lock torch version to 2.0.1 when build for #1283 #1290
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When --tensor-parallel-size is greater than 1, multi-gpu parallel startup will get stuck. |
HermitSun
suggested changes
Oct 9, 2023
| @@ -3,7 +3,7 @@ requires = [ | |||
| "ninja", | |||
| "packaging", | |||
| "setuptools", | |||
| "torch >= 2.0.0", | |||
| "torch == 2.0.1", | |||
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Will torch >= 2.0.0, < 2.1.0 be better? It seems that torch == 2.0.0 works as well.
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Thanks for the suggestion. I think this is good since xformers requires torch 2.0.1
(RECOMMENDED, linux & win) Install latest stable with pip: Requires PyTorch 2.0.1
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This only works for cuda 11.x, but not for further cuda 12.x or higher : ( |
WoosukKwon
approved these changes
Oct 10, 2023
irfansharif
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Oct 13, 2023
Fixes #463. Pytorch 2.1.0 (https://github.com/pytorch/pytorch/releases/tag/v2.1.0) was just released just last week, and it's built using CUDA 12.1. The image we're using uses CUDA 11.8, as recommended by vLLM. Previously vLLM specified a dependency on torch>=2.0.0, and picked up this 2.1.0 version. That was pinned back to 2.0.1 in vllm-project/vllm#1290. When picking up that SHA however, we ran into what vllm-project/vllm#1239 fixes. So for now point to temporary fork with that fix.
irfansharif
added a commit
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Oct 14, 2023
Fixes #463. Pytorch 2.1.0 (https://github.com/pytorch/pytorch/releases/tag/v2.1.0) was just released just last week, and it's built using CUDA 12.1. The image we're using uses CUDA 11.8, as recommended by vLLM. Previously vLLM specified a dependency on torch>=2.0.0, and picked up this 2.1.0 version. That was pinned back to 2.0.1 in vllm-project/vllm#1290. When picking up that SHA however, we ran into what vllm-project/vllm#1239 fixes. So for now point to temporary fork with that fix.
gongy
pushed a commit
to modal-labs/modal-examples
that referenced
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Jan 5, 2024
Fixes #463. Pytorch 2.1.0 (https://github.com/pytorch/pytorch/releases/tag/v2.1.0) was just released just last week, and it's built using CUDA 12.1. The image we're using uses CUDA 11.8, as recommended by vLLM. Previously vLLM specified a dependency on torch>=2.0.0, and picked up this 2.1.0 version. That was pinned back to 2.0.1 in vllm-project/vllm#1290. When picking up that SHA however, we ran into what vllm-project/vllm#1239 fixes. So for now point to temporary fork with that fix.
hongxiayang
pushed a commit
to hongxiayang/vllm
that referenced
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Feb 13, 2024
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torch 2.1.0 was compiled with CUDA 12.1, which not compatible with vllm。issue #1283