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2026-07-13 13:18:33 +08:00

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Python

# Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from abc import abstractmethod
from typing import Any, Dict, Optional, Tuple, Type
import torch
from deepspeed.runtime.config_utils import DeepSpeedConfigModel
from ..ds_module import DSModuleBase
from ..configs.norm_config import DSNormConfig
from ..module_registry import DSModuleRegistryBase
from ...inference_parameter import InferenceParameter
class DSPostNormBase(DSModuleBase):
"""
Base MixIn for all Post-Normalization modules. The interface represented by this
module is:
residual, hidden_out = norm(residual + hidden_in)
If residual and hidden_out are the same data type, then they may alias each other.
Furthermore, residual should be updated in-place.
"""
@staticmethod
def config_class() -> Type[DeepSpeedConfigModel]:
return DSNormConfig
def __init__(self, config: DSNormConfig, implementation_config: Dict[str, Any]) -> None:
super().__init__(config, implementation_config)
@abstractmethod
def transform_param(self, param: torch.Tensor) -> InferenceParameter:
"""
Transform a gamma/beta parameter. It is assumed that both transformations are
the same.
Parameters:
param (torch.Tensor): Gamma or beta parameter.
"""
...
def forward(self,
residual: torch.Tensor,
hidden_states: torch.Tensor,
gamma: torch.Tensor,
beta: Optional[torch.Tensor] = None) -> Tuple[torch.Tensor, torch.Tensor]:
"""
Parameters:
residual (torch.Tensor): Residual tensor.
hidden_states (torch.Tensor): Hidden states tensor.
Returns:
(torch.Tensor, torch.Tensor): Tuple of residual and hidden states.
Hidden states may alias with residual.
"""
raise NotImplementedError()
class DSPostNormRegistry(DSModuleRegistryBase):
registry: Dict = {}
@staticmethod
def associated_class() -> Type[DSModuleBase]:
return DSPostNormBase