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Apr 1, 2026
| num_channels = 3 | ||
| sizes = (16, 16) | ||
| image = floats_tensor((batch_size, num_channels, num_frames) + sizes).to(torch_device) | ||
| image = torch.randn(batch_size, num_channels, num_frames, *sizes).to(torch_device) |
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Would use randn_tensor. You can use a Generator on CPU for better deterministic output.
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| @property | ||
| def dummy_input_tiling(self): | ||
| # Bridge for AutoencoderTesterMixin which still uses the old interface |
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I would recommend just creating a new Mixin e.g AutoencoderTestMixin that follows the new format and then once all the new AE tests are merged, we can remove the old class.
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