mirror of
https://github.com/k2-fsa/icefall.git
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19c4214958
* Fix style and add copyright * Minor fix * Remove duplicate lines * Reformat conformer.py by black * Reformat code style with black. * Fix github workflows * Fix lhotse installation * Install icefall requirements * Update k2 version, remove lhotse from test workflow
50 lines
1.5 KiB
Python
Executable File
50 lines
1.5 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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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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from subsampling import Conv2dSubsampling
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from subsampling import VggSubsampling
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import torch
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def test_conv2d_subsampling():
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N = 3
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odim = 2
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for T in range(7, 19):
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for idim in range(7, 20):
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model = Conv2dSubsampling(idim=idim, odim=odim)
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x = torch.empty(N, T, idim)
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y = model(x)
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assert y.shape[0] == N
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assert y.shape[1] == ((T - 1) // 2 - 1) // 2
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assert y.shape[2] == odim
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def test_vgg_subsampling():
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N = 3
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odim = 2
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for T in range(7, 19):
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for idim in range(7, 20):
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model = VggSubsampling(idim=idim, odim=odim)
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x = torch.empty(N, T, idim)
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y = model(x)
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assert y.shape[0] == N
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assert y.shape[1] == ((T - 1) // 2 - 1) // 2
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assert y.shape[2] == odim
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