Spaces:
Sleeping
Sleeping
| # 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. | |
| from itertools import product | |
| import pytest | |
| import torch | |
| from audiocraft.modules.seanet import SEANetEncoder, SEANetDecoder, SEANetResnetBlock | |
| from audiocraft.modules import StreamableConv1d, StreamableConvTranspose1d | |
| class TestSEANetModel: | |
| def test_base(self): | |
| encoder = SEANetEncoder() | |
| decoder = SEANetDecoder() | |
| x = torch.randn(1, 1, 24000) | |
| z = encoder(x) | |
| assert list(z.shape) == [1, 128, 75], z.shape | |
| y = decoder(z) | |
| assert y.shape == x.shape, (x.shape, y.shape) | |
| def test_causal(self): | |
| encoder = SEANetEncoder(causal=True) | |
| decoder = SEANetDecoder(causal=True) | |
| x = torch.randn(1, 1, 24000) | |
| z = encoder(x) | |
| assert list(z.shape) == [1, 128, 75], z.shape | |
| y = decoder(z) | |
| assert y.shape == x.shape, (x.shape, y.shape) | |
| def test_conv_skip_connection(self): | |
| encoder = SEANetEncoder(true_skip=False) | |
| decoder = SEANetDecoder(true_skip=False) | |
| x = torch.randn(1, 1, 24000) | |
| z = encoder(x) | |
| assert list(z.shape) == [1, 128, 75], z.shape | |
| y = decoder(z) | |
| assert y.shape == x.shape, (x.shape, y.shape) | |
| def test_seanet_encoder_decoder_final_act(self): | |
| encoder = SEANetEncoder(true_skip=False) | |
| decoder = SEANetDecoder(true_skip=False, final_activation='Tanh') | |
| x = torch.randn(1, 1, 24000) | |
| z = encoder(x) | |
| assert list(z.shape) == [1, 128, 75], z.shape | |
| y = decoder(z) | |
| assert y.shape == x.shape, (x.shape, y.shape) | |
| def _check_encoder_blocks_norm(self, encoder: SEANetEncoder, n_disable_blocks: int, norm: str): | |
| n_blocks = 0 | |
| for layer in encoder.model: | |
| if isinstance(layer, StreamableConv1d): | |
| n_blocks += 1 | |
| assert layer.conv.norm_type == 'none' if n_blocks <= n_disable_blocks else norm | |
| elif isinstance(layer, SEANetResnetBlock): | |
| for resnet_layer in layer.block: | |
| if isinstance(resnet_layer, StreamableConv1d): | |
| # here we add + 1 to n_blocks as we increment n_blocks just after the block | |
| assert resnet_layer.conv.norm_type == 'none' if (n_blocks + 1) <= n_disable_blocks else norm | |
| def test_encoder_disable_norm(self): | |
| n_residuals = [0, 1, 3] | |
| disable_blocks = [0, 1, 2, 3, 4, 5, 6] | |
| norms = ['weight_norm', 'none'] | |
| for n_res, disable_blocks, norm in product(n_residuals, disable_blocks, norms): | |
| encoder = SEANetEncoder(n_residual_layers=n_res, norm=norm, | |
| disable_norm_outer_blocks=disable_blocks) | |
| self._check_encoder_blocks_norm(encoder, disable_blocks, norm) | |
| def _check_decoder_blocks_norm(self, decoder: SEANetDecoder, n_disable_blocks: int, norm: str): | |
| n_blocks = 0 | |
| for layer in decoder.model: | |
| if isinstance(layer, StreamableConv1d): | |
| n_blocks += 1 | |
| assert layer.conv.norm_type == 'none' if (decoder.n_blocks - n_blocks) < n_disable_blocks else norm | |
| elif isinstance(layer, StreamableConvTranspose1d): | |
| n_blocks += 1 | |
| assert layer.convtr.norm_type == 'none' if (decoder.n_blocks - n_blocks) < n_disable_blocks else norm | |
| elif isinstance(layer, SEANetResnetBlock): | |
| for resnet_layer in layer.block: | |
| if isinstance(resnet_layer, StreamableConv1d): | |
| assert resnet_layer.conv.norm_type == 'none' \ | |
| if (decoder.n_blocks - n_blocks) < n_disable_blocks else norm | |
| def test_decoder_disable_norm(self): | |
| n_residuals = [0, 1, 3] | |
| disable_blocks = [0, 1, 2, 3, 4, 5, 6] | |
| norms = ['weight_norm', 'none'] | |
| for n_res, disable_blocks, norm in product(n_residuals, disable_blocks, norms): | |
| decoder = SEANetDecoder(n_residual_layers=n_res, norm=norm, | |
| disable_norm_outer_blocks=disable_blocks) | |
| self._check_decoder_blocks_norm(decoder, disable_blocks, norm) | |
| def test_disable_norm_raises_exception(self): | |
| # Invalid disable_norm_outer_blocks values raise exceptions | |
| with pytest.raises(AssertionError): | |
| SEANetEncoder(disable_norm_outer_blocks=-1) | |
| with pytest.raises(AssertionError): | |
| SEANetEncoder(ratios=[1, 1, 2, 2], disable_norm_outer_blocks=7) | |
| with pytest.raises(AssertionError): | |
| SEANetDecoder(disable_norm_outer_blocks=-1) | |
| with pytest.raises(AssertionError): | |
| SEANetDecoder(ratios=[1, 1, 2, 2], disable_norm_outer_blocks=7) | |