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Upstream sync 2024 05 19 #249

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merged 131 commits into from
Jun 3, 2024
Merged

Upstream sync 2024 05 19 #249

merged 131 commits into from
Jun 3, 2024

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@robertgshaw2-redhat robertgshaw2-redhat commented May 19, 2024

Upstream sync 2024 05 25 (#249)

SUMMARY:
Merge commits from vllm-project@c7f2cf2 to vllm-project@f68470e

Note that vllm-project@c7f2cf2 is NOT included in this merge.


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zhaoyang-star and others added 30 commits May 19, 2024 15:00
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.
…-project#4660)

[Core][Distributed] support both cpu and device tensor in broadcast tensor dict (vllm-project#4660)
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.
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cool.

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looks good, but can you update "remote push" workflow for python 3.10? it is still set to use "tmp", around line 55

test_skip_list: neuralmagic/tests/skip-for-remote-push-tmp.txt

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I could only look at a fraction of the file changes. there are a few known issues, but I'm approving.

@robertgshaw2-redhat robertgshaw2-redhat merged commit fec3563 into main Jun 3, 2024
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@robertgshaw2-redhat robertgshaw2-redhat deleted the upstream-sync-2024-05-19 branch June 3, 2024 15:22
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