Upstream sync 2024 05 05 #224

…t#4376) Co-authored-by: WoosukKwon <[email protected]>

Co-authored-by: Danny Guinther <[email protected]>

…fill (vllm-project#4309)

…oject#4373)

Co-authored-by: Simon Mo <[email protected]>

…t#4348)

…les (vllm-project#4343) Co-authored-by: Woosuk Kwon <[email protected]>

…4355)

…m-project#4406)

Co-authored-by: Antoni Baum <[email protected]>

…errupted (vllm-project#4363)

) Co-authored-by: DefTruth <[email protected]>

Signed-off-by: Prashant Gupta <[email protected]> Co-authored-by: Travis Johnson <[email protected]>

…ect#4402)

…ct#4418)

Co-authored-by: Robert Shaw <[email protected]> Co-authored-by: Robert Shaw <[email protected]>

…project#3922) Co-authored-by: alexm <[email protected]> Co-authored-by: mgoin <[email protected]>

…project#4444)

…ect#4165) Co-authored-by: Lei Wen <[email protected]>

Signed-off-by: Prashant Gupta <[email protected]> Co-authored-by: Roger Wang <[email protected]>

Co-authored-by: Philipp Moritz <[email protected]> Co-authored-by: Woosuk Kwon <[email protected]> Co-authored-by: mgoin <[email protected]> Co-authored-by: Tyler Michael Smith <[email protected]> Co-authored-by: Cody Yu <[email protected]>

…int (vllm-project#3467) Co-authored-by: Lily Liu <[email protected]> Co-authored-by: Cyrus Leung <[email protected]>

…ersion (vllm-project#4467)

…vllm-project#4494) Co-authored-by: Simon Mo <[email protected]>

… obtain the CUDA version. (vllm-project#4173) Signed-off-by: AnyISalIn <[email protected]>

…ect#4503)

…-project#4534) Signed-off-by: Travis Johnson <[email protected]>

…#4237) Co-authored-by: Lei Wen <[email protected]>

…ect#4142) Co-authored-by: Lei Wen <[email protected]> Co-authored-by: Sage Moore <[email protected]>

…vllm-project#4357)

This PR updates the tuning script for the fused_moe kernel to support FP8 and also adds configurations for TP4. Note that for the configuration I removed num_warps and num_stages for small batch sizes since that improved performance and brought the benchmarks on par with the numbers before in that regime to make sure this is a strict improvement over the status quo. All the numbers below are for mistralai/Mixtral-8x7B-Instruct-v0.1, 1000 input and 50 output tokens. Before this PR (with static activation scaling): qps = 1: 9.8 ms ITL, 0.49s e2e latency qps = 2: 9.7 ms ITL, 0.49s e2e latency qps = 4: 10.1 ms ITL, 0.52s e2e latency qps = 6: 11.9 ms ITL, 0.59s e2e latency qps = 8: 14.0 ms ITL, 0.70s e2e latency qps = 10: 15.7 ms ITL, 0.79s e2e latency After this PR (with static activation scaling): qps = 1: 9.8 ms ITL, 0.49s e2e latency qps = 2: 9.7 ms ITL, 0.49s e2e latency qps = 4: 10.2 ms ITL, 0.53s e2e latency qps = 6: 11.9 ms ITL, 0.59s e2e latency qps = 8: 11.9 ms ITL, 0.59s e2e latency qps = 10: 12.1 ms ITL, 0.61s e2e latency

Remove the device="cuda" declarations in mixtral as promised in vllm-project#4343

…to be provided (vllm-project#4273)

…n is not 1 and max_tokens is large & Add tests for preemption (vllm-project#4451)

…vllm-project#4524)

Co-authored-by: Cade Daniel <[email protected]>

Co-authored-by: Zhuohan Li <[email protected]>

…t#4552)

…lm-project#4559)

…ject#4405) Co-authored-by: SangBin Cho <[email protected]>

…4267) Co-authored-by: simon-mo <[email protected]>

…ject#4566)

vllm-project#4567)

…m-project#4518)

…default to None (vllm-project#4586)

Co-authored-by: LiuXiaoxuanPKU <[email protected]>

… Dynamic/Static Activations) (vllm-project#4527) Follow on to vllm-project#4332 to enable FP8 checkpoint loading for Mixtral and supersedes vllm-project#4436. This PR enables the following checkpoint loading features for Mixtral: Supports loading fp8 checkpoints for Mixtral, such as this "nm-testing/Mixtral-8x7B-Instruct-v0.1-FP8" test model Supports static or dynamic activation quantization with static weight quantization (all per tensor) Supports different scales for each expert weight Supports Fp8 in QKV layer Notes: The Expert Gate/Router always runs at half / full precision for now. If there are different weight scales between QKV layer (for separate QKV weights), they are re-quantized using layer.weight_scale.max() so we can have a single gemm for performance.

…trics (vllm-project#3937)

FILL IN THE PR DESCRIPTION HERE FIX #xxxx (*link existing issues this PR will resolve*) **BEFORE SUBMITTING, PLEASE READ THE CHECKLIST BELOW AND FILL IN THE DESCRIPTION ABOVE** --- <details>  <summary><b> PR Checklist (Click to Expand) </b></summary> <p>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.</p> <h3>PR Title and Classification</h3> <p>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:</p> <ul> <li><code>[Bugfix]</code> for bug fixes.</li> <li><code>[CI/Build]</code> for build or continuous integration improvements.</li> <li><code>[Doc]</code> for documentation fixes and improvements.</li> <li><code>[Model]</code> for adding a new model or improving an existing model. Model name should appear in the title.</li> <li><code>[Frontend]</code> For changes on the vLLM frontend (e.g., OpenAI API server, <code>LLM</code> class, etc.) </li> <li><code>[Kernel]</code> for changes affecting CUDA kernels or other compute kernels.</li> <li><code>[Core]</code> for changes in the core vLLM logic (e.g., <code>LLMEngine</code>, <code>AsyncLLMEngine</code>, <code>Scheduler</code>, etc.)</li> <li><code>[Hardware][Vendor]</code> for hardware-specific changes. Vendor name should appear in the prefix (e.g., <code>[Hardware][AMD]</code>).</li> <li><code>[Misc]</code> for PRs that do not fit the above categories. Please use this sparingly.</li> </ul> <p><strong>Note:</strong> If the PR spans more than one category, please include all relevant prefixes.</p> <h3>Code Quality</h3> <p>The PR need to meet the following code quality standards:</p> <ul> <li>We adhere to <a href="https://google.github.io/styleguide/pyguide.html">Google Python style guide</a> and <a href="https://google.github.io/styleguide/cppguide.html">Google C++ style guide</a>.</li> <li>Pass all linter checks. Please use <a href="https://github.com/vllm-project/vllm/blob/main/format.sh"><code>format.sh</code></a> to format your code.</li> <li>The code need to be well-documented to ensure future contributors can easily understand the code.</li> <li>Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.</li> <li>Please add documentation to <code>docs/source/</code> if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.</li> </ul> <h3>Notes for Large Changes</h3> <p>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 <code>rfc-required</code> and might not go through the PR.</p> <h3>What to Expect for the Reviews</h3> <p>The goal of the vLLM team is to be a <i>transparent reviewing machine</i>. 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: </p> <ul> <li> 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.</li> <li> 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.</li> <li> After the review, the reviewer will put an <code> action-required</code> label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.</li> <li> 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. </li> </ul> <h3>Thank You</h3> <p> 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! </p> </details>

Commits on May 7, 2024

stray issues

robertgshaw2-neuralmagic committed May 7, 2024

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Commits on May 9, 2024

fixed torch reinit

Robert Shaw committed May 9, 2024

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Upstream sync 2024 05 05 #224

Upstream sync 2024 05 05 #224

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