Disable cuda version check in vllm-openai image #4530
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simon-mo
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May 1, 2024
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sorry i just merged the other PR, can you resolve the conflict? |
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🤦♂️ sorry another conflict |
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@simon-mo The conflict is solved. Please take a review. |
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ruff formatting formatting -isort formatting yapf add request class init file added adding CPU_executor change adding support for cpu engine formatting backslash error fix formatting tests update update worker test update worker test formatting Disable cuda version check in vllm-openai image (vllm-project#4530) [Bugfix] Fix `asyncio.Task` not being subscriptable (vllm-project#4623) [CI] use ccache actions properly in release workflow (vllm-project#4629) [CI] Add retry for agent lost (vllm-project#4633) Update lm-format-enforcer to 0.10.1 (vllm-project#4631) [Kernel] Make static FP8 scaling more robust (vllm-project#4570) Previously FP8 static scaling works if the scales are overestimating the maxima of all activation tensors during computation. However this will not always be the case even if the scales were calibrated very carefully. For example, with the activations in my checkpoint https://huggingface.co/pcmoritz/Mixtral-8x7B-v0.1-fp8-act-scale (which was calibrated on https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k), I'm getting the following mostly random performance on MMLU: | Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |------------------|-------|------|-----:|------|-----:|---|-----:| |mmlu |N/A |none | 0|acc |0.2295|± |0.0035| | - humanities |N/A |none | 5|acc |0.2421|± |0.0062| | - other |N/A |none | 5|acc |0.2398|± |0.0076| | - social_sciences|N/A |none | 5|acc |0.2171|± |0.0074| | - stem |N/A |none | 5|acc |0.2125|± |0.0073| With the fix in this PR where the scaled activations are clamped between [-std::numeric_limits<c10::Float8_e4m3fn>::max(), std::numeric_limits<c10::Float8_e4m3fn>::max()] to make sure there are no NaNs, the performance is | Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |------------------|-------|------|-----:|------|-----:|---|-----:| |mmlu |N/A |none | 0|acc |0.7008|± |0.0036| | - humanities |N/A |none | 5|acc |0.6453|± |0.0065| | - other |N/A |none | 5|acc |0.7692|± |0.0072| | - social_sciences|N/A |none | 5|acc |0.8083|± |0.0070| | - stem |N/A |none | 5|acc |0.6115|± |0.0083| This is not perfect yet but is getting very close to the FP16 / dynamic activation scale performance. [Core][Optimization] change python dict to pytorch tensor (vllm-project#4607) [Build/CI] Fixing 'docker run' to re-enable AMD CI tests. (vllm-project#4642) [Bugfix] Fixed error in slice_lora_b for MergedQKVParallelLinearWithLora (vllm-project#4609) [Core][Optimization] change copy-on-write from dict[int, list] to list (vllm-project#4648) [Bug fix][Core] fixup ngram not setup correctly (vllm-project#4551) Co-authored-by: Lei Wen <wenlei03@qiyi.com> Co-authored-by: Cade Daniel <edacih@gmail.com> Co-authored-by: Cody Yu <hao.yu.cody@gmail.com> [Core][Distributed] support cpu&device in broadcast tensor dict (vllm-project#4660) [Core][Distributed] support both cpu and device tensor in broadcast tensor dict (vllm-project#4660) [Core] Optimize sampler get_logprobs (vllm-project#4594) [CI] Make mistral tests pass (vllm-project#4596) [Bugfix][Kernel] allow non-power-of-2 for prefix prefill with alibi (vllm-project#4573) [Misc] Add `get_name` method to attention backends (vllm-project#4685) [Core] Faster startup for LoRA enabled models (vllm-project#4634) [Core][Optimization] change python dict to pytorch tensor for blocks to swap (vllm-project#4659) [CI/Test] fix swap test for multi gpu (vllm-project#4689) [Misc] Use vllm-flash-attn instead of flash-attn (vllm-project#4686) [Dynamic Spec Decoding] Auto-disable by the running queue size (vllm-project#4592) Co-authored-by: Cade Daniel <edacih@gmail.com> [Speculative decoding] [Bugfix] Fix overallocation in ngram + spec logprobs (vllm-project#4672) [Bugfix] Fine-tune gptq_marlin configs to be more similar to marlin (vllm-project#4626) consolidation
SwapnilDreams100
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May 29, 2024
formatting ruff formatting formatting -isort formatting yapf add request class init file added adding CPU_executor change adding support for cpu engine formatting backslash error fix formatting tests update update worker test update worker test formatting Disable cuda version check in vllm-openai image (vllm-project#4530) [Bugfix] Fix `asyncio.Task` not being subscriptable (vllm-project#4623) [CI] use ccache actions properly in release workflow (vllm-project#4629) [CI] Add retry for agent lost (vllm-project#4633) Update lm-format-enforcer to 0.10.1 (vllm-project#4631) [Kernel] Make static FP8 scaling more robust (vllm-project#4570) Previously FP8 static scaling works if the scales are overestimating the maxima of all activation tensors during computation. However this will not always be the case even if the scales were calibrated very carefully. For example, with the activations in my checkpoint https://huggingface.co/pcmoritz/Mixtral-8x7B-v0.1-fp8-act-scale (which was calibrated on https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k), I'm getting the following mostly random performance on MMLU: | Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |------------------|-------|------|-----:|------|-----:|---|-----:| |mmlu |N/A |none | 0|acc |0.2295|± |0.0035| | - humanities |N/A |none | 5|acc |0.2421|± |0.0062| | - other |N/A |none | 5|acc |0.2398|± |0.0076| | - social_sciences|N/A |none | 5|acc |0.2171|± |0.0074| | - stem |N/A |none | 5|acc |0.2125|± |0.0073| With the fix in this PR where the scaled activations are clamped between [-std::numeric_limits<c10::Float8_e4m3fn>::max(), std::numeric_limits<c10::Float8_e4m3fn>::max()] to make sure there are no NaNs, the performance is | Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |------------------|-------|------|-----:|------|-----:|---|-----:| |mmlu |N/A |none | 0|acc |0.7008|± |0.0036| | - humanities |N/A |none | 5|acc |0.6453|± |0.0065| | - other |N/A |none | 5|acc |0.7692|± |0.0072| | - social_sciences|N/A |none | 5|acc |0.8083|± |0.0070| | - stem |N/A |none | 5|acc |0.6115|± |0.0083| This is not perfect yet but is getting very close to the FP16 / dynamic activation scale performance. [Core][Optimization] change python dict to pytorch tensor (vllm-project#4607) [Build/CI] Fixing 'docker run' to re-enable AMD CI tests. (vllm-project#4642) [Bugfix] Fixed error in slice_lora_b for MergedQKVParallelLinearWithLora (vllm-project#4609) [Core][Optimization] change copy-on-write from dict[int, list] to list (vllm-project#4648) [Bug fix][Core] fixup ngram not setup correctly (vllm-project#4551) Co-authored-by: Lei Wen <wenlei03@qiyi.com> Co-authored-by: Cade Daniel <edacih@gmail.com> Co-authored-by: Cody Yu <hao.yu.cody@gmail.com> [Core][Distributed] support cpu&device in broadcast tensor dict (vllm-project#4660) [Core][Distributed] support both cpu and device tensor in broadcast tensor dict (vllm-project#4660) [Core] Optimize sampler get_logprobs (vllm-project#4594) [CI] Make mistral tests pass (vllm-project#4596) [Bugfix][Kernel] allow non-power-of-2 for prefix prefill with alibi (vllm-project#4573) [Misc] Add `get_name` method to attention backends (vllm-project#4685) [Core] Faster startup for LoRA enabled models (vllm-project#4634) [Core][Optimization] change python dict to pytorch tensor for blocks to swap (vllm-project#4659) [CI/Test] fix swap test for multi gpu (vllm-project#4689) [Misc] Use vllm-flash-attn instead of flash-attn (vllm-project#4686) [Dynamic Spec Decoding] Auto-disable by the running queue size (vllm-project#4592) Co-authored-by: Cade Daniel <edacih@gmail.com> [Speculative decoding] [Bugfix] Fix overallocation in ngram + spec logprobs (vllm-project#4672) [Bugfix] Fine-tune gptq_marlin configs to be more similar to marlin (vllm-project#4626) consolidation
mawong-amd
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Fix #4521
Currently we no need to check cuda version when using fp8 kv cache. As of now, vLLM's binaries are compiled with CUDA 12.1 and public PyTorch release versions by default. The vllm-openai image has also CUDA 12.1.