Russell Bryant
e489ad7a21
- **Add SPDX license headers to python source files** - **Check for SPDX headers using pre-commit** commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745 Author: Russell Bryant <rbryant@redhat.com> Date: Fri Jan 31 14:18:24 2025 -0500 Add SPDX license headers to python source files This commit adds SPDX license headers to python source files as recommended to the project by the Linux Foundation. These headers provide a concise way that is both human and machine readable for communicating license information for each source file. It helps avoid any ambiguity about the license of the code and can also be easily used by tools to help manage license compliance. The Linux Foundation runs license scans against the codebase to help ensure we are in compliance with the licenses of the code we use, including dependencies. Having these headers in place helps that tool do its job. More information can be found on the SPDX site: - https://spdx.dev/learn/handling-license-info/ Signed-off-by: Russell Bryant <rbryant@redhat.com> commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea Author: Russell Bryant <rbryant@redhat.com> Date: Fri Jan 31 14:36:32 2025 -0500 Check for SPDX headers using pre-commit Signed-off-by: Russell Bryant <rbryant@redhat.com> --------- Signed-off-by: Russell Bryant <rbryant@redhat.com>
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import os
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from importlib.util import find_spec
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from typing import Any, Dict, List, Optional
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from torch.nn import Module
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from vllm.model_executor.layers.quantization.base_config import (
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QuantizationConfig)
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SUPPORTED_QUANT_DTYPE_LIST = ['s8', 'f8e4m3fn']
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class NeuronQuantConfig(QuantizationConfig):
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"""Int8 Quantization Config class for Neuron Backend."""
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def __init__(
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self,
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dequant_dtype: str = "f16",
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quantize_method: str = "vector_dynamic",
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) -> None:
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self.quant_dtype = os.getenv("NEURON_QUANT_DTYPE", "s8")
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if self.quant_dtype not in SUPPORTED_QUANT_DTYPE_LIST:
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raise ValueError(
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f"Neuron quantization datatype {self.quant_dtype} is not valid,"
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f"the quantization datatype should match one of the below types"
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f"{SUPPORTED_QUANT_DTYPE_LIST}")
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self.dequant_dtype = dequant_dtype
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self.quantize_method = quantize_method
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def get_name(self) -> str:
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return "neuron_quant"
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def get_supported_act_dtypes(self) -> List[str]:
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return SUPPORTED_QUANT_DTYPE_LIST
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@classmethod
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def get_min_capability(cls) -> int:
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raise NotImplementedError(
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"This function should not be called with Neuron Backend")
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@staticmethod
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def get_config_filenames() -> List[str]:
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return []
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@classmethod
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def from_config(cls, config: Dict[str, Any]) -> "NeuronQuantConfig":
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quantize_method = cls.get_from_keys(config, ["quantize_method"])
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dequant_dtype = cls.get_from_keys(config, ["dequant_dtype"])
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return cls(dequant_dtype=dequant_dtype,
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quantize_method=quantize_method)
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def get_quant_method(self, layer: Module, prefix: str) -> Optional[Any]:
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if find_spec("transformers_neuronx") is not None:
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return self.get_quantization_config()
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else:
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raise NotImplementedError(
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"Neuron Quantization is only supported through"
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" transformers_neuronx.")
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def get_quantization_config(self):
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from transformers_neuronx.config import QuantizationConfig
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return QuantizationConfig(quant_dtype=self.quant_dtype,
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dequant_dtype=self.dequant_dtype,
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quantize_method=self.quantize_method)
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