PYTHON

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()