Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Bugfix] Fix the fp8 kv_cache check error that occurs when failing to obtain the CUDA version. #4173

Merged
merged 1 commit into from
May 1, 2024

Conversation

AnyISalIn
Copy link
Contributor

Fix the fp8 kv_cache check error that occurs when failing to obtain the CUDA version.

PR Checklist (Click to Expand)

Thank you for your contribution to vLLM! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM maintain the code quality and improve the efficiency of the review process.

PR Title and Classification

Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:

  • [Bugfix] for bug fixes.
  • [CI/Build] for build or continuous integration improvements.
  • [Doc] for documentation fixes and improvements.
  • [Model] for adding a new model or improving an existing model. Model name should appear in the title.
  • [Frontend] For changes on the vLLM frontend (e.g., OpenAI API server, LLM class, etc.)
  • [Kernel] for changes affecting CUDA kernels or other compute kernels.
  • [Core] for changes in the core vLLM logic (e.g., LLMEngine, AsyncLLMEngine, Scheduler, etc.)
  • [Hardware][Vendor] for hardware-specific changes. Vendor name should appear in the prefix (e.g., [Hardware][AMD]).
  • [Misc] for PRs that do not fit the above categories. Please use this sparingly.

Note: If the PR spans more than one category, please include all relevant prefixes.

Code Quality

The PR need to meet the following code quality standards:

  • We adhere to Google Python style guide and Google C++ style guide.
  • Pass all linter checks. Please use format.sh to format your code.
  • The code need to be well-documented to ensure future contributors can easily understand the code.
  • Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.
  • Please add documentation to docs/source/ if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.

Notes for Large Changes

Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with rfc-required and might not go through the PR.

What to Expect for the Reviews

The goal of the vLLM team is to be a transparent reviewing machine. We would like to make the review process transparent and efficient and make sure no contributor feel confused or frustrated. However, the vLLM team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process:

  • After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.
  • After the PR is assigned, the reviewer will provide status update every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM team.
  • After the review, the reviewer will put an action-required label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.
  • Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.

Thank You

Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM. Your contributions make vLLM a great tool for everyone!

…he CUDA version.

Signed-off-by: AnyISalIn <anyisalin@gmail.com>
Comment on lines 327 to +329
nvcc_cuda_version = get_nvcc_cuda_version()
if nvcc_cuda_version < Version("11.8"):
if nvcc_cuda_version is not None \
and nvcc_cuda_version < Version("11.8"):
Copy link
Contributor

@chiragjn chiragjn May 1, 2024

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks for this!

Just curious, why is this check on nvcc and not on libcudart version in the first place?
E.g. torch.version.cuda or some other way?


I was wondering if I have cuda runtime 11.8 without nvcc installed this condition evaluates to False and no error would be raised.

For the docker image it would not matter because it has cuda 12.x

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

It is better to check cuda version on libcudart, as vllm-openai images only has cuda runtime.

Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

+1 I fixed a bug for removing nvcc dependency: #4666

@simon-mo simon-mo merged commit a88bb9b into vllm-project:main May 1, 2024
44 of 46 checks passed
robertgshaw2-neuralmagic pushed a commit to neuralmagic/nm-vllm that referenced this pull request May 6, 2024
… obtain the CUDA version. (vllm-project#4173)

Signed-off-by: AnyISalIn <anyisalin@gmail.com>
z103cb pushed a commit to z103cb/opendatahub_vllm that referenced this pull request May 7, 2024
… obtain the CUDA version. (vllm-project#4173)

Signed-off-by: AnyISalIn <anyisalin@gmail.com>
dtrifiro pushed a commit to opendatahub-io/vllm that referenced this pull request May 7, 2024
… obtain the CUDA version. (vllm-project#4173)

Signed-off-by: AnyISalIn <anyisalin@gmail.com>
mawong-amd pushed a commit to ROCm/vllm that referenced this pull request Jun 3, 2024
… obtain the CUDA version. (vllm-project#4173)

Signed-off-by: AnyISalIn <anyisalin@gmail.com>
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

6 participants