for col in range(n_cols): # Tiles each filter into a big horizontal grid
for row in range(images_per_row):
channel_image = layer_activation[0,:, :, col * images_per_row + row]
channel_image -= channel_image.mean()
channel_image /= channel_image.std()
channel_image *= 64
channel_image += 128
channel_image = np.clip(channel_image, 0, 255).astype('uint8')
display_grid[col * size : (col + 1) * size, # Displays the grid
row * size : (row + 1) * size] = channel_image
scale = 1. / size
plt.figure(figsize=(scale * display_grid.shape[1],
scale * display_grid.shape[0]))
plt.title(layer_name)
plt.grid(False)
plt.imshow(display_grid, aspect='auto', cmap='viridis')
Error Message : AttributeError: ‘tensorflow.python.framework.ops.EagerTensor’ object has no attribute ‘mean’