Enable scaled FP8 (e4m3fn) KV cache on ROCm (AMD GPU) (#3290)
Co-authored-by: Gregory Shtrasberg <Gregory.Shtrasberg@amd.com> Co-authored-by: HaiShaw <hixiao@gmail.com> Co-authored-by: AdrianAbeyta <Adrian.Abeyta@amd.com> Co-authored-by: Matthew Wong <Matthew.Wong2@amd.com> Co-authored-by: root <root@gt-pla-u18-08.pla.dcgpu> Co-authored-by: mawong-amd <156021403+mawong-amd@users.noreply.github.com> Co-authored-by: ttbachyinsda <ttbachyinsda@outlook.com> Co-authored-by: guofangze <guofangze@kuaishou.com> Co-authored-by: Michael Goin <mgoin64@gmail.com> Co-authored-by: jacobthebanana <50071502+jacobthebanana@users.noreply.github.com> Co-authored-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
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@@ -24,6 +24,7 @@ def main(args: argparse.Namespace):
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dtype=args.dtype,
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enforce_eager=args.enforce_eager,
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kv_cache_dtype=args.kv_cache_dtype,
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quantization_param_path=args.quantization_param_path,
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device=args.device,
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ray_workers_use_nsight=args.ray_workers_use_nsight,
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enable_chunked_prefill=args.enable_chunked_prefill,
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@@ -127,10 +128,23 @@ if __name__ == '__main__':
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parser.add_argument(
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"--kv-cache-dtype",
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type=str,
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choices=['auto', 'fp8_e5m2'],
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choices=['auto', 'fp8'],
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default='auto',
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help=
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'Data type for kv cache storage. If "auto", will use model data type.')
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'Data type for kv cache storage. If "auto", will use model data type. '
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'FP8_E5M2 (without scaling) is only supported on cuda version greater '
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'than 11.8. On ROCm (AMD GPU), FP8_E4M3 is instead supported for '
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'common inference criteria.')
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parser.add_argument(
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'--quantization-param-path',
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type=str,
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default=None,
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help='Path to the JSON file containing the KV cache scaling factors. '
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'This should generally be supplied, when KV cache dtype is FP8. '
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'Otherwise, KV cache scaling factors default to 1.0, which may cause '
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'accuracy issues. FP8_E5M2 (without scaling) is only supported on '
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'cuda version greater than 11.8. On ROCm (AMD GPU), FP8_E4M3 is '
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'instead supported for common inference criteria.')
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parser.add_argument(
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'--profile',
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action='store_true',
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