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[Misc] Upgrade to pytorch 2.5 #9588

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merged 10 commits into from
Oct 27, 2024
+48 −25
Merged

[Misc] Upgrade to pytorch 2.5 #9588

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e970933
upgrade to pytorch 2.5 (still needs newer xformers
bnellnm Oct 17, 2024
5a54b48
update xformers
bnellnm Oct 22, 2024
1ea632b
use better method for specifying cuda libs
bnellnm Oct 25, 2024
c00efe3
try to make pytorch 2.5 use CUDA 12.1
bnellnm Oct 25, 2024
c4ebdba
remove extra index 12.1 for now
bnellnm Oct 25, 2024
39f9c34
update flash attn git hash
bnellnm Oct 25, 2024
f1f3caa
downgrade cpu pytorch version
bnellnm Oct 25, 2024
568510a
Merge branch 'main' into pt25
youkaichao Oct 27, 2024
0068133
fix sdpa cudnn
youkaichao Oct 27, 2024
5250a65
fix tests
youkaichao Oct 27, 2024
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2 changes: 1 addition & 1 deletion CMakeLists.txt
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Expand Up @@ -49,7 +49,7 @@ set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx11
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.4.0")
set(TORCH_SUPPORTED_VERSION_CUDA "2.5.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.5.0")

#
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6 changes: 1 addition & 5 deletions cmake/utils.cmake
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Expand Up @@ -424,11 +424,7 @@ function (define_gpu_extension_target GPU_MOD_NAME)
# Don't use `TORCH_LIBRARIES` for CUDA since it pulls in a bunch of
# dependencies that are not necessary and may not be installed.
if (GPU_LANGUAGE STREQUAL "CUDA")
if ("${CUDA_CUDA_LIB}" STREQUAL "")
set(CUDA_CUDA_LIB "${CUDA_CUDA_LIBRARY}")
endif()
target_link_libraries(${GPU_MOD_NAME} PRIVATE ${CUDA_CUDA_LIB}
${CUDA_LIBRARIES})
target_link_libraries(${GPU_MOD_NAME} PRIVATE CUDA::cudart CUDA::cuda_driver)
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Nice!

else()
target_link_libraries(${GPU_MOD_NAME} PRIVATE ${TORCH_LIBRARIES})
endif()
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2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -6,7 +6,7 @@ requires = [
"packaging",
"setuptools>=61",
"setuptools-scm>=8.0",
"torch == 2.4.0",
"torch == 2.5.0",
"wheel",
"jinja2",
]
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2 changes: 1 addition & 1 deletion requirements-build.txt
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Expand Up @@ -4,6 +4,6 @@ ninja
packaging
setuptools>=61
setuptools-scm>=8
torch==2.4.0
torch==2.5.0
wheel
jinja2
2 changes: 1 addition & 1 deletion requirements-cpu.txt
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Expand Up @@ -2,5 +2,5 @@
-r requirements-common.txt

# Dependencies for x86_64 CPUs
torch == 2.4.0+cpu; platform_machine != "ppc64le"
torch == 2.5.0+cpu; platform_machine != "ppc64le"
torchvision; platform_machine != "ppc64le" # required for the image processor of phi3v, this must be updated alongside torch
6 changes: 3 additions & 3 deletions requirements-cuda.txt
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Expand Up @@ -4,7 +4,7 @@
# Dependencies for NVIDIA GPUs
ray >= 2.9
nvidia-ml-py # for pynvml package
torch == 2.4.0
torch == 2.5.0
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@robertgshaw2-redhat robertgshaw2-redhat Oct 22, 2024 •
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Only concern here is now torch==2.5.0 uses the 12.4 cuda bindings by default. We might want to update the installation docs (including on the readme) to alert users that they may want to pass --extra-index-url https://download.pytorch.org/whl/cu121 during installation depending on the machine they are using

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@robertgshaw2-neuralmagic Does this mean that there would need to be multiple vllm packages (one for 12.1 and one for 12.4)? Or should I try to install pytorch 2.5 built with 12.1 (if such a thing exists)?

# These must be updated alongside torch
torchvision == 0.19 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
xformers == 0.0.27.post2; platform_system == 'Linux' and platform_machine == 'x86_64' # Requires PyTorch 2.4.0
torchvision == 0.20 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
xformers == 0.0.28.post2; platform_system == 'Linux' and platform_machine == 'x86_64' # Requires PyTorch 2.5.0
2 changes: 1 addition & 1 deletion requirements-openvino.txt
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@@ -1,7 +1,7 @@
# Common dependencies
-r requirements-common.txt

torch == 2.4.0 # should be aligned with "common" vLLM torch version
torch == 2.5.0 # should be aligned with "common" vLLM torch version
openvino >= 2024.4.0 # since 2024.4.0 both CPU and GPU support Paged Attention

optimum @ git+https://github.com/huggingface/optimum.git@main # latest optimum is used to support latest transformers version
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