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on
A100
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# Copyright (c) 2025 NVIDIA CORPORATION.
# Licensed under the MIT license.
# Adapted from https://github.com/NVlabs/VILA/tree/main under the Apache 2.0 license.
# LICENSE is in incl_licenses directory.
from dataclasses import dataclass
from transformers import PretrainedConfig
@dataclass
class QuantizationConfig:
quantize_model: str = "false"
symm: bool = True
epsilon: float = 1e-10
fabit: str = "E4M3"
fwbit: str = "E4M3"
bobit: str = "E5M2"
row_blocksize: int = -1
col_blocksize: int = -1
qchoice: str = "none"
pad_to_multiple_of: int = 0
def __init__(
self,
quantize_model,
symm,
epsilon,
fabit,
fwbit,
bobit,
row_blocksize,
col_blocksize,
qchoice,
pad_to_multiple_of,
**kwargs,
):
super().__init__()
self.quantize_model = quantize_model
self.symm = symm
self.epsilon = epsilon
self.fabit = fabit
self.fwbit = fwbit
self.bobit = bobit
self.row_blocksize = row_blocksize
self.col_blocksize = col_blocksize
self.qchoice = qchoice
self.pad_to_multiple_of = pad_to_multiple_of
# class QuantizationConfig(PretrainedConfig):
# def __init__(
# self,
# quantize_model="false",
# symm=True,
# epsilon=1e-10,
# fabit="E4M3",
# fwbit="E4M3",
# bobit="E5M2",
# row_blocksize=-1,
# col_blocksize=-1,
# qchoice="none",
# pad_to_multiple_of=0,
# **kwargs,
# ):
# super().__init__()
# self.quantize_model = quantize_model
# self.symm = symm
# self.epsilon = epsilon
# self.fabit = fabit
# self.fwbit = fwbit
# self.bobit = bobit
# self.row_blocksize = row_blocksize
# self.col_blocksize = col_blocksize
# self.qchoice = qchoice
# self.pad_to_multiple_of = pad_to_multiple_of
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