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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 | |