44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
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import torch
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import torch_npu
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# TODO(linfeng): Temporary compatibility shim for MXFP4/MXFP8 because current torch_npu
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# releases do not expose the required dtype attributes yet. Simplify or remove this
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# file after the torch_npu release in March 2026 includes those dtype symbols.
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FLOAT8_E8M0FNU_DTYPE = getattr(torch_npu, "float8_e8m0fnu", getattr(torch, "float8_e8m0fnu", None))
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FLOAT4_E2M1FN_X2_DTYPE = getattr(torch_npu, "float4_e2m1fn_x2", getattr(torch, "float4_e2m1fn_x2", None))
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HIFLOAT8_DTYPE = getattr(torch_npu, "hifloat8", None)
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def _get_missing_symbols(symbols: tuple[str, ...]) -> list[str]:
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return [symbol for symbol in symbols if not hasattr(torch_npu, symbol)]
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def _ensure_symbols_available(feature: str, symbols: tuple[str, ...]) -> None:
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missing_symbols = _get_missing_symbols(symbols)
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if not missing_symbols:
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return
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missing_symbols_str = ", ".join(missing_symbols)
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raise RuntimeError(
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f"{feature} requires a newer torch_npu runtime. Missing symbols: {missing_symbols_str}. "
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"Please upgrade torch_npu or disable MXFP quantization."
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)
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def ensure_mxfp8_scale_dtype_available(feature: str) -> None:
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_ensure_symbols_available(feature, ("float8_e8m0fnu",))
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def ensure_mxfp4_dtype_available(feature: str) -> None:
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_ensure_symbols_available(feature, ("float4_e2m1fn_x2", "float8_e8m0fnu"))
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def ensure_mxfp8_linear_available(feature: str) -> None:
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_ensure_symbols_available(feature, ("float8_e8m0fnu", "npu_dynamic_mx_quant", "npu_quant_matmul"))
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def ensure_mxfp8_moe_available(feature: str) -> None:
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_ensure_symbols_available(
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feature,
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("float8_e8m0fnu", "npu_dynamic_mx_quant", "npu_grouped_matmul_swiglu_quant_v2"),
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)
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