Fix simplify ssim implementation#2563
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vfdev-5 merged 7 commits intopytorch:masterfrom May 4, 2022
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…/sadra-barikbin/ignite into Fix-simplify-SSIM-implementation
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Thanks @sadra-barikbin , lgtm!
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@sadra-barikbin I had to run in on cuda to make sure :( |
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May 4, 2022
| def reset(self) -> None: | ||
| # Not a tensor because batch size is not known in advance. | ||
| self._sum_of_batchwise_ssim = 0.0 # type: Union[float, torch.Tensor] | ||
| self._sum_of_ssim = torch.tensor(0.0, device=self._device) |
vfdev-5
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May 4, 2022
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| @sync_all_reduce("_sum_of_batchwise_ssim", "_num_examples") | ||
| @sync_all_reduce("_sum_of_ssim", "_num_examples") | ||
| def compute(self) -> torch.Tensor: |
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Let's return just python float instead of a tensor ?
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| assert isinstance(ignite_ssim, torch.Tensor) | ||
| assert ignite_ssim.dtype == torch.float64 | ||
| assert ignite_ssim.device == torch.device(device) | ||
| assert np.allclose(ignite_ssim.cpu().numpy(), skimg_ssim, atol=atol) | ||
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| def test_ssim(): | ||
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | ||
| y_pred = torch.rand(8, 3, 224, 224, device=device) | ||
| y = y_pred * 0.8 | ||
| _test_ssim( | ||
| y_pred, y, data_range=1.0, kernel_size=7, sigma=1.5, gaussian=False, use_sample_covariance=True, device=device | ||
| ) | ||
| assert ignite_ssim.device.type == torch.device(device).type | ||
| assert np.allclose(ignite_ssim.cpu().numpy(), skimg_ssim, atol=7e-5) |
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As we can return float instead of Tensor, let's update tests
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Fixes #2532
Description:
Based on #2562 ,
updatemethod became simpler.Check list: