zip -> izip

theano/scan_module/scan_utils.py

@@ -15,6 +15,7 @@ __contact__ = "Razvan Pascanu <r.pascanu@gmail>"
 
 import copy
 import logging
+from itertools import izip
 
 import numpy
 
@@ -291,7 +292,7 @@ def equal_computations(xs, ys, in_xs=None, in_ys=None):
     if in_ys is None:
         in_ys = []
 
-    for x, y in zip(xs, ys):
+    for x, y in izip(xs, ys):
         if x.owner and not y.owner:
             return False
         if y.owner and not x.owner:
@@ -301,7 +302,7 @@ def equal_computations(xs, ys, in_xs=None, in_ys=None):
                 return False
     if len(in_xs) != len(in_ys):
         return False
-    for _x, _y in zip(in_xs, in_ys):
+    for _x, _y in izip(in_xs, in_ys):
         if _x.type != _y.type:
             return False
 
@@ -313,7 +314,7 @@ def equal_computations(xs, ys, in_xs=None, in_ys=None):
     n_nodes = len(nds_x)
     cont = True
     idx = 0
-    for dx, dy in zip(xs, ys):
+    for dx, dy in izip(xs, ys):
         if not dx.owner or not dy.owner:
             if dy.owner or dx.owner:
                 return False
@@ -338,7 +339,7 @@ def equal_computations(xs, ys, in_xs=None, in_ys=None):
         elif len(nd_x.outputs) != len(nd_y.outputs):
             cont = False
         else:
-            for dx, dy in zip(nd_x.inputs, nd_y.inputs):
+            for dx, dy in izip(nd_x.inputs, nd_y.inputs):
                 if (dx, dy) not in common:
                     if dx != dy:
                         if (isinstance(dx, tensor.Constant) and
@@ -353,7 +354,7 @@ def equal_computations(xs, ys, in_xs=None, in_ys=None):
                             cont = False
 
         if cont:
-            for dx, dy in zip(nd_x.outputs, nd_y.outputs):
+            for dx, dy in izip(nd_x.outputs, nd_y.outputs):
                 common.add((dx, dy))
         idx += 1
 
@@ -372,7 +373,7 @@ def infer_shape(outs, inputs, input_shapes):
     # inside.  We don't use the full ShapeFeature interface, but we
     # let it initialize itself with an empty env, otherwise we will
     # need to do it manually
-    for inp, inp_shp in zip(inputs, input_shapes):
+    for inp, inp_shp in izip(inputs, input_shapes):
         if inp_shp is not None and len(inp_shp) != inp.ndim:
             assert len(inp_shp) == inp.ndim
 
@@ -380,7 +381,7 @@ def infer_shape(outs, inputs, input_shapes):
     shape_feature.on_attach(theano.gof.Env([], []))
 
     # Initialize shape_of with the input shapes
-    for inp, inp_shp in zip(inputs, input_shapes):
+    for inp, inp_shp in izip(inputs, input_shapes):
         shape_feature.set_shape(inp, inp_shp)
 
     def local_traverse(out):
@@ -689,7 +690,7 @@ def reconstruct_graph(inputs, outputs, tag=None):
         tag = ''
     nw_inputs = [safe_new(x, tag) for x in inputs]
     givens = {}
-    for nw_x, x in zip(nw_inputs, inputs):
+    for nw_x, x in izip(nw_inputs, inputs):
         givens[x] = nw_x
     allinputs = theano.gof.graph.inputs(outputs)
     for inp in allinputs: