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Guard CublasOps behind --fast arg
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@ -136,8 +136,9 @@ parser.add_argument("--deterministic", action="store_true", help="Make pytorch u
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class PerformanceFeature(enum.Enum):
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Fp16Accumulation = "fp16_accumulation"
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Fp8MatrixMultiplication = "fp8_matrix_mult"
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CublasOps = "cublas_ops"
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parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult")
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parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult cublas_ops")
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parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
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parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
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@ -388,7 +388,12 @@ def pick_operations(weight_dtype, compute_dtype, load_device=None, disable_fast_
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):
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return fp8_ops
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if CUBLAS_IS_AVAILABLE and weight_dtype == torch.float16 and (compute_dtype == torch.float16 or compute_dtype is None):
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if (
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PerformanceFeature.CublasOps in args.fast and
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CUBLAS_IS_AVAILABLE and
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weight_dtype == torch.float16 and
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(compute_dtype == torch.float16 or compute_dtype is None)
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):
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logging.info("Using cublas ops")
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return cublas_ops
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