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https://github.com/vllm-project/vllm.git
synced 2025-10-20 14:53:52 +08:00
compilation is fixed
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@ -5,7 +5,7 @@ requests >= 2.26.0
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tqdm
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blake3
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py-cpuinfo
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transformers >= 4.45.2 # Required for Llama 3.2 and Qwen2-VL.
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transformers >= 4.48.2 # Required for Bamba model and Transformers backend.
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tokenizers >= 0.19.1 # Required for Llama 3.
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protobuf # Required by LlamaTokenizer.
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fastapi >= 0.107.0, < 0.113.0; python_version < '3.9'
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@ -34,6 +34,6 @@ pyyaml
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six>=1.16.0; python_version > '3.11' # transitive dependency of pandas that needs to be the latest version for python 3.12
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setuptools>=74.1.1; python_version > '3.11' # Setuptools is used by triton, we need to ensure a modern version is installed for 3.12+ so that it does not try to import distutils, which was removed in 3.12
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einops # Required for Qwen2-VL.
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compressed-tensors == 0.8.1 # required for compressed-tensors
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compressed-tensors == 0.9.1 # required for compressed-tensors
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depyf==0.18.0 # required for profiling and debugging with compilation config
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cloudpickle # allows pickling lambda functions in model_executor/models/registry.py
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cloudpickle # allows pickling lambda functions in model_executor/models/registry.py
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@ -2,7 +2,7 @@
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# This file is autogenerated by pip-compile with Python 3.12
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# by the following command:
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#
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# python3.12 -m piptools compile requirements-test.in -o requirements-test.txt
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# python3.12 -m piptools compile requirements-test.in -o requirements-test.txt
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#
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absl-py==2.1.0
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# via rouge-score
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@ -106,9 +106,17 @@ dnspython==2.7.0
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docutils==0.16
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# via awscli
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einops==0.8.0
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# via -r requirements-test.in
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# via
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# -r requirements-test.in
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# encodec
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# vector-quantize-pytorch
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# vocos
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einx==0.3.0
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# via vector-quantize-pytorch
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email-validator==2.2.0
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# via pydantic
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encodec==0.1.1
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# via vocos
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evaluate==0.4.3
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# via lm-eval
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fastparquet==2024.11.0
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@ -125,6 +133,8 @@ filelock==3.16.1
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# triton
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fonttools==4.54.1
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# via matplotlib
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frozendict==2.4.6
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# via einx
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frozenlist==1.5.0
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# via
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# aiohttp
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@ -159,6 +169,7 @@ huggingface-hub==0.26.2
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# timm
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# tokenizers
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# transformers
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# vocos
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idna==3.10
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# via
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# anyio
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@ -261,6 +272,8 @@ numpy==1.26.4
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# cupy-cuda12x
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# datasets
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# decord
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# einx
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# encodec
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# evaluate
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# fastparquet
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# genai-perf
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@ -283,6 +296,7 @@ numpy==1.26.4
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# torchvision
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# transformers
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# tritonclient
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# vocos
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nvidia-cublas-cu12==12.4.5.8
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# via
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# nvidia-cudnn-cu12
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@ -455,6 +469,7 @@ pyyaml==6.0.2
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# responses
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# timm
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# transformers
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# vocos
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ray[adag]==2.40.0
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# via -r requirements-test.in
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redis==5.2.0
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@ -517,6 +532,7 @@ scipy==1.13.1
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# scikit-learn
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# sentence-transformers
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# statsmodels
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# vocos
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sentence-transformers==3.2.1
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# via -r requirements-test.in
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sentencepiece==0.2.0
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@ -540,7 +556,9 @@ sqlitedict==2.1.0
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statsmodels==0.14.4
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# via genai-perf
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sympy==1.13.1
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# via torch
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# via
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# einx
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# torch
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tabledata==1.3.3
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# via pytablewriter
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tabulate==0.9.0
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@ -568,12 +586,21 @@ torch==2.5.1
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# -r requirements-test.in
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# accelerate
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# bitsandbytes
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# encodec
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# lm-eval
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# peft
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# sentence-transformers
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# tensorizer
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# timm
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# torchaudio
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# torchvision
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# vector-quantize-pytorch
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# vocos
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torchaudio==2.5.1
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# via
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# -r requirements-test.in
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# encodec
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# vocos
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torchvision==0.20.1
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# via timm
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tqdm==4.66.6
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@ -584,13 +611,15 @@ tqdm==4.66.6
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# lm-eval
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# nltk
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# peft
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# pqdm
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# sentence-transformers
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# tqdm-multiprocess
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# transformers
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tqdm-multiprocess==0.0.11
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# via lm-eval
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transformers==4.47.0
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transformers==4.48.2
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# via
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# -r requirements-test.in
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# genai-perf
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# lm-eval
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# peft
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@ -615,6 +644,7 @@ typing-extensions==4.12.2
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# huggingface-hub
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# librosa
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# mistral-common
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# pqdm
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# pydantic
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# pydantic-core
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# torch
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@ -626,6 +656,10 @@ urllib3==2.2.3
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# requests
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# responses
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# tritonclient
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vector-quantize-pytorch==1.21.2
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# via -r requirements-test.in
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vocos==0.1.0
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# via -r requirements-test.in
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word2number==1.1
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# via lm-eval
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xxhash==3.5.0
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@ -638,4 +672,4 @@ zstandard==0.23.0
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# via lm-eval
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# The following packages are considered to be unsafe in a requirements file:
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# setuptools
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# setuptools
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@ -766,11 +766,6 @@ class TPUModelRunner(ModelRunnerBase):
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logger.info(" -- Compilation for decode done in %.2f [secs].",
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end - start)
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def _initialize_kv_cache(self):
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kv_cache_spec = self.get_kv_cache_spec()
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kv_cache_config = get_kv_cache_config(vllm_config, kv_cache_spec,
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availble_gpu_memory)
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def initialize_kv_cache(self, kv_cache_config: KVCacheConfig) -> None:
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"""
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Initialize KV cache based on `kv_cache_config`.
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