more readme

README.md

@@ -55,7 +55,12 @@ class TinyBobNet:
 model = TinyBobNet()
 optim = optim.SGD([model.l1, model.l2], lr=0.001)
 
-# ... and complete like pytorch
+# ... and complete like pytorch, with (x,y) data
+
+out = model.forward(x)
+loss = out.mul(y).mean()
+loss.backward()
+optim.step()
 ```
 
 ### TODO (to make real neural network library)

test/mnist.py

@@ -41,14 +41,14 @@ for i in (t := trange(1000)):
   y = Tensor(y)
   
   # network
-  outs = model.forward(x)
+  out = model.forward(x)
 
   # NLL loss function
-  loss = outs.mul(y).mean()
+  loss = out.mul(y).mean()
   loss.backward()
   optim.step()
   
-  cat = np.argmax(outs.data, axis=1)
+  cat = np.argmax(out.data, axis=1)
   accuracy = (cat == Y).mean()
   
   # printing