fix some spacing

Author: jcjohnson

README.md

@@ -230,9 +230,6 @@ for t in range(500):
 import torch
 from torch.autograd import Variable
 
-
-
-
 class MyReLU(torch.autograd.Function):
   """
   We can implement our own custom autograd Functions by subclassing
@@ -391,7 +388,6 @@ with tf.Session() as sess:
 import torch
 from torch.autograd import Variable
 
-
 # N is batch size; D_in is input dimension;
 # H is hidden dimension; D_out is output dimension.
 N, D_in, H, D_out = 64, 1000, 100, 10

autograd/two_layer_net_custom_function.py

@@ -1,8 +1,6 @@
 import torch
 from torch.autograd import Variable
 
-
-
 """
 A fully-connected ReLU network with one hidden layer and no biases, trained to
 predict y from x by minimizing squared Euclidean distance.
@@ -14,7 +12,6 @@
 the ReLU function.
 """
 
-
 class MyReLU(torch.autograd.Function):
   """
   We can implement our own custom autograd Functions by subclassing

nn/dynamic_net.py

@@ -68,4 +68,3 @@ def forward(self, x):
   optimizer.zero_grad()
   loss.backward()
   optimizer.step()
-

nn/two_layer_net_nn.py

@@ -1,7 +1,6 @@
 import torch
 from torch.autograd import Variable
 
-
 """
 A fully-connected ReLU network with one hidden layer, trained to predict y from x
 by minimizing squared Euclidean distance.

nn/two_layer_net_optim.py

@@ -1,7 +1,6 @@
 import torch
 from torch.autograd import Variable
 
-
 """
 A fully-connected ReLU network with one hidden layer, trained to predict y from x
 by minimizing squared Euclidean distance.
@@ -54,4 +53,3 @@
 
   # Calling the step function on an Optimizer makes an update to its parameters
   optimizer.step()
-