_next_token_mean_secs": mean_time_to_next_token,
"first_compile_generate_time_secs": first_compile_generate_time,
"second_compile_generate_time_secs": second_compile_generate_time,
"third_compile_generate_time_secs": third_compile_generate_time,
"fourth_compile_generate_time_secs": fourth_compile_generate_time,
},
)
```

View File

@ -1,326 +0,0 @@
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Run benchmark using the `optimum-benchmark` library with some customization in `transformers`.
Assume we are under `transformers` root directory: (make sure the commits are valid commits)
```bash
python benchmark/benchmark.py --config-dir benchmark/config --config-name generation --commit=9b9c7f03da625b13643e99205c691fe046461724 --metrics=decode.latency.mean,per_token.latency.mean,per_token.throughput.value backend.model=google/gemma-2b benchmark.input_shapes.sequence_length=5,7 benchmark.input_shapes.batch_size=1,2 --multirun
```
"""
import argparse
import glob
import json
import os.path
import re
import tempfile
from contextlib import contextmanager
from pathlib import Path
from git import Repo
from huggingface_hub import HfApi
from optimum_benchmark import Benchmark
from optimum_benchmark_wrapper import main
PATH_TO_REPO = Path(__file__).parent.parent.resolve()
@contextmanager
def checkout_commit(repo: Repo, commit_id: str):
"""
Context manager that checks out a given commit when entered, but gets back to the reference it was at on exit.
Args:
repo (`git.Repo`): A git repository (for instance the Transformers repo).
commit_id (`str`): The commit reference to checkout inside the context manager.
"""
current_head = repo.head.commit if repo.head.is_detached else repo.head.ref
try:
repo.git.checkout(commit_id)
yield
finally:
repo.git.checkout(current_head)
def summarize(run_dir, metrics, expand_metrics=False):
"""Produce a summary for each optimum-benchmark launched job's output directory found in `run_dir`.
Each summary's format is as follows (for `expand_metrics=False`):
```
{
"model": "google/gemma-2b",
"commit": "3cd6ed22e4d49219f300f5055e71e3929aba20d7",
"config": "benchmark.input_shapes.batch_size=1,benchmark.input_shapes.sequence_length=5",
"metrics": {
"decode.latency.mean": 1.624666809082031,
"per_token.latency.mean": 0.012843788806628804,
"per_token.throughput.value": 77.85864553330948
}
}
```
"""
reports = glob.glob(os.path.join(run_dir, "**/benchmark_report.json"), recursive=True)
report_dirs = [str(Path(report).parent) for report in reports]
summaries = []
for report_dir in report_dirs:
commit = re.search(r"/commit=([^/]+)", report_dir).groups()[0]
if not os.path.isfile(os.path.join(report_dir, "benchmark.json")):
continue
benchmark = Benchmark.from_json(os.path.join(report_dir, "benchmark.json"))
report = benchmark.report
model = benchmark.config.backend["model"]
# Ths looks like `benchmark.input_shapes.batch_size=1,benchmark.input_shapes.sequence_length=5`.
# (we rely on the usage of hydra's `${hydra.job.override_dirname}`.)
benchmark_name = re.sub(f"backend.model={model},*", "", report_dir)
benchmark_name = str(Path(benchmark_name).parts[-1])
if benchmark_name.startswith("commit="):
benchmark_name = benchmark.config.name
metrics_values = {}
# post-processing of report: show a few selected/important metric
for metric in metrics:
keys = metric.split(".")
value = report.to_dict()
current = metrics_values
for key in keys:
# Avoid KeyError when a user's specified metric has typo.
# TODO: Give warnings.
if key not in value:
continue
value = value[key]
if expand_metrics:
if isinstance(value, dict):
if key not in current:
current[key] = {}
current = current[key]
else:
current[key] = value
if not expand_metrics:
metrics_values[metric] = value
# show some config information
print(f"model: {model}")
print(f"commit: {commit}")
print(f"config: {benchmark_name}")
if len(metrics_values) > 0:
print("metrics:")
if expand_metrics:
print(metrics_values)
else:
for metric, value in metrics_values.items():
print(f" - {metric}: {value}")
print("-" * 80)
summary = {
"model": model,
"commit": commit,
"config": benchmark_name,
"metrics": metrics_values,
}
summaries.append(summary)
with open(os.path.join(report_dir, "summary.json"), "w") as fp:
json.dump(summary, fp, indent=4)
return summaries
def combine_summaries(summaries):
"""Combine a list of summary obtained from the function `summarize`.
The combined summary's format is as follows:
```
"google/gemma-2b": {
"benchmark.input_shapes.batch_size=1,benchmark.input_shapes.sequence_length=5": {
"3cd6ed22e4d49219f300f5055e71e3929aba20d7": {
"metrics": {"decode.latency.mean": 1.624666809082031}
},
"c97ee28b117c0abe8e08891f402065e4df6d72aa": {
"metrics": {"decode.latency.mean": 1.6278163452148438}
}
},
"benchmark.input_shapes.batch_size=2,benchmark.input_shapes.sequence_length=5": {
"3cd6ed22e4d49219f300f5055e71e3929aba20d7": {
"metrics": {"decode.latency.mean": 1.6947791748046876}
},
"c97ee28b117c0abe8e08891f402065e4df6d72aa": {
"metrics": {
"decode.latency.mean": 1.6980519409179688}
}
}
}
```
"""
combined = {}
for summary in summaries:
model = summary["model"]
config = summary["config"]
commit = summary["commit"]
if model not in combined:
combined[model] = {}
if config not in combined[model]:
combined[model][config] = {}
if commit not in combined[model][config]:
combined[model][config][commit] = {"metrics": summary["metrics"]}
with open(os.path.join(exp_run_dir, "summary.json"), "w") as fp:
json.dump(combined, fp, indent=4)
print(json.dumps(combined, indent=4))
return combined
if __name__ == "__main__":
def list_str(values):
return values.split(",")
parser = argparse.ArgumentParser()
parser.add_argument("--config-dir", type=str, required=True, help="The path to the config directory.")
parser.add_argument("--config-name", type=str, required=True, help="The config name.")
# arguments specific to this wrapper for our own customization
parser.add_argument("--ensure_empty", type=bool, default=True, help="If to create a temporary directory.")
parser.add_argument(
"--commit",
type=list_str,
default="",
help="Comma-separated list of branch names and/or commit sha values on which the benchmark will run. If `diff` is specified, it will run on both the current head and the `main` branch.",
)
parser.add_argument("--metrics", type=str, help="The metrics to be included in the summary.")
parser.add_argument("--repo_id", type=str, default=None, help="The repository to which the file will be uploaded.")
parser.add_argument("--path_in_repo", type=str, default=None, help="Relative filepath in the repo.")
parser.add_argument("--token", type=str, default=None, help="A valid user access token (string).")
args, optimum_benchmark_args = parser.parse_known_args()
repo = Repo(PATH_TO_REPO)
metrics = [
"prefill.latency.mean",
"prefill.throughput.value",
"decode.latency.mean",
"decode.throughput.value",
"per_token.latency.mean",
"per_token.throughput.value",
]
if args.metrics is not None:
metrics = args.metrics.split(",")
# Get `backend.model` in a hacky way: We want to control the experiment flow manually.
models = [""]
for idx, arg in enumerate(optimum_benchmark_args):
if arg.startswith("backend.model="):
models = arg[len("backend.model=") :]
models = models.split(",")
break
optimum_benchmark_args = [arg for arg in optimum_benchmark_args if not arg.startswith("backend.model=")]
# Get the commit(s)
current_head = str(repo.head.commit) if repo.head.is_detached else str(repo.head.ref)
commits = [x for x in args.commit if x != ""]
if len(commits) == 0:
commits = [current_head]
elif len(commits) == 1 and commits[0] == "diff":
# compare to `main`
commits = ["main", current_head]
# Get the specified run directory
run_dir_arg_idx, run_dir = -1, None
sweep_dir_arg_idx, sweep_dir = -1, None
for idx, arg in enumerate(optimum_benchmark_args):
if arg.startswith("hydra.run.dir="):
run_dir = arg[len("hydra.run.dir=") :]
run_dir_arg_idx = idx
elif arg.startswith("hydra.sweep.dir="):
sweep_dir = arg[len("hydra.sweep.dir=") :]
sweep_dir_arg_idx = idx
exp_run_dir, arg_dix, arg_name = (
(sweep_dir, sweep_dir_arg_idx, "hydra.sweep.dir")
if "--multirun" in optimum_benchmark_args
else (run_dir, run_dir_arg_idx, "hydra.run.dir")
)
# TODO: not hardcoded
if exp_run_dir is None and args.ensure_empty:
exp_run_dir = "_benchmark"
if args.ensure_empty:
os.makedirs(exp_run_dir, exist_ok=True)
exp_run_dir = tempfile.mkdtemp(dir=exp_run_dir)
run_summaries = []
for commit in commits:
with checkout_commit(repo, commit):
commit = str(repo.head.commit)
commit_run_dir = exp_run_dir
if exp_run_dir is not None:
commit_run_dir = os.path.join(exp_run_dir, rf"commit\={commit}")
print(f"Run benchmark on commit: {commit}")
for model in models:
model_arg = [f"backend.model={model}"] if model != "" else []
dir_args = []
if commit_run_dir is not None:
if arg_dix > -1:
optimum_benchmark_args[arg_dix] = f"{arg_name}={commit_run_dir}"
else:
dir_args = [
f"hydra.sweep.dir={commit_run_dir}",
f"hydra.run.dir={commit_run_dir}/" + "${hydra.job.override_dirname}",
]
main(args.config_dir, args.config_name, model_arg + dir_args + optimum_benchmark_args)
if commit_run_dir is not None:
# Need to remove the `\` character
summaries = summarize(commit_run_dir.replace("\\", ""), metrics)
run_summaries.extend(summaries)
# aggregate the information across the commits
if exp_run_dir is not None:
with open(os.path.join(exp_run_dir, "summaries.json"), "w") as fp:
json.dump(run_summaries, fp, indent=4)
combined_summary = combine_summaries(run_summaries)
if args.repo_id is not None and args.path_in_repo is not None:
# Upload to Hub
api = HfApi()
api.upload_folder(
folder_path=exp_run_dir,
path_in_repo=args.path_in_repo,
repo_id=args.repo_id,
repo_type="dataset",
token=args.token,
)

View File

@ -1,144 +0,0 @@
import argparse
import importlib.util
import logging
import os
from typing import Dict
import psycopg2
import sys
from psycopg2.extras import Json
from psycopg2.extensions import register_adapter
register_adapter(dict, Json)
class ImportModuleException(Exception):
pass
class MetricsRecorder:
def __init__(self, connection, logger: logging.Logger, branch: str, commit_id: str, commit_msg: str):
self.conn = connection
self.conn.autocommit = True
self.logger = logger
self.branch = branch
self.commit_id = commit_id
self.commit_msg = commit_msg
def initialise_benchmark(self, metadata: Dict[str, str]) -> int:
"""
Creates a new benchmark, returns the benchmark id
"""
# gpu_name: str, model_id: str
with self.conn.cursor() as cur:
cur.execute(
"INSERT INTO benchmarks (branch, commit_id, commit_message, metadata) VALUES (%s, %s, %s, %s) RETURNING benchmark_id",
(self.branch, self.commit_id, self.commit_msg, metadata),
)
benchmark_id = cur.fetchone()[0]
logger.debug(f"initialised benchmark #{benchmark_id}")
return benchmark_id
def collect_device_measurements(self, benchmark_id: int, cpu_util, mem_megabytes, gpu_util, gpu_mem_megabytes):
"""
Collect device metrics, such as CPU & GPU usage. These are "static", as in you cannot pass arbitrary arguments to the function.
"""
with self.conn.cursor() as cur:
cur.execute(
"INSERT INTO device_measurements (benchmark_id, cpu_util, mem_megabytes, gpu_util, gpu_mem_megabytes) VALUES (%s, %s, %s, %s, %s)",
(benchmark_id, cpu_util, mem_megabytes, gpu_util, gpu_mem_megabytes),
)
self.logger.debug(
f"inserted device measurements for benchmark #{benchmark_id} [CPU util: {cpu_util}, mem MBs: {mem_megabytes}, GPU util: {gpu_util}, GPU mem MBs: {gpu_mem_megabytes}]"
)
def collect_model_measurements(self, benchmark_id: int, measurements: Dict[str, float]):
with self.conn.cursor() as cur:
cur.execute(
"""
INSERT INTO model_measurements (
benchmark_id,
measurements
) VALUES (%s, %s)
""",
(
benchmark_id,
measurements,
),
)
self.logger.debug(f"inserted model measurements for benchmark #{benchmark_id}: {measurements}")
def close(self):
self.conn.close()
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.INFO)
formatter = logging.Formatter("[%(levelname)s - %(asctime)s] %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)
def parse_arguments():
"""
Parse command line arguments for the benchmarking CLI.
"""
parser = argparse.ArgumentParser(description="CLI for benchmarking the huggingface/transformers.")
parser.add_argument(
"branch",
type=str,
help="The branch name on which the benchmarking is performed.",
)
parser.add_argument(
"commit_id",
type=str,
help="The commit hash on which the benchmarking is performed.",
)
parser.add_argument(
"commit_msg",
type=str,
help="The commit message associated with the commit, truncated to 70 characters.",
)
args = parser.parse_args()
return args.branch, args.commit_id, args.commit_msg
def import_from_path(module_name, file_path):
try:
spec = importlib.util.spec_from_file_location(module_name, file_path)
module = importlib.util.module_from_spec(spec)
sys.modules[module_name] = module
spec.loader.exec_module(module)
return module
except Exception as e:
raise ImportModuleException(f"failed to load python module: {e}")
if __name__ == "__main__":
benchmarks_folder_path = os.path.dirname(os.path.realpath(__file__))
branch, commit_id, commit_msg = parse_arguments()
for entry in os.scandir(benchmarks_folder_path):
try:
if not entry.name.endswith(".py"):
continue
if entry.path == __file__:
continue
logger.debug(f"loading: {entry.name}")
module = import_from_path(entry.name.split(".")[0], entry.path)
logger.info(f"runnning benchmarks in: {entry.name}")
module.run_benchmark(logger, branch, commit_id, commit_msg)
except ImportModuleException as e:
logger.error(e)
except Exception as e:
logger.error(f"error running benchmarks for {entry.name}: {e}")

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@ -1,57 +0,0 @@
defaults:
- benchmark # inheriting benchmark schema
- scenario: inference
- launcher: process
- backend: pytorch
- _self_ # for hydra 1.1 compatibility
name: pytorch_generate
launcher:
start_method: spawn
device_isolation: true
device_isolation_action: warn
backend:
device: cuda
device_ids: 0
no_weights: true
model: meta-llama/Llama-2-7b-hf
cache_implementation: static
torch_compile: true
torch_dtype: float16
torch_compile_config:
backend: inductor
mode: reduce-overhead
fullgraph: true
scenario:
input_shapes:
batch_size: 1
sequence_length: 7
generate_kwargs:
max_new_tokens: 128
min_new_tokens: 128
do_sample: false
memory: true
latency: true
iterations: 2
duration: 0
# hydra/cli specific settings
hydra:
run:
# where to store run results
dir: runs/${name}
job:
# change working directory to the run directory
chdir: true
env_set:
# set environment variable OVERRIDE_BENCHMARKS to 1
# to not skip benchmarks that have been run before
OVERRIDE_BENCHMARKS: 1
LOG_LEVEL: WARN
sweep:
dir: multirun
subdir: ${hydra.job.override_dirname}

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@ -1,10 +0,0 @@
apiVersion: 1
providers:
- name: 'Transformers Benchmarks'
orgId: 1
type: file
updateIntervalSeconds: 10
allowUiUpdates: true
options:
path: /etc/grafana/dashboards

File diff suppressed because it is too large Load Diff

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@ -1,17 +0,0 @@
apiVersion: 1
datasources:
- name: grafana-postgresql-datasource
uid: be28nkzirtb0gd
type: postgres
url: $GRAFANA_POSTGRES_DATASOURCE_URL
user: $GRAFANA_POSTGRES_DATASOURCE_USER
secureJsonData:
password: $GRAFANA_POSTGRES_DATASOURCE_PWD
jsonData:
database: metrics
maxOpenConns: 100
maxIdleConns: 100
maxIdleConnsAuto: true
connMaxLifetime: 14400
postgresVersion: 1000
timescaledb: false

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@ -1,33 +0,0 @@
CREATE TABLE IF NOT EXISTS benchmarks (
benchmark_id SERIAL PRIMARY KEY,
branch VARCHAR(255),
commit_id VARCHAR(72),
commit_message VARCHAR(70),
metadata jsonb,
created_at timestamp without time zone NOT NULL DEFAULT (current_timestamp AT TIME ZONE 'UTC')
);
CREATE INDEX IF NOT EXISTS benchmarks_benchmark_id_idx ON benchmarks (benchmark_id);
CREATE INDEX IF NOT EXISTS benchmarks_branch_idx ON benchmarks (branch);
CREATE TABLE IF NOT EXISTS device_measurements (
measurement_id SERIAL PRIMARY KEY,
benchmark_id int REFERENCES benchmarks (benchmark_id),
cpu_util double precision,
mem_megabytes double precision,
gpu_util double precision,
gpu_mem_megabytes double precision,
time timestamp without time zone NOT NULL DEFAULT (current_timestamp AT TIME ZONE 'UTC')
);
CREATE INDEX IF NOT EXISTS device_measurements_branch_idx ON device_measurements (benchmark_id);
CREATE TABLE IF NOT EXISTS model_measurements (
measurement_id SERIAL PRIMARY KEY,
benchmark_id int REFERENCES benchmarks (benchmark_id),
measurements jsonb,
time timestamp without time zone NOT NULL DEFAULT (current_timestamp AT TIME ZONE 'UTC')
);
CREATE INDEX IF NOT EXISTS model_measurements_branch_idx ON model_measurements (benchmark_id);

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@ -1,342 +0,0 @@
from logging import Logger
import os
from threading import Event, Thread
from time import perf_counter, sleep
from typing import Optional
from benchmarks_entrypoint import MetricsRecorder
import gpustat
import psutil
import psycopg2
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig, StaticCache
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
os.environ["TOKENIZERS_PARALLELISM"] = "1"
torch.set_float32_matmul_precision("high")
def collect_metrics(benchmark_id, continue_metric_collection, metrics_recorder):
p = psutil.Process(os.getpid())
while not continue_metric_collection.is_set():
with p.oneshot():
cpu_util = p.cpu_percent()
mem_megabytes = p.memory_info().rss / (1024 * 1024)
gpu_stats = gpustat.GPUStatCollection.new_query()
gpu_util = gpu_stats[0]["utilization.gpu"]
gpu_mem_megabytes = gpu_stats[0]["memory.used"]
metrics_recorder.collect_device_measurements(
benchmark_id, cpu_util, mem_megabytes, gpu_util, gpu_mem_megabytes
)
sleep(0.01)
def run_benchmark(logger: Logger, branch: str, commit_id: str, commit_msg: str, num_tokens_to_generate=100):
continue_metric_collection = Event()
metrics_thread = None
model_id = "meta-llama/Llama-2-7b-hf"
metrics_recorder = MetricsRecorder(psycopg2.connect("dbname=metrics"), logger, branch, commit_id, commit_msg)
try:
gpu_stats = gpustat.GPUStatCollection.new_query()
gpu_name = gpu_stats[0]["name"]
benchmark_id = metrics_recorder.initialise_benchmark({"gpu_name": gpu_name, "model_id": model_id})
logger.info(f"running benchmark #{benchmark_id} on {gpu_name} for {model_id}")
metrics_thread = Thread(
target=collect_metrics,
args=[benchmark_id, continue_metric_collection, metrics_recorder],
)
metrics_thread.start()
logger.info("started background thread to fetch device metrics")
os.environ["TOKENIZERS_PARALLELISM"] = "false" # silence warnings when compiling
device = "cuda"
logger.info("downloading weights")
# This is to avoid counting download in model load time measurement
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16)
gen_config = GenerationConfig(do_sample=False, top_p=1, temperature=1)
logger.info("loading model")
start = perf_counter()
model = AutoModelForCausalLM.from_pretrained(
model_id, torch_dtype=torch.float16, generation_config=gen_config
).eval()
model.to(device)
torch.cuda.synchronize()
end = perf_counter()
model_load_time = end - start
logger.info(f"loaded model in: {model_load_time}s")
tokenizer = AutoTokenizer.from_pretrained(model_id)
prompt = "Why dogs are so cute?"
inputs = tokenizer(prompt, return_tensors="pt").to(device)
# Specify the max length (including both the prompt and the response)
# When calling `generate` with `cache_implementation="static" later, this is also used to create a `StaticCache` object
# with sequence length = `max_length`. The longer the more you will re-use it
seq_length = inputs["input_ids"].shape[1]
model.generation_config.max_length = seq_length + num_tokens_to_generate
batch_size = inputs["input_ids"].shape[0]
# Copied from the gpt-fast repo
def multinomial_sample_one_no_sync(probs_sort): # Does multinomial sampling without a cuda synchronization
q = torch.empty_like(probs_sort).exponential_(1)
return torch.argmax(probs_sort / q, dim=-1, keepdim=True).to(dtype=torch.int)
def logits_to_probs(logits, temperature: float = 1.0, top_k: Optional[int] = None):
logits = logits / max(temperature, 1e-5)
if top_k is not None:
v, _ = torch.topk(logits, min(top_k, logits.size(-1)))
pivot = v.select(-1, -1).unsqueeze(-1)
logits = torch.where(logits < pivot, -float("Inf"), logits)
probs = torch.nn.functional.softmax(logits, dim=-1)
return probs
def sample(logits, temperature: float = 1.0, top_k: Optional[int] = None):
probs = logits_to_probs(logits[:, -1], temperature, top_k)
idx_next = multinomial_sample_one_no_sync(probs)
return idx_next, probs
def decode_one_token(model, cur_token, cache_position, past_key_values):
logits = model(
cur_token,
cache_position=cache_position,
past_key_values=past_key_values,
return_dict=False,
use_cache=True,
)[0]
new_token = sample(logits, temperature=0.6, top_k=5)[0]
return new_token
#########
# Eager #
#########
with torch.no_grad():
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + num_tokens_to_generate,
)
cache_position = torch.arange(seq_length, device=device)
start = perf_counter()
model(
**inputs,
cache_position=cache_position,
past_key_values=past_key_values,
return_dict=False,
use_cache=True,
)
end = perf_counter()
first_eager_fwd_pass_time = end - start
logger.info(f"completed first eager fwd pass in: {first_eager_fwd_pass_time}s")
start = perf_counter()
output = model.generate(**inputs, do_sample=False)
end = perf_counter()
first_eager_generate_time = end - start
logger.info(f"completed first eager generation in: {first_eager_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + num_tokens_to_generate,
)
cache_position = torch.arange(seq_length, device=device)
start = perf_counter()
model(
**inputs,
cache_position=cache_position,
past_key_values=past_key_values,
return_dict=False,
use_cache=True,
)
end = perf_counter()
second_eager_fwd_pass_time = end - start
logger.info(f"completed second eager fwd pass in: {second_eager_fwd_pass_time}s")
start = perf_counter()
model.generate(**inputs, do_sample=False)
end = perf_counter()
second_eager_generate_time = end - start
logger.info(f"completed second eager generation in: {second_eager_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
torch.compiler.reset()
################
# Forward pass #
################
# `torch.compile(model, ...)` is not recommended as you compile callbacks
# and full generate. We recommend compiling only the forward for now.
# "reduce-overhead" will use cudagraphs.
generated_ids = torch.zeros(
(batch_size, num_tokens_to_generate + seq_length), dtype=torch.int, device=device
)
generated_ids[:, :seq_length] = inputs["input_ids"]
decode_one_token = torch.compile(decode_one_token, mode="reduce-overhead", fullgraph=True)
# model.forward = torch.compile(model.forward, mode="reduce-overhead", fullgraph=True)
# TODO use decode_one_token(model, input_id.clone(), cache_position) for verification
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + num_tokens_to_generate + 10,
)
cache_position = torch.arange(seq_length, device=device)
all_generated_tokens = []
### First compile, prefill
start = perf_counter()
next_token = decode_one_token(
model, inputs["input_ids"], cache_position=cache_position, past_key_values=past_key_values
)
torch.cuda.synchronize()
end = perf_counter()
time_to_first_token = end - start
logger.info(f"completed first compile generation in: {time_to_first_token}s")
cache_position += 1
all_generated_tokens += next_token.clone().detach().cpu().tolist()
cache_position = torch.tensor([seq_length], device=device)
### First compile, decoding
start = perf_counter()
next_token = decode_one_token(
model, next_token.clone(), cache_position=cache_position, past_key_values=past_key_values
)
torch.cuda.synchronize()
end = perf_counter()
time_to_second_token = end - start
logger.info(f"completed second compile generation in: {time_to_first_token}s")
cache_position += 1
all_generated_tokens += next_token.clone().detach().cpu().tolist()
### Second compile, decoding
start = perf_counter()
next_token = decode_one_token(
model, next_token.clone(), cache_position=cache_position, past_key_values=past_key_values
)
torch.cuda.synchronize()
end = perf_counter()
time_to_third_token = end - start
logger.info(f"completed third compile forward in: {time_to_first_token}s")
cache_position += 1
all_generated_tokens += next_token.clone().detach().cpu().tolist()
### Using cuda graphs decoding
start = perf_counter()
for _ in range(1, num_tokens_to_generate):
all_generated_tokens += next_token.clone().detach().cpu().tolist()
next_token = decode_one_token(
model, next_token.clone(), cache_position=cache_position, past_key_values=past_key_values
)
cache_position += 1
torch.cuda.synchronize()
end = perf_counter()
mean_time_to_next_token = (end - start) / num_tokens_to_generate
logger.info(f"completed next compile generation in: {mean_time_to_next_token}s")
logger.info(f"generated: {tokenizer.batch_decode(all_generated_tokens)}")
####################
# Generate compile #
####################
torch.compiler.reset()
# we will not compile full generate as it' s to intensive, tho we measure full forward!
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + 128,
)
# 1st call
start = perf_counter()
output = model.generate(**inputs, past_key_values=past_key_values)
torch.cuda.synchronize()
end = perf_counter()
first_compile_generate_time = end - start
logger.info(f"completed first compile generation in: {first_compile_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + 128,
)
# 2nd call
start = perf_counter()
output = model.generate(**inputs, past_key_values=past_key_values)
torch.cuda.synchronize()
end = perf_counter()
second_compile_generate_time = end - start
logger.info(f"completed second compile generation in: {second_compile_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + 128,
)
# 3nd call
start = perf_counter()
output = model.generate(**inputs, past_key_values=past_key_values)
end = perf_counter()
third_compile_generate_time = end - start
logger.info(f"completed second compile generation in: {third_compile_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
past_key_values = StaticCache(
model.config,
batch_size=batch_size,
device=device,
dtype=torch.float16,
max_cache_len=seq_length + 128,
)
# 4th call
start = perf_counter()
output = model.generate(**inputs, past_key_values=past_key_values)
end = perf_counter()
fourth_compile_generate_time = end - start
logger.info(f"completed second compile generation in: {fourth_compile_generate_time}s")
logger.info(f"generated: {tokenizer.batch_decode(output.cpu().tolist())}")
metrics_recorder.collect_model_measurements(
benchmark_id,
{
"model_load_time": model_load_time,
"first_eager_forward_pass_time_secs": first_eager_fwd_pass_time,
"second_eager_forward_pass_time_secs": second_eager_fwd_pass_time,
"first_eager_generate_time_secs": first_eager_generate_time,
"second_eager_generate_time_secs": second_eager_generate_time,
"time_to_first_token_secs": time_to_first_token,
"time_to_second_token_secs": time_to_second_token,
"time_to_third_token_secs": time_to_third_token,
"time_to_next_token_mean_secs": mean_time_to_next_token,
"first_compile_generate_time_secs": first_compile_generate_time,
"second_compile_generate_time_secs": second_compile_generate_time,
"third_compile_generate_time_secs": third_compile_generate_time,
"fourth_compile_generate_time_secs": fourth_compile_generate_time,
},
)
except Exception as e:
logger.error(f"Caught exception: {e}")
continue_metric_collection.set()
if metrics_thread is not None:
metrics_thread.join()
metrics_recorder.close()

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@ -1,16 +0,0 @@
import argparse
import subprocess
def main(config_dir, config_name, args):
subprocess.run(["optimum-benchmark", "--config-dir", f"{config_dir}", "--config-name", f"{config_name}"] + ["hydra/job_logging=disabled", "hydra/hydra_logging=disabled"] + args)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--config-dir", type=str, required=True, help="The path to the config directory.")
parser.add_argument("--config-name", type=str, required=True, help="The config name.")
args, unknown = parser.parse_known_args()
main(args.config_dir, args.config_name, unknown)

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@ -1,5 +0,0 @@
gpustat==1.1.1
psutil==6.0.0
psycopg2==2.9.9
torch>=2.4.0
hf_transfer

View File

@ -53,7 +53,7 @@ NOT_DEVICE_TESTS = {
"test_torch_save_load",
"test_initialization",
"test_forward_signature",
"test_model_get_set_embeddings",
"test_model_common_attributes",
"test_model_main_input_name",
"test_correct_missing_keys",
"test_tie_model_weights",

View File

@ -1,9 +0,0 @@
# Dockers for `transformers`
In this folder you will find various docker files, and some subfolders.
- dockerfiles (ex: `consistency.dockerfile`) present under `~/docker` are used for our "fast" CIs. You should be able to use them for tasks that only need CPU. For example `torch-light` is a very light weights container (703MiB).
- subfloder contain dockerfiles used for our `slow` CIs, which *can* be used for GPU tasks, but they are **BIG** as they were not specifically designed for a single model / single task. Thus the `~/docker/transformers-pytorch-gpu` includes additional dependencies to allow us to run ALL model tests (say `librosa` or `tesseract`, which you do not need to run LLMs)
Note that in both case, you need to run `uv pip install -e .`, which should take around 5 seconds. We do it outside the dockerfile for the need of our CI: we checkout a new branch each time, and the `transformers` code is thus updated.
We are open to contribution, and invite the community to create dockerfiles with potential arguments that properly choose extras depending on the model's dependencies! :hugs:

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@ -1,16 +1,14 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
USER root
ARG REF=main
RUN apt-get update && apt-get install -y time git g++ pkg-config make git-lfs
ENV UV_PYTHON=/usr/local/bin/python
RUN apt-get update && apt-get install -y time git pkg-config make git-lfs
ENV VIRTUAL_ENV=/usr/local
RUN pip install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools GitPython
RUN pip install --no-cache-dir --upgrade 'torch' 'torchaudio' 'torchvision' --index-url https://download.pytorch.org/whl/cpu
# tensorflow pin matching setup.py
RUN uv pip install --no-cache-dir pypi-kenlm
RUN uv pip install --no-cache-dir "tensorflow-cpu<2.16" "tf-keras<2.16"
RUN uv pip install --no-cache-dir "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[flax,quality,testing,torch-speech,vision]"
RUN uv pip install --no-cache-dir --upgrade 'torch' --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache-dir tensorflow-cpu tf-keras
RUN uv pip install --no-cache-dir "transformers[flax,quality,vision,testing]"
RUN git lfs install
RUN pip uninstall -y transformers
RUN apt-get clean && rm -rf /var/lib/apt/lists/* && apt-get autoremove && apt-get autoclean
RUN apt-get clean && rm -rf /var/lib/apt/lists/* && apt-get autoremove && apt-get autoclean

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@ -1,8 +1,8 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git cmake wget xz-utils build-essential g++5 libprotobuf-dev protobuf-compiler
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN wget https://github.com/ku-nlp/jumanpp/releases/download/v2.0.0-rc3/jumanpp-2.0.0-rc3.tar.xz

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@ -1,9 +1,9 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git
RUN apt-get install -y g++ cmake
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv
RUN uv pip install --no-cache-dir -U pip setuptools albumentations seqeval
RUN pip install --upgrade --no-cache-dir "transformers[tf-cpu,sklearn,testing,sentencepiece,tf-speech,vision]"

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@ -1,8 +1,8 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-deps timm accelerate --extra-index-url https://download.pytorch.org/whl/cpu

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@ -1,9 +1,9 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git libgl1-mesa-glx libgl1 g++ tesseract-ocr
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache-dir --no-deps timm accelerate

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@ -1,10 +1,9 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git g++ cmake
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir "scipy<1.13" "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[flax,testing,sentencepiece,flax-speech,vision]"
RUN pip install --no-cache-dir "scipy<1.13" "transformers[flax,testing,sentencepiece,flax-speech,vision]"
RUN pip uninstall -y transformers
RUN apt-get clean && rm -rf /var/lib/apt/lists/* && apt-get autoremove && apt-get autoclean

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@ -1,10 +1,9 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git cmake g++
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[sklearn,tf-cpu,testing,sentencepiece,tf-speech,vision]"
RUN pip install --no-cache-dir "transformers[sklearn,tf-cpu,testing,sentencepiece,tf-speech,vision]"
RUN uv pip install --no-cache-dir "protobuf==3.20.3" tensorflow_probability
RUN apt-get clean && rm -rf /var/lib/apt/lists/*

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@ -1,11 +1,10 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git pkg-config openssh-client git
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-deps timm accelerate --extra-index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache-dir librosa "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[sklearn,sentencepiece,vision,testing]"
RUN uv pip install --no-cache-dir librosa "transformers[sklearn,sentencepiece,vision,testing]"
RUN pip uninstall -y transformers

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@ -1,9 +1,8 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y time git
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip install uv && uv venv
RUN uv pip install --no-cache-dir -U pip setuptools GitPython "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[ruff]" urllib3
RUN uv pip install --no-cache-dir -U pip setuptools GitPython transformers "ruff==0.1.5" urllib3
RUN apt-get install -y jq curl && apt-get clean && rm -rf /var/lib/apt/lists/*

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@ -1,12 +1,11 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ pkg-config openssh-client git
RUN apt-get install -y cmake
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --upgrade --no-cache-dir "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[tf-cpu,sklearn,testing,sentencepiece,tf-speech,vision]"
RUN pip install --upgrade --no-cache-dir "transformers[tf-cpu,sklearn,testing,sentencepiece,tf-speech,vision]"
RUN uv pip install --no-cache-dir "protobuf==3.20.3"
RUN pip uninstall -y transformers
RUN apt-get clean && rm -rf /var/lib/apt/lists/* && apt-get autoremove && apt-get autoclean

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@ -1,13 +1,12 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN uv pip install --no-deps accelerate
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu
RUN pip install --no-cache-dir "scipy<1.13" "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[flax,audio,sklearn,sentencepiece,vision,testing]"
RUN pip install --no-cache-dir "scipy<1.13" "transformers[flax, audio, sklearn,sentencepiece,vision,testing]"
# RUN pip install --no-cache-dir "scipy<1.13" "transformers[flax,testing,sentencepiece,flax-speech,vision]"

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@ -1,11 +1,10 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git git-lfs
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-deps timm accelerate --extra-index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache-dir librosa "git+https://github.com/huggingface/transformers.git@${REF}#egg=transformers[sklearn,sentencepiece,vision,testing,tiktoken]"
RUN uv pip install --no-deps timm accelerate --extra-index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache-dir librosa "transformers[sklearn,sentencepiece,vision,testing]"
RUN pip uninstall -y transformers

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@ -1,10 +1,10 @@
FROM python:3.9-slim
FROM python:3.10-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
RUN echo ${REF}
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git git-lfs
ENV UV_PYTHON=/usr/local/bin/python
ENV VIRTUAL_ENV=/usr/local
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools
RUN uv pip install --no-cache-dir --no-deps accelerate --extra-index-url https://download.pytorch.org/whl/cpu
RUN pip install --no-cache-dir 'torch' 'torchvision' 'torchaudio' --index-url https://download.pytorch.org/whl/cpu

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@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -9,7 +9,7 @@ SHELL ["sh", "-lc"]
# The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
# to be used as arguments for docker build (so far).
ARG PYTORCH='2.6.0'
ARG PYTORCH='2.3.0'
# (not always a valid torch version)
ARG INTEL_TORCH_EXT='2.3.0'
# Example: `cu102`, `cu113`, etc.
@ -26,7 +26,7 @@ RUN git clone https://github.com/huggingface/transformers && cd transformers &&
# 1. Put several commands in a single `RUN` to avoid image/layer exporting issue. Could be revised in the future.
# 2. Regarding `torch` part, We might need to specify proper versions for `torchvision` and `torchaudio`.
# Currently, let's not bother to specify their versions explicitly (so installed with their latest release versions).
RUN python3 -m pip install --no-cache-dir -U tensorflow==2.13 protobuf==3.20.3 "tensorflow_text<2.16" "tensorflow_probability<0.22" && python3 -m pip install --no-cache-dir -e ./transformers[dev,onnxruntime] && [ ${#PYTORCH} -gt 0 -a "$PYTORCH" != "pre" ] && VERSION='torch=='$PYTORCH'.*' || VERSION='torch'; echo "export VERSION='$VERSION'" >> ~/.profile && echo torch=$VERSION && [ "$PYTORCH" != "pre" ] && python3 -m pip install --no-cache-dir -U $VERSION torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/$CUDA || python3 -m pip install --no-cache-dir -U --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/$CUDA
RUN python3 -m pip install --no-cache-dir -U tensorflow==2.13 protobuf==3.20.3 tensorflow_text tensorflow_probability && python3 -m pip install --no-cache-dir -e ./transformers[dev,onnxruntime] && [ ${#PYTORCH} -gt 0 -a "$PYTORCH" != "pre" ] && VERSION='torch=='$PYTORCH'.*' || VERSION='torch'; echo "export VERSION='$VERSION'" >> ~/.profile && echo torch=$VERSION && [ "$PYTORCH" != "pre" ] && python3 -m pip install --no-cache-dir -U $VERSION torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/$CUDA || python3 -m pip install --no-cache-dir -U --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/$CUDA
RUN python3 -m pip uninstall -y flax jax
@ -43,18 +43,14 @@ RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/pef
RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/optimum@main#egg=optimum
# For video model testing
RUN python3 -m pip install --no-cache-dir av==9.2.0
RUN python3 -m pip install --no-cache-dir decord av==9.2.0
# For GGUF tests
RUN python3 -m pip install --no-cache-dir gguf
# Some slow tests require bnb
RUN python3 -m pip install --no-cache-dir bitsandbytes
# Some tests require quanto
RUN python3 -m pip install --no-cache-dir quanto
# `quanto` will install `ninja` which leads to many `CUDA error: an illegal memory access ...` in some model tests
# (`deformable_detr`, `rwkv`, `mra`)
RUN python3 -m pip uninstall -y ninja
# For `dinat` model
# The `XXX` part in `torchXXX` needs to match `PYTORCH` (to some extent)
RUN python3 -m pip install --no-cache-dir natten==0.15.1+torch220$CUDA -f https://shi-labs.com/natten/wheels
@ -65,9 +61,6 @@ RUN python3 -m pip install --no-cache-dir python-Levenshtein
# For `FastSpeech2ConformerTokenizer` tokenizer
RUN python3 -m pip install --no-cache-dir g2p-en
# For Some bitsandbytes tests
RUN python3 -m pip install --no-cache-dir einops
# When installing in editable mode, `transformers` is not recognized as a package.
# this line must be added in order for python to be aware of transformers.
RUN cd transformers && python3 setup.py develop

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@ -8,9 +8,7 @@ RUN python3 -m pip install --no-cache-dir --upgrade pip && python3 -m pip instal
RUN apt-get -y update && apt-get install -y libsndfile1-dev && apt install -y tesseract-ocr
# Torch needs to be installed before deepspeed
# RUN python3 -m pip install --no-cache-dir ./transformers[deepspeed]
RUN python3 -m pip uninstall -y deepspeed
RUN DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install deepspeed --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
RUN python3 -m pip install --no-cache-dir ./transformers[deepspeed]
RUN python3 -m pip install --no-cache-dir torchvision git+https://github.com/facebookresearch/detectron2.git pytesseract
RUN python3 -m pip install -U "itsdangerous<2.1.0"

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@ -48,8 +48,8 @@ RUN python3 -m pip uninstall -y torch-tensorrt apex
# Pre-build **nightly** release of DeepSpeed, so it would be ready for testing (otherwise, the 1st deepspeed test will timeout)
RUN python3 -m pip uninstall -y deepspeed
# This has to be run inside the GPU VMs running the tests. (So far, it fails here due to GPU checks during compilation.)
# Issue: https://github.com/deepspeedai/DeepSpeed/issues/2010
# RUN git clone https://github.com/deepspeedai/DeepSpeed && cd DeepSpeed && rm -rf build && \
# Issue: https://github.com/microsoft/DeepSpeed/issues/2010
# RUN git clone https://github.com/microsoft/DeepSpeed && cd DeepSpeed && rm -rf build && \
# DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 DS_BUILD_UTILS=1 python3 -m pip install . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
RUN python3 -m pip install -U "itsdangerous<2.1.0"

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@ -1,18 +1,17 @@
FROM rocm/dev-ubuntu-22.04:6.2.4
FROM rocm/dev-ubuntu-22.04:6.0.2
# rocm/pytorch has no version with 2.1.0
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
RUN apt update && \
apt install -y --no-install-recommends git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-dev python3-pip python3-dev ffmpeg git-lfs && \
apt install -y --no-install-recommends git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-dev python3-pip python3-dev ffmpeg && \
apt clean && \
rm -rf /var/lib/apt/lists/*
RUN git lfs install
RUN python3 -m pip install --no-cache-dir --upgrade pip numpy
RUN python3 -m pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
RUN python3 -m pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.0
RUN python3 -m pip install --no-cache-dir --upgrade importlib-metadata setuptools ninja git+https://github.com/facebookresearch/detectron2.git pytesseract "itsdangerous<2.1.0"
@ -31,5 +30,5 @@ RUN python3 -m pip uninstall -y tensorflow flax
# this line must be added in order for python to be aware of transformers.
RUN cd transformers && python3 setup.py develop
# Remove nvml and nvidia-ml-py as it is not compatible with ROCm. apex is not tested on NVIDIA either.
RUN python3 -m pip uninstall py3nvml pynvml nvidia-ml-py apex -y
# Remove nvml as it is not compatible with ROCm. apex is not tested on NVIDIA either.
RUN python3 -m pip uninstall py3nvml pynvml apex -y

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@ -1,11 +1,11 @@
FROM rocm/dev-ubuntu-22.04:6.2.4
FROM rocm/dev-ubuntu-22.04:5.6
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
ARG PYTORCH='2.5.1'
ARG TORCH_VISION='0.20.0'
ARG TORCH_AUDIO='2.5.0'
ARG ROCM='6.2'
ARG PYTORCH='2.1.1'
ARG TORCH_VISION='0.16.1'
ARG TORCH_AUDIO='2.1.1'
ARG ROCM='5.6'
RUN apt update && \
apt install -y --no-install-recommends \
@ -22,7 +22,7 @@ RUN apt update && \
apt clean && \
rm -rf /var/lib/apt/lists/*
RUN python3 -m pip install --no-cache-dir --upgrade pip ninja "pydantic>=2.0.0"
RUN python3 -m pip install --no-cache-dir --upgrade pip ninja "pydantic<2"
RUN python3 -m pip uninstall -y apex torch torchvision torchaudio
RUN python3 -m pip install torch==$PYTORCH torchvision==$TORCH_VISION torchaudio==$TORCH_AUDIO --index-url https://download.pytorch.org/whl/rocm$ROCM --no-cache-dir
@ -45,4 +45,4 @@ RUN cd transformers && python3 setup.py develop
RUN python3 -c "from deepspeed.launcher.runner import main"
# Remove nvml as it is not compatible with ROCm
RUN python3 -m pip uninstall py3nvml pynvml nvidia-ml-py apex -y
RUN python3 -m pip uninstall py3nvml pynvml -y

View File

@ -1,5 +1,5 @@
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-11.html#rel-23-11
FROM nvcr.io/nvidia/pytorch:23.11-py3
FROM nvcr.io/nvidia/pytorch:23.04-py3
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -42,12 +42,12 @@ RUN python3 -m pip uninstall -y deepspeed
# This has to be run (again) inside the GPU VMs running the tests.
# The installation works here, but some tests fail, if we don't pre-build deepspeed again in the VMs running the tests.
# TODO: Find out why test fail.
RUN DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install deepspeed --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
RUN DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install "deepspeed<=0.14.0" --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
# When installing in editable mode, `transformers` is not recognized as a package.
# this line must be added in order for python to be aware of transformers.
RUN cd transformers && python3 setup.py develop
# The base image ships with `pydantic==1.8.2` which is not working - i.e. the next command fails
RUN python3 -m pip install -U --no-cache-dir "pydantic>=2.0.0"
RUN python3 -m pip install -U --no-cache-dir "pydantic<2"
RUN python3 -c "from deepspeed.launcher.runner import main"

View File

@ -34,8 +34,8 @@ RUN python3 -m pip uninstall -y torch-tensorrt apex
# Pre-build **nightly** release of DeepSpeed, so it would be ready for testing (otherwise, the 1st deepspeed test will timeout)
RUN python3 -m pip uninstall -y deepspeed
# This has to be run inside the GPU VMs running the tests. (So far, it fails here due to GPU checks during compilation.)
# Issue: https://github.com/deepspeedai/DeepSpeed/issues/2010
# RUN git clone https://github.com/deepspeedai/DeepSpeed && cd DeepSpeed && rm -rf build && \
# Issue: https://github.com/microsoft/DeepSpeed/issues/2010
# RUN git clone https://github.com/microsoft/DeepSpeed && cd DeepSpeed && rm -rf build && \
# DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 DS_BUILD_UTILS=1 python3 -m pip install . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
## For `torchdynamo` tests

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@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -11,7 +11,7 @@ ARG REF=main
RUN git clone https://github.com/huggingface/transformers && cd transformers && git checkout $REF
# If set to nothing, will install the latest version
ARG PYTORCH='2.6.0'
ARG PYTORCH='2.3.0'
ARG TORCH_VISION=''
ARG TORCH_AUDIO=''
# Example: `cu102`, `cu113`, etc.

View File

@ -1,4 +1,4 @@
FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -9,12 +9,12 @@ SHELL ["sh", "-lc"]
# The following `ARG` are mainly used to specify the versions explicitly & directly in this docker file, and not meant
# to be used as arguments for docker build (so far).
ARG PYTORCH='2.5.1'
ARG PYTORCH='2.3.0'
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu118'
ARG CUDA='cu121'
RUN apt update
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python python3-pip ffmpeg
RUN python3 -m pip install --no-cache-dir --upgrade pip
ARG REF=main
@ -36,46 +36,28 @@ RUN python3 -m pip install --no-cache-dir einops
# Add bitsandbytes for mixed int8 testing
RUN python3 -m pip install --no-cache-dir bitsandbytes
# Add auto-gptq for gtpq quantization testing, installed from source for pytorch==2.5.1 compatibility
# TORCH_CUDA_ARCH_LIST="7.5+PTX" is added to make the package compile for Tesla T4 gpus available for the CI.
RUN pip install gekko
RUN git clone https://github.com/PanQiWei/AutoGPTQ.git && cd AutoGPTQ && TORCH_CUDA_ARCH_LIST="7.5+PTX" python3 setup.py install
# Add auto-gptq for gtpq quantization testing
RUN python3 -m pip install --no-cache-dir auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
# Add optimum for gptq quantization testing
RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/optimum@main#egg=optimum
# Add PEFT
RUN python3 -m pip install --no-cache-dir git+https://github.com/huggingface/peft@main#egg=peft
# Add aqlm for quantization testing
RUN python3 -m pip install --no-cache-dir aqlm[gpu]==1.0.2
# Add vptq for quantization testing
RUN python3 -m pip install --no-cache-dir vptq
# Add spqr for quantization testing
RUN python3 -m pip install --no-cache-dir spqr_quant[gpu]
# Add hqq for quantization testing
RUN python3 -m pip install --no-cache-dir hqq
# For GGUF tests
RUN python3 -m pip install --no-cache-dir gguf
# Add autoawq for quantization testing
# >=v0.2.7 needed for compatibility with transformers > 4.46
RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.7.post2/autoawq-0.2.7.post2-py3-none-any.whl
# >=v0.2.3 needed for compatibility with torch 2.2.1
RUN python3 -m pip install --no-cache-dir https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+cu118-cp38-cp38-linux_x86_64.whl
# Add quanto for quantization testing
RUN python3 -m pip install --no-cache-dir optimum-quanto
RUN python3 -m pip install --no-cache-dir quanto
# Add eetq for quantization testing
RUN python3 -m pip install git+https://github.com/NetEase-FuXi/EETQ.git
# Add flute-kernel and fast_hadamard_transform for quantization testing
RUN python3 -m pip install --no-cache-dir flute-kernel==0.3.0 -i https://flute-ai.github.io/whl/cu118
RUN python3 -m pip install --no-cache-dir fast_hadamard_transform==1.0.4.post1
# When installing in editable mode, `transformers` is not recognized as a package.
# this line must be added in order for python to be aware of transformers.
RUN cd transformers && python3 setup.py develop
RUN cd transformers && python3 setup.py develop

View File

@ -1,4 +1,4 @@
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
@ -18,7 +18,7 @@ RUN [ ${#TENSORFLOW} -gt 0 ] && VERSION='tensorflow=='$TENSORFLOW'.*' || VERSIO
RUN python3 -m pip uninstall -y torch flax
RUN python3 -m pip install -U "itsdangerous<2.1.0"
RUN python3 -m pip install --no-cache-dir -U "tensorflow_probability<0.22"
RUN python3 -m pip install --no-cache-dir -U tensorflow_probability
# When installing in editable mode, `transformers` is not recognized as a package.
# this line must be added in order for python to be aware of transformers.

View File

@ -276,14 +276,14 @@ building the return.
Here's an example of a single value return:
```python
```
Returns:
`List[int]`: A list of integers in the range [0, 1] --- 1 for a special token, 0 for a sequence token.
```
Here's an example of a tuple return, comprising several objects:
```python
```
Returns:
`tuple(torch.FloatTensor)` comprising various elements depending on the configuration ([`BertConfig`]) and inputs:
- ** loss** (*optional*, returned when `masked_lm_labels` is provided) `torch.FloatTensor` of shape `(1,)` --
@ -322,9 +322,10 @@ includes an example of how to transcribe speech to text in the
The syntax for Example docstrings can look as follows:
```python
```
Example:
```python
>>> from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
>>> from datasets import load_dataset
>>> import torch
@ -346,6 +347,7 @@ The syntax for Example docstrings can look as follows:
>>> transcription = processor.batch_decode(predicted_ids)
>>> transcription[0]
'MISTER QUILTER IS THE APOSTLE OF THE MIDDLE CLASSES AND WE ARE GLAD TO WELCOME HIS GOSPEL'
```
```
The docstring should give a minimal, clear example of how the respective model

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