Test ResnetBlock2D #1850
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Test ResnetBlock2D #1850
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patil-suraj
reviewed
Dec 29, 2022
tests/test_layers_utils.py
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| def test_resnet_default(self): | ||
| torch.manual_seed(0) | ||
| sample = torch.randn(1, 32, 64, 64) | ||
| temb = torch.randn(1, 128) | ||
| resnet_block = ResnetBlock2D(in_channels=32, temb_channels=128) | ||
| with torch.no_grad(): | ||
| output_tensor = resnet_block(sample, temb) | ||
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| assert output_tensor.shape == (1, 32, 64, 64) | ||
| output_slice = output_tensor[0, -1, -3:, -3:] | ||
| expected_slice = torch.tensor([-1.9010, -0.2974, -0.8245, -1.3533, 0.8742, -0.9645, -2.0584, 1.3387, -0.4746]) | ||
| assert torch.allclose(output_slice.flatten(), expected_slice, atol=1e-3) | ||
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| def test_restnet_with_use_in_shortcut(self): | ||
| torch.manual_seed(0) | ||
| sample = torch.randn(1, 32, 64, 64) | ||
| temb = torch.randn(1, 128) | ||
| resnet_block = ResnetBlock2D(in_channels=32, temb_channels=128, use_in_shortcut=True) | ||
| with torch.no_grad(): | ||
| output_tensor = resnet_block(sample, temb) | ||
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| assert output_tensor.shape == (1, 32, 64, 64) | ||
| output_slice = output_tensor[0, -1, -3:, -3:] | ||
| expected_slice = torch.tensor([0.2226, -1.0791, -0.1629, 0.3659, -0.2889, -1.2376, 0.0582, 0.9206, 0.0044]) | ||
| assert torch.allclose(output_slice.flatten(), expected_slice, atol=1e-3) |
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This looks good! We should also test this for GPU, this can be done using the torch_device. Check the AttentionBlockTests for reference. Let me know if you need any help.
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@patil-suraj Added and tested on both GPU and MPS. Lmk what else is needed. Thanks!
There are a few fast tests failing though -- those are due to test_pipelines.py::CustomPipelineTests, which is irrelevant to the changes here and has been failing from the main branch.
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@patil-suraj let me know if we can merge this. Thanks ~
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This looks super cool - thanks a lot @hchings :-) |
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What does this PR do?
Add test cases for Resnet block. Issue: #200