dict(zip()) -> dict(izip()) (and OrderedDict)

theano/compile/builders.py

 import theano
 from theano import gof
+from theano.compat import izip
 from theano.compile.function_module import orig_function
 from theano.compile import SharedVariable, rebuild_collect_shared
 from theano.gof import ops_with_inner_function
@@ -80,8 +81,8 @@ class OpFromGraph(gof.Op):
                               if isinstance(var, SharedVariable)]
         shared_vars = [var.type() for var in self.shared_inputs]
         new = rebuild_collect_shared(outputs, inputs=inputs + shared_vars,
-                                     replace=dict(zip(self.shared_inputs,
-                                                      shared_vars)),
+                                     replace=dict(izip(self.shared_inputs,
+                                                       shared_vars)),
                                      copy_inputs_over=False)
         (new_inputs, new_outputs,
          [clone_d, update_d, update_expr, shared_inputs]) = new
@@ -143,8 +144,8 @@ class OpFromGraph(gof.Op):
             grad_ops = self.grad_ops
         else:
             gs = theano.gradient.grad(cost=None,
-                                      known_grads=dict(zip(self.new_outputs,
-                                                           output_grads)),
+                                      known_grads=dict(izip(self.new_outputs,
+                                                            output_grads)),
                                       wrt=self.new_inputs,
                                       disconnected_inputs='ignore')
 

theano/compile/function_module.py

@@ -1047,11 +1047,11 @@ class FunctionMaker(object):
 
                         t2 = removeAllFgraph(t2)
 
-                        givens = dict(zip(gof.graph.inputs([t1]),
-                                          gof.graph.inputs([t2])))
+                        givens = dict(izip(gof.graph.inputs([t1]),
+                                           gof.graph.inputs([t2])))
 
-                        temp = dict(zip(gof.graph.inputs([t1]),
-                                        gof.graph.inputs([t2])))
+                        temp = dict(izip(gof.graph.inputs([t1]),
+                                         gof.graph.inputs([t2])))
 
                         # hack to remove inconstent entry in givens
                         # seems to work that but source of inconsistency

theano/gof/opt.py

@@ -17,6 +17,7 @@ import numpy
 
 import theano
 from theano import config
+from theano.compat import izip
 from theano.compat.six import string_types, iteritems
 from theano.compat.six.moves import reduce
 from theano.gof import graph, op, utils, unify, toolbox
@@ -1211,7 +1212,7 @@ class PatternSub(LocalOptimizer):
                 ret = self.transform(real_node, get_nodes=False)
                 if ret is not False and ret is not None:
                     assert len(real_node.outputs) == len(ret)
-                    return dict(zip(real_node.outputs, ret))
+                    return dict(izip(real_node.outputs, ret))
 
         if node.op != self.op:
             return False

theano/gradient.py

 """Driver for gradient calculations."""
 from __future__ import print_function
 import theano.compat.six.moves.builtins as builtins
-from theano.compat import izip
 import logging
 import time
 import warnings
@@ -12,7 +11,7 @@ import theano
 
 from theano import gof
 from theano.gof import Variable
-from theano.compat import OrderedDict
+from theano.compat import OrderedDict, izip
 from theano.compat.six.moves import xrange
 from theano.gof.null_type import NullType, null_type
 from theano.gof.op import get_debug_values
@@ -700,7 +699,7 @@ def subgraph_grad(wrt, end, start=None, cost=None, details=False):
             for i in range(len(grads)):
                 grads[i] += cost_grads[i]
 
-    pgrads = OrderedDict(zip(params, grads))
+    pgrads = OrderedDict(izip(params, grads))
     # separate wrt from end grads:
     wrt_grads = list(pgrads[k] for k in wrt)
     end_grads = list(pgrads[k] for k in end)

theano/sandbox/scan.py

@@ -18,6 +18,7 @@ from theano.compile import SharedVariable, function
 from theano.compat.six import iteritems
 from theano import compile
 from theano import gof
+from theano.compat import izip
 from theano.compat import OrderedDict, ifilter
 from theano.tensor import opt
 from theano import tensor
@@ -457,8 +458,8 @@ def scan(fn,
     # as non sequences at the end of our args
     fake_nonseqs = [x.type() for x in non_seqs]
     fake_outputs = scan_utils.clone(outputs + updates.values(),
-                                    replace=dict(zip(non_seqs,
-                                                     fake_nonseqs)))
+                                    replace=dict(izip(non_seqs,
+                                                      fake_nonseqs)))
     all_inputs = ifilter(
         lambda x: (isinstance(x, gof.Variable) and
                    not isinstance(x, SharedVariable) and
@@ -567,7 +568,7 @@ def scan(fn,
                          if (not isinstance(arg, SharedVariable) and
                              not isinstance(arg, tensor.Constant))]
 
-    givens.update(dict(zip(other_scan_args, other_inner_args)))
+    givens.update(dict(izip(other_scan_args, other_inner_args)))
     other_shared_scan_args = [arg.variable for arg
                         in dummy_f.maker.expanded_inputs
                         if (isinstance(arg.variable, SharedVariable) and
@@ -576,8 +577,7 @@ def scan(fn,
                         in dummy_f.maker.expanded_inputs
                         if (isinstance(arg.variable, SharedVariable) and
                             not arg.update)]
-    givens.update(dict(zip(other_shared_scan_args,
-                           other_shared_inner_args)))
+    givens.update(dict(izip(other_shared_scan_args, other_shared_inner_args)))
 
     ##
     # Step 6. Re-order the outputs and clone them replacing things

theano/sandbox/scan_module/tests/test_scan.py

@@ -136,8 +136,7 @@ class TestScan(unittest.TestCase):
                 shared_outs = [sh * 5 for sh in shared_vars]
                 states_out = [x for x in states_out]
                 pure_outs = [2 for x in xrange(n_outputs)]
-            return states_out + pure_outs, dict(zip(shared_vars,
-                                                    shared_outs))
+            return states_out + pure_outs, dict(izip(shared_vars, shared_outs))
 
         def execute_inner_graph(*args):
             """

theano/scalar/basic.py

@@ -13,6 +13,7 @@ you probably want to use theano.tensor.[c,z,f,d,b,w,i,l,]scalar!
 """
 from __future__ import print_function
 
+from itertools import chain
 import math
 import warnings
 from copy import copy
@@ -21,7 +22,7 @@ from textwrap import dedent
 import numpy
 
 import theano
-from theano.compat import PY3, imap
+from theano.compat import PY3, imap, izip
 from theano import gof, printing
 from theano.gof import (Op, utils, Variable, Constant, Type, Apply,
                         FunctionGraph)
@@ -3425,7 +3426,7 @@ class Composite(ScalarOp):
             res2 = theano.compile.rebuild_collect_shared(
                 inputs=outputs[0].owner.op.inputs,
                 outputs=outputs[0].owner.op.outputs,
-                replace=dict(zip(outputs[0].owner.op.inputs, res[1]))
+                replace=dict(izip(outputs[0].owner.op.inputs, res[1]))
             )
             assert len(res2[1]) == len(outputs)
             assert len(res[0]) == len(inputs)
@@ -3461,7 +3462,7 @@ class Composite(ScalarOp):
             assert len(inputs) == self.nin
             res = theano.compile.rebuild_collect_shared(
                 self.outputs,
-                replace=dict(zip(self.inputs, inputs)),
+                replace=dict(izip(self.inputs, inputs)),
                 rebuild_strict=False)
             # After rebuild_collect_shared, the Variable in inputs
             # are not necessarily in the graph represented by res.
@@ -3485,11 +3486,9 @@ class Composite(ScalarOp):
         raise NotImplementedError("grad is not implemented for Composite")
 
     def c_code(self, node, nodename, inames, onames, sub):
-        d = dict(zip(["i%i" % i for i in xrange(len(inames))],
-                     inames) +
-                 zip(["o%i" % i for i in xrange(len(onames))],
-                     onames),
-                 **sub)
+        d = dict(chain(izip(("i%i" % i for i in xrange(len(inames))), inames),
+                       izip(("o%i" % i for i in xrange(len(onames))),
+                            onames)), **sub)
         d['nodename'] = nodename
         if not 'id' in sub:
             # The use of a dummy id is safe as the code is in a separate block.

theano/scan_module/scan.py

@@ -46,7 +46,7 @@ import logging
 import numpy
 import warnings
 
-from theano.compat import ifilter
+from theano.compat import ifilter, izip
 from theano.compat.six import iteritems
 from theano.compile import SharedVariable, function
 from theano import compile
@@ -790,8 +790,8 @@ def scan(fn,
     # as non sequences at the end of our args
     fake_nonseqs = [x.type() for x in non_seqs]
     fake_outputs = scan_utils.clone(outputs,
-                                    replace=OrderedDict(zip(non_seqs,
-                                                     fake_nonseqs)))
+                                    replace=OrderedDict(izip(non_seqs,
+                                                             fake_nonseqs)))
     all_inputs = ifilter(
         lambda x: (isinstance(x, gof.Variable) and
                    not isinstance(x, SharedVariable) and
@@ -915,7 +915,7 @@ def scan(fn,
                          if (not isinstance(arg, SharedVariable) and
                              not isinstance(arg, tensor.Constant))]
 
-    givens.update(OrderedDict(zip(other_scan_args, other_inner_args)))
+    givens.update(OrderedDict(izip(other_scan_args, other_inner_args)))
 
     if strict:
         non_seqs_set = set(non_sequences if non_sequences != None else [])
@@ -939,8 +939,8 @@ def scan(fn,
                             in dummy_f.maker.expanded_inputs
                             if (isinstance(arg.variable, SharedVariable) and
                                 not arg.update)]
-    givens.update(OrderedDict(zip(other_shared_scan_args,
-                           other_shared_inner_args)))
+    givens.update(OrderedDict(izip(other_shared_scan_args,
+                                   other_shared_inner_args)))
 
     ##
     # Step 6. Re-order the outputs and clone them replacing things

theano/tensor/utils.py

 import numpy
 
 import theano
+from theano.compat import izip
 from theano.gof.cc import hash_from_code
 
 
@@ -96,7 +97,7 @@ def shape_of_variables(fgraph, input_shapes):
                                for dim in input_shapes[inp]]
     numeric_output_dims = compute_shapes(*numeric_input_dims)
 
-    sym_to_num_dict = dict(zip(output_dims, numeric_output_dims))
+    sym_to_num_dict = dict(izip(output_dims, numeric_output_dims))
 
     l = {}
     for var in fgraph.shape_feature.shape_of:

theano/tests/test_gradient.py

@@ -8,7 +8,7 @@ import numpy as np
 
 import theano
 from theano import gof
-from theano.compat import OrderedDict
+from theano.compat import OrderedDict, izip
 from theano.tests import unittest_tools as utt
 
 from theano import gradient
@@ -26,8 +26,8 @@ def grad_sources_inputs(sources, inputs):
     """
     if inputs is None:
         inputs = theano.gof.graph.inputs([source[0] for source in sources])
-    return dict(zip(inputs, theano.gradient.grad(cost=None, known_grads=dict(sources),
-        wrt=inputs, consider_constant=inputs)))
+    return dict(izip(inputs, theano.gradient.grad(cost=None, known_grads=dict(sources),
+                                                  wrt=inputs, consider_constant=inputs)))
 
 
 class testgrad_sources_inputs(unittest.TestCase):
@@ -467,7 +467,7 @@ def test_known_grads():
     for layer in layers:
         print('Testing by separately computing ', layer)
         first = theano.tensor.grad(cost, layer, disconnected_inputs='ignore')
-        known = dict(zip(layer, first))
+        known = dict(izip(layer, first))
         full = theano.tensor.grad(cost=None,
                 known_grads=known, wrt=inputs, disconnected_inputs='ignore')
         full = theano.function(inputs, full)
@@ -599,7 +599,7 @@ def test_subgraph_grad():
             wrt=params[i], end=grad_ends[i],
             start=next_grad, cost=costs[i]
         )
-        next_grad = OrderedDict(zip(grad_ends[i], next_grad))
+        next_grad = OrderedDict(izip(grad_ends[i], next_grad))
         param_grads.extend(param_grad)
     
     pgrads = theano.function(inputs, param_grads)