le_image.shape)
Input shape: torch.Size([1, 3, 128, 128])

>>> print("Output shape:", model(sample_image, timestep=0).sample.shape)
Output shape: torch.Size([1, 3, 128, 128]) Great! Next, you’ll need a scheduler to add some noise to the image.  Create a scheduler The scheduler behaves differently depending on whether you’re using the model for training or inference. During inference, the scheduler generates image from the noise. During training