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https://github.com/k2-fsa/icefall.git
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53b79fafa7
* Fix an error in TDNN-LSTM training. * WIP: Refactoring * Refactor transformer.py * Remove unused code. * Minor fixes. * Fix decoder padding mask. * Add MMI training with word pieces. * Remove unused files. * Minor fixes. * Refactoring. * Minor fixes. * Use pre-computed alignments in LF-MMI training. * Minor fixes. * Update decoding script. * Add doc about how to check and use extracted alignments. * Fix style issues. * Fix typos. * Fix style issues. * Disable macOS tests for now.
34 lines
858 B
Python
Executable File
34 lines
858 B
Python
Executable File
#!/usr/bin/env python3
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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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