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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import pytest | |
| import torch | |
| import torch.nn as nn | |
| from mmcv.cnn.bricks import DepthwiseSeparableConvModule | |
| def test_depthwise_separable_conv(): | |
| with pytest.raises(AssertionError): | |
| # conv_cfg must be a dict or None | |
| DepthwiseSeparableConvModule(4, 8, 2, groups=2) | |
| # test default config | |
| conv = DepthwiseSeparableConvModule(3, 8, 2) | |
| assert conv.depthwise_conv.conv.groups == 3 | |
| assert conv.pointwise_conv.conv.kernel_size == (1, 1) | |
| assert not conv.depthwise_conv.with_norm | |
| assert not conv.pointwise_conv.with_norm | |
| assert conv.depthwise_conv.activate.__class__.__name__ == 'ReLU' | |
| assert conv.pointwise_conv.activate.__class__.__name__ == 'ReLU' | |
| x = torch.rand(1, 3, 256, 256) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 255, 255) | |
| # test dw_norm_cfg | |
| conv = DepthwiseSeparableConvModule(3, 8, 2, dw_norm_cfg=dict(type='BN')) | |
| assert conv.depthwise_conv.norm_name == 'bn' | |
| assert not conv.pointwise_conv.with_norm | |
| x = torch.rand(1, 3, 256, 256) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 255, 255) | |
| # test pw_norm_cfg | |
| conv = DepthwiseSeparableConvModule(3, 8, 2, pw_norm_cfg=dict(type='BN')) | |
| assert not conv.depthwise_conv.with_norm | |
| assert conv.pointwise_conv.norm_name == 'bn' | |
| x = torch.rand(1, 3, 256, 256) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 255, 255) | |
| # test norm_cfg | |
| conv = DepthwiseSeparableConvModule(3, 8, 2, norm_cfg=dict(type='BN')) | |
| assert conv.depthwise_conv.norm_name == 'bn' | |
| assert conv.pointwise_conv.norm_name == 'bn' | |
| x = torch.rand(1, 3, 256, 256) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 255, 255) | |
| # add test for ['norm', 'conv', 'act'] | |
| conv = DepthwiseSeparableConvModule(3, 8, 2, order=('norm', 'conv', 'act')) | |
| x = torch.rand(1, 3, 256, 256) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 255, 255) | |
| conv = DepthwiseSeparableConvModule( | |
| 3, 8, 3, padding=1, with_spectral_norm=True) | |
| assert hasattr(conv.depthwise_conv.conv, 'weight_orig') | |
| assert hasattr(conv.pointwise_conv.conv, 'weight_orig') | |
| output = conv(x) | |
| assert output.shape == (1, 8, 256, 256) | |
| conv = DepthwiseSeparableConvModule( | |
| 3, 8, 3, padding=1, padding_mode='reflect') | |
| assert isinstance(conv.depthwise_conv.padding_layer, nn.ReflectionPad2d) | |
| output = conv(x) | |
| assert output.shape == (1, 8, 256, 256) | |
| # test dw_act_cfg | |
| conv = DepthwiseSeparableConvModule( | |
| 3, 8, 3, padding=1, dw_act_cfg=dict(type='LeakyReLU')) | |
| assert conv.depthwise_conv.activate.__class__.__name__ == 'LeakyReLU' | |
| assert conv.pointwise_conv.activate.__class__.__name__ == 'ReLU' | |
| output = conv(x) | |
| assert output.shape == (1, 8, 256, 256) | |
| # test pw_act_cfg | |
| conv = DepthwiseSeparableConvModule( | |
| 3, 8, 3, padding=1, pw_act_cfg=dict(type='LeakyReLU')) | |
| assert conv.depthwise_conv.activate.__class__.__name__ == 'ReLU' | |
| assert conv.pointwise_conv.activate.__class__.__name__ == 'LeakyReLU' | |
| output = conv(x) | |
| assert output.shape == (1, 8, 256, 256) | |
| # test act_cfg | |
| conv = DepthwiseSeparableConvModule( | |
| 3, 8, 3, padding=1, act_cfg=dict(type='LeakyReLU')) | |
| assert conv.depthwise_conv.activate.__class__.__name__ == 'LeakyReLU' | |
| assert conv.pointwise_conv.activate.__class__.__name__ == 'LeakyReLU' | |
| output = conv(x) | |
| assert output.shape == (1, 8, 256, 256) | |