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34 lines
1.4 KiB
34 lines
1.4 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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 paddle
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from paddlespeech.s2t.modules.subsampling import Conv2dSubsampling4
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class Conv2dSubsampling4Pure(Conv2dSubsampling4):
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def __init__(self, idim: int, odim: int, dropout_rate: float):
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super().__init__(idim, odim, dropout_rate, None)
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self.output_dim = ((idim - 1) // 2 - 1) // 2 * odim
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self.receptive_field_length = 2 * (
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3 - 1) + 3 # stride_1 * (kernel_size_2 - 1) + kerel_size_1
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def forward(self, x: paddle.Tensor,
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x_len: paddle.Tensor) -> [paddle.Tensor, paddle.Tensor]:
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x = x.unsqueeze(1) # (b, c=1, t, f)
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x = self.conv(x)
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#b, c, t, f = paddle.shape(x) #not work under jit
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x = x.transpose([0, 2, 1, 3]).reshape([0, 0, -1])
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x_len = ((x_len - 1) // 2 - 1) // 2
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return x, x_len
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