52 lines
2.1 KiB
Python
52 lines
2.1 KiB
Python
# MIT License
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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# Copyright (c) [2023] [Meta Platforms, Inc. and affiliates.]
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# Copyright (c) [2025] [Ziyue Jiang]
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# SPDX-License-Identifier: MIT
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# This file has been modified by Ziyue Jiang on 2025/03/19
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# Original file was released under MIT, with the full license text # available at https://github.com/facebookresearch/encodec/blob/gh-pages/LICENSE.
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# This modified file is released under the same license.
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"""LSTM layers module."""
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from torch import nn
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class SLSTM(nn.Module):
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"""
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LSTM without worrying about the hidden state, nor the layout of the data.
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Expects input as convolutional layout.
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"""
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def __init__(self, dimension: int, num_layers: int = 2, skip: bool = True):
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super().__init__()
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self.skip = skip
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self.lstm = nn.LSTM(dimension, dimension, num_layers)
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# 修改transpose顺序
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def forward(self, x):
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x1 = x.permute(2, 0, 1)
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y, _ = self.lstm(x1)
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y = y.permute(1, 2, 0)
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if self.skip:
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y = y + x
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return y
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