You could visualize each “slice” of the activation volume coming from the convolution.
I created a small code snippet:
def show_activation_volume(grid):
    grid_arr = grid.numpy().transpose(1, 2, 0)
    grid_arr -= grid_arr.min()
    grid_arr /= grid_arr.max()
    plt.imshow(grid_arr)  

x = Variable(torch.randn(1, 3, 24, 24))
conv = nn.Conv2d(3, 50, 3)
output = conv(x)
output = output.data.transpose(0, 1)
grid = make_grid(output)
show_activation_volume(grid)

Is this what you are looking for?