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# Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from dataclasses import dataclass
@dataclass
class LoRAConfig:
"""
Configuration settings for LoRAOptimizedLinear.
Attributes:
lora_r (int): LoRA attention dimension, also know as the rank. Defaults is 64.
lora_alpha (float): LoRA scaling factor, default is 16.
base_weight_sharding (int): The degree to which the base weights are sharded,
should typically be set to the data-parallel world size to maximize the memory
reduction benefits. Defaults to 1, which means this feature is disabled.
"""
lora_r: int = 64
lora_alpha: float = 16.
base_weight_sharding: int = 1
@dataclass
class QuantizationConfig:
"""
Configuration settings for quantization for LoRAOptimizedLinear, QuantizedLinear,
and QuantizedParameter
Attributes:
q_bits (int): The number of bits used for quantization. Default is 8.
mantissa_bits (int): The number of bits reserved for the mantissa in fixed-point quantization. Default is 3.
group_size (int): The size of the group used for quantization. Default is 512.
"""
q_bits: int = 8
mantissa_bits: int = 3
group_size: int = 512
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