how to visualize pytorch model filters
import numpy as np
import matplotlib.pyplot as plt
from torchvision import utils
def visTensor(tensor, ch=0, allkernels=False, nrow=8, padding=1):
n,c,w,h = tensor.shape
if allkernels: tensor = tensor.view(n*c, -1, w, h)
elif c != 3: tensor = tensor[:,ch,:,:].unsqueeze(dim=1)
rows = np.min((tensor.shape[0] // nrow + 1, 64))
grid = utils.make_grid(tensor, nrow=nrow, normalize=True, padding=padding)
plt.figure( figsize=(nrow,rows) )
plt.imshow(grid.numpy().transpose((1, 2, 0)))
if __name__ == "__main__":
layer = 1
filter = model.features[layer].weight.data.clone()
visTensor(filter, ch=0, allkernels=False)
plt.axis('off')
plt.ioff()
plt.show()