-
Notifications
You must be signed in to change notification settings - Fork 3k
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
[Build/CI] Fixing 'docker run' to re-enable AMD CI tests. #4642
[Build/CI] Fixing 'docker run' to re-enable AMD CI tests. #4642
Conversation
@@ -26,7 +26,7 @@ steps: | |||
- label: "AMD: {{ step.label }}" | |||
agents: | |||
queue: amd | |||
command: bash .buildkite/run-amd-test.sh "'cd {{ (step.working_dir or default_working_dir) | safe }} && {{ step.command or (step.commands | join(' && ')) | safe }}'" | |||
command: bash .buildkite/run-amd-test.sh "cd {{ (step.working_dir or default_working_dir) | safe }} ; {{ step.command or (step.commands | join(" ; ")) | safe }}" |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This might not fail the bash command inside. If the test failed, the whole command will not exit with 1.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I've checked (https://buildkite.com/vllm/ci/builds/6722)
I does fail on the failing test inside.
Even on the partially failing test, it still fails. See e.g. "AMD: Speculative decoding tests" or "AMD: Models Test" or "AMD: Engine Test" in the above build.
Looks like the AMD CI is broken after this PR? I saw the same error message in many CI runs for AMD tests:
|
No, this error is proven to be un-related to the present PR. We have definitely seen this issue before this PR. |
I see. Also I'm working on #4535 that changes AMD kernels a bit, but I keep seeing the compilation errors which I didn't see in the NVIDIA build. So I tried to find an existing success build for reference. If you have any idea about that error (https://buildkite.com/vllm/ci/builds/6803#018f550a-e708-4a0a-a48c-97a5a4d85a40/1106-1856) please let me know. |
The error you're referring to appears to be a cmake error during the container build. It is apparently persistent through multiple attempts across different AMD tests in the referred build. It is definitely not related to the PR #4642, though, as rocm containers were getting built before it. Cmake must have complained about something at some point above the final error message. To isolate and analyze the cause of the error during this CI build you'll need to make a fresh clone of the repo and then build a standard rocm docker container:
That how it gets built in the CI anyway ( vllm/.buildkite/run-amd-test.sh Line 20 in 8344f77
The stdout dump will give you plenty of information about your issue. |
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
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
This PR achieves the following goals:
Corrects docker run interface to launch containers properly;
Trims the number of AMD tests.