Hi, I want to create a function graph_hidden(net, layer, node), that takes a neural network, a layer (either 1 or 2) and a node (number from 0 to num. nodes) and plot the activation of the node.
I have this code so far but it keeps encountering errors, any advice would help greatly!
xrange = torch.arange(start=-8,end=8.1,step=0.01,dtype=torch.float32)
yrange = torch.arange(start=-8,end=8.1,step=0.01,dtype=torch.float32)
xcoord = xrange.repeat(yrange.size()[0])
ycoord = torch.repeat_interleave(yrange, xrange.size()[0], dim=0)
grid = torch.cat((xcoord.unsqueeze(1),ycoord.unsqueeze(1)),1)
with torch.no_grad(): # suppress updating of gradients
net.eval() # toggle batch norm, dropout
if (layer == 1):
output = net.hid1[node](grid)
elif (layer == 2):
output = net.hid2[node](grid)
net.train() # toggle batch norm, dropout back again
pred = (output >= 0.5).float()
# plot function computed by model
plt.clf()
plt.pcolormesh(xrange,yrange,pred.cpu().view(yrange.size()[0],xrange.size()[0]),
cmap='Wistia', shading='auto')