Fix f8f8bf16_lite quantize op input in quantize_and_compute
#3667
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This pull request was exported from Phabricator. Differential Revision: D69272912 |
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Summary: heuristics tuning result for fp8 mixed precision fast_gemv: P1725480254 achieved perf numbers on par/almost identical with `cuda_lite_fp8` (trt-llm gemv kernel). Differential Revision: D69128901
Differential Revision: D69213404
…h#3667) Summary: X-link: facebookresearch/FBGEMM#745 A minor fix for trt-llm cudaCoreGemm `cuda_lite` op in quantize_bench script. when testing with `--bench_quantize` detected a failure with input ``` ... tree/deeplearning/fbgemm/fbgemm_gpu/experimental/gen_ai/bench/quantize_ops.py", line 797, in quantize_and_compute return self.compute(xq, wq, x_scale * w_scale) TypeError: FP8LiteGemm.compute() missing 1 required positional argument: 'w_scale' ``` Reviewed By: jwfromm Differential Revision: D69272912
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…h#3667) Summary: X-link: facebookresearch/FBGEMM#745 A minor fix for trt-llm cudaCoreGemm `cuda_lite` op in quantize_bench script. when testing with `--bench_quantize` detected a failure with input ``` ... tree/deeplearning/fbgemm/fbgemm_gpu/experimental/gen_ai/bench/quantize_ops.py", line 797, in quantize_and_compute return self.compute(xq, wq, x_scale * w_scale) TypeError: FP8LiteGemm.compute() missing 1 required positional argument: 'w_scale' ``` Reviewed By: jwfromm Differential Revision: D69272912
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Summary:
X-link: https://github.com/facebookresearch/FBGEMM/pull/745
A minor fix for trt-llm cudaCoreGemm
cuda_liteop in quantize_bench script.when testing with
--bench_quantizedetected a failure with inputReviewed By: jwfromm
Differential Revision: D69272912