mirror of https://github.com/hpcaitech/ColossalAI
79 lines
2.2 KiB
Python
79 lines
2.2 KiB
Python
# Copyright 2021 AlQuraishi Laboratory
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import torch
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import torch.nn as nn
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from functools import partialmethod
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from typing import Union, List
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class Dropout(nn.Module):
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"""
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Implementation of dropout with the ability to share the dropout mask
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along a particular dimension.
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If not in training mode, this module computes the identity function.
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"""
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def __init__(self, r: float, batch_dim: Union[int, List[int]]):
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"""
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Args:
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r:
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Dropout rate
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batch_dim:
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Dimension(s) along which the dropout mask is shared
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"""
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super(Dropout, self).__init__()
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self.r = r
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if type(batch_dim) == int:
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batch_dim = [batch_dim]
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self.batch_dim = batch_dim
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self.dropout = nn.Dropout(self.r)
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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"""
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Args:
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x:
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Tensor to which dropout is applied. Can have any shape
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compatible with self.batch_dim
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"""
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shape = list(x.shape)
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if self.batch_dim is not None:
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for bd in self.batch_dim:
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shape[bd] = 1
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mask = x.new_ones(shape)
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mask = self.dropout(mask)
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x *= mask
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return x
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class DropoutRowwise(Dropout):
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"""
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Convenience class for rowwise dropout as described in subsection
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1.11.6.
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"""
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__init__ = partialmethod(Dropout.__init__, batch_dim=-3)
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class DropoutColumnwise(Dropout):
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"""
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Convenience class for columnwise dropout as described in subsection
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1.11.6.
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"""
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__init__ = partialmethod(Dropout.__init__, batch_dim=-2)
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