mirror of
https://github.com/pytorch/pytorch.git
synced 2025-11-05 08:24:57 +08:00
cce156ac94
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58363 Previous implemntation relied on us directly writing the yaml instead of just having a conditional block, this allows us better readability for pull request triggers Signed-off-by: Eli Uriegas <seemethere101@gmail.com> Test Plan: Imported from OSS Reviewed By: walterddr Differential Revision: D28465271 Pulled By: seemethere fbshipit-source-id: fd556bb6bac4954fcddb4a2b0383e996f292a794
162 lines
6.9 KiB
Python
Executable File
162 lines
6.9 KiB
Python
Executable File
#!/usr/bin/env python3
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from pathlib import Path
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import jinja2
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DOCKER_REGISTRY = "308535385114.dkr.ecr.us-east-1.amazonaws.com"
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GITHUB_DIR = Path(__file__).parent.parent
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CPU_TEST_RUNNER = "linux.2xlarge"
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CUDA_TEST_RUNNER = "linux.8xlarge.nvidia.gpu"
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class PyTorchLinuxWorkflow:
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def __init__(
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self,
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build_environment: str,
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docker_image_base: str,
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on_pull_request: bool = False,
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enable_doc_jobs: bool = False,
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):
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self.build_environment = build_environment
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self.docker_image_base = docker_image_base
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self.test_runner_type = CPU_TEST_RUNNER
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self.on_pull_request = on_pull_request
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self.enable_doc_jobs = enable_doc_jobs
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if "cuda" in build_environment:
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self.test_runner_type = CUDA_TEST_RUNNER
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def generate_workflow_file(
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self, workflow_template: jinja2.Template, jinja_env: jinja2.Environment
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) -> Path:
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output_file_path = GITHUB_DIR.joinpath(
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f"workflows/{self.build_environment}.yml"
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)
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with open(output_file_path, "w") as output_file:
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output_file.writelines(["# @generated DO NOT EDIT MANUALLY\n"])
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output_file.write(
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workflow_template.render(
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build_environment=self.build_environment,
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docker_image_base=self.docker_image_base,
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test_runner_type=self.test_runner_type,
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enable_doc_jobs=self.enable_doc_jobs,
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on_pull_request=self.on_pull_request,
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)
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)
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output_file.write('\n')
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return output_file_path
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WORKFLOWS = [
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PyTorchLinuxWorkflow(
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build_environment="pytorch-linux-xenial-py3.6-gcc5.4",
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docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4",
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on_pull_request=True,
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enable_doc_jobs=True,
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),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-paralleltbb-linux-xenial-py3.6-gcc5.4",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-parallelnative-linux-xenial-py3.6-gcc5.4",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-pure_torch-linux-xenial-py3.6-gcc5.4",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc5.4",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-gcc7",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3.6-gcc7",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-asan",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-asan",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang7-onnx",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang7-onnx",
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# ),
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PyTorchLinuxWorkflow(
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build_environment="pytorch-linux-xenial-cuda10.2-cudnn7-py3.6-gcc7",
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docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7",
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),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-cuda11.1-cudnn8-py3.6-gcc7",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-libtorch-linux-xenial-cuda11.1-cudnn8-py3.6-gcc7",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-bionic-py3.6-clang9-noarch",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-xla-linux-bionic-py3.6-clang9",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-vulkan-linux-bionic-py3.6-clang9",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.6-clang9",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-bionic-py3.8-gcc9-coverage",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-py3.8-gcc9",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-bionic-rocm3.9-py3.6",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-bionic-rocm3.9-py3.6",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-x86_32",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-x86_64",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-arm-v7a",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-android-ndk-r19c-arm-v8a",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-mobile",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-asan",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-custom-dynamic",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-custom-static",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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# PyTorchLinuxWorkflow(
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# build_environment="pytorch-linux-xenial-py3.6-clang5-mobile-code-analysis",
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# docker_image_base=f"{DOCKER_REGISTRY}/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
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# ),
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]
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if __name__ == "__main__":
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jinja_env = jinja2.Environment(
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variable_start_string="!{{",
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loader=jinja2.FileSystemLoader(str(GITHUB_DIR.joinpath("templates"))),
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)
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workflow_template = jinja_env.get_template("linux_ci_workflow.yml.in")
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for workflow in WORKFLOWS:
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print(
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workflow.generate_workflow_file(
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workflow_template=workflow_template,
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jinja_env=jinja_env
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)
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)
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