X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=miniflow.py;h=04b9a23b7e372b041ffbccb97fe2d2ca9bad0436;hb=5ab8211805831629148d7b436b8770590f1987b0;hp=b5c8cb430bceab57c05136b4c26e534b56ab257e;hpb=7080726691be9341436db5a664778679600c5f62;p=pytorch.git

diff --git a/miniflow.py b/miniflow.py
index b5c8cb4..04b9a23 100755
--- a/miniflow.py
+++ b/miniflow.py
@@ -33,18 +33,15 @@ def sample_phi(nb):
 
 ######################################################################
 
-# START_LOG_PROBA
 def LogProba(x, ldj):
     log_p = ldj - 0.5 * (x**2 + math.log(2*pi))
     return log_p
-# END_LOG_PROBA
 
 ######################################################################
 
-# START_MODEL
 class PiecewiseLinear(nn.Module):
     def __init__(self, nb, xmin, xmax):
-        super(PiecewiseLinear, self).__init__()
+        super().__init__()
         self.xmin = xmin
         self.xmax = xmax
         self.nb = nb
@@ -59,7 +56,6 @@ class PiecewiseLinear(nn.Module):
         a = (u - n).clamp(0, 1)
         x = (1 - a) * y[n] + a * y[n + 1]
         return x
-# END_MODEL
 
     def invert(self, y):
         ys = self.alpha + self.xi.exp().cumsum(0).view(1, -1)
@@ -88,7 +84,6 @@ criterion = nn.MSELoss()
 for k in range(nb_epochs):
     acc_loss = 0
 
-# START_OPTIMIZATION
     for input in train_input.split(batch_size):
         input.requires_grad_()
         output = model(input)
@@ -103,7 +98,6 @@ for k in range(nb_epochs):
         optimizer.zero_grad()
         loss.backward()
         optimizer.step()
-# END_OPTIMIZATION
 
         acc_loss += loss.item()
     if k%10 == 0: print(k, loss.item())