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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""LSTM layers module."""
from torch import nn
class SLSTM(nn.Module):
"""
LSTM without worrying about the hidden state, nor the layout of the data.
Expects input as convolutional layout.
"""
def __init__(self, dimension: int, num_layers: int = 2, skip: bool = True):
super().__init__()
self.skip = skip
self.lstm = nn.LSTM(dimension, dimension, num_layers)
# def forward(self, x):
# x = x.permute(2, 0, 1)
# y, _ = self.lstm(x)
# if self.skip:
# y = y + x
# y = y.permute(1, 2, 0)
# return y
# 修改transpose顺序
def forward(self, x):
# # 插入reshape
# x = x.reshape(x.shape)
x1 = x.permute(2, 0, 1)
y, _ = self.lstm(x1)
y = y.permute(1, 2, 0)
if self.skip:
y = y + x
return y
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