(img, one_channel=False)
| 104 | |
| 105 | # Helper function for inline image display |
| 106 | def matplotlib_imshow(img, one_channel=False): |
| 107 | if one_channel: |
| 108 | img = img.mean(dim=0) |
| 109 | img = img / 2 + 0.5 # unnormalize |
| 110 | npimg = img.numpy() |
| 111 | if one_channel: |
| 112 | plt.imshow(npimg, cmap="Greys") |
| 113 | else: |
| 114 | plt.imshow(np.transpose(npimg, (1, 2, 0))) |
| 115 | |
| 116 | dataiter = iter(training_loader) |
| 117 | images, labels = next(dataiter) |