Things that need to be lists but aren't.

theano/compile/debugmode.py

@@ -2291,8 +2291,8 @@ class _Maker(FunctionMaker):  # inheritance buys a few helper functions
             inputs = [inputs]
 
         # Wrap them in In or Out instances if needed.
-        inputs = map(self.wrap_in, inputs)
-        outputs = map(self.wrap_out, outputs)
+        inputs, outputs = (list(map(self.wrap_in, inputs)),
+                           list(map(self.wrap_out, outputs)))
         _inputs = gof.graph.inputs([o.variable for o in outputs] +
                                    [i.update for i in inputs
                                     if getattr(i, 'update', False)])
@@ -2320,7 +2320,7 @@ class _Maker(FunctionMaker):  # inheritance buys a few helper functions
                 optimizer(fgraph)
 
                 theano.compile.function_module.insert_deepcopy(
-                    fgraph, inputs, outputs + additional_outputs)
+                    fgraph, inputs, list(chain(outputs, additional_outputs)))
             finally:
                 theano.config.compute_test_value = compute_test_value_orig
 

theano/gof/tests/test_cc.py

@@ -87,7 +87,7 @@ class MyOp(Op):
 
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if input.type is not tdouble:
                 raise Exception("Error 1")

theano/gof/tests/test_destroyhandler.py

@@ -65,7 +65,7 @@ class MyOp(Op):
 
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 raise Exception("Error 1")

theano/gof/tests/test_graph.py

@@ -46,7 +46,7 @@ def MyVariable(thingy):
 class MyOp(Op):
 
     def make_node(self, *inputs):
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 print(input, input.type, type(input), type(input.type))

theano/gof/tests/test_link.py

@@ -39,7 +39,7 @@ class MyOp(Op):
 
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if input.type is not tdouble:
                 raise Exception("Error 1")

theano/gof/tests/test_op.py

@@ -57,7 +57,7 @@ class MyType(Type):
 class MyOp(Op):
 
     def make_node(self, *inputs):
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 raise Exception("Error 1")

theano/gof/tests/test_opt.py

@@ -39,7 +39,7 @@ class MyOp(Op):
         self.x = x
 
     def make_node(self, *inputs):
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 raise Exception("Error 1")

theano/gof/tests/test_toolbox.py

@@ -39,7 +39,7 @@ class MyOp(Op):
 
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 raise Exception("Error 1")

theano/scalar/tests/test_basic.py

@@ -237,7 +237,7 @@ class test_upgrade_to_float(object):
     # at least float32, not float16.
 
     unary_ops_vals = [
-        (inv, list(range(-127, 0) + range(1, 127))),
+        (inv, list(range(-127, 0)) + list(range(1, 127))),
         (sqrt, list(range(0, 128))),
         (log, list(range(1, 128))),
         (log2, list(range(1, 128))),
@@ -262,7 +262,7 @@ class test_upgrade_to_float(object):
         (arctanh, [0])]
 
     binary_ops_vals = [
-        (arctan2, list(range(-127, 128), range(-127, 128)))]
+        (arctan2, list(range(-127, 128)), list(range(-127, 128)))]
 
     @staticmethod
     def _test_unary(unary_op, x_range):
@@ -306,8 +306,8 @@ class test_upgrade_to_float(object):
     def test_true_div(self):
         # true_div's upcast policy is not exactly "upgrade_to_float",
         # so the test is a little bit different
-        x_range = range(-127, 128)
-        y_range = range(-127, 0) + range(1, 127)
+        x_range = list(range(-127, 128))
+        y_range = list(range(-127, 0)) + list(range(1, 127))
 
         xi = int8('xi')
         yi = int8('yi')

theano/scan_module/tests/test_scan.py

@@ -1706,7 +1706,7 @@ class T_Scan(unittest.TestCase):
 
         # Also validate that the mappings outer_inp_from_outer_out and
         # outer_inp_from_inner_inp produce the correct results
-        scan_node = updates.values()[0].owner
+        scan_node = list(updates.values())[0].owner
 
         result = scan_node.op.var_mappings['outer_inp_from_outer_out']
         expected_result = {0: 3, 1: 5, 2: 4}
@@ -3662,7 +3662,7 @@ class T_Scan(unittest.TestCase):
                                  n_steps=10,
                                  truncate_gradient=-1,
                                  go_backwards=False)
-        cost = updates.values()[0]
+        cost = list(updates.values())[0]
         g_sh = tensor.grad(cost, shared_var)
         fgrad = theano.function([], g_sh)
         assert fgrad() == 1

theano/tensor/tests/test_basic.py

@@ -846,7 +846,8 @@ _good_broadcast_div_mod_normal_float_no_complex = dict(
     uinteger=(randint(2, 3).astype("uint8"),
               randint_nonzero(2, 3).astype("uint8")),
     int8=[numpy.tile(numpy.arange(-127, 128, dtype='int8'), [254, 1]).T,
-          numpy.tile(numpy.array(range(-127, 0) + range(1, 128), dtype='int8'),
+          numpy.tile(numpy.array(list(range(-127, 0)) + list(range(1, 128)),
+                                 dtype='int8'),
                      [255, 1])],
     # This empty2 doesn't work for some tests. I don't remember why
     #empty2=(numpy.asarray([0]), numpy.asarray([])),
@@ -933,7 +934,7 @@ TrueDivInplaceTester = makeBroadcastTester(
 _good_inv = dict(
     normal=[5 * rand_nonzero((2, 3))],
     integers=[randint_nonzero(2, 3)],
-    int8=[numpy.array(range(-127, 0) + range(1, 127), dtype='int8')],
+    int8=[numpy.array(list(range(-127, 0)) + list(range(1, 127)), dtype='int8')],
     complex=[randcomplex_nonzero((2, 3))],
     empty=[numpy.asarray([], dtype=config.floatX)])
 

theano/tensor/tests/test_extra_ops.py

@@ -388,7 +388,7 @@ class CompressTester(utt.InferShapeTester):
 
 class TestRepeatOp(utt.InferShapeTester):
     def _possible_axis(self, ndim):
-        return [None] + range(ndim) + [-i for i in range(ndim)]
+        return [None] + list(range(ndim)) + [-i for i in range(ndim)]
 
     def setUp(self):
         super(TestRepeatOp, self).setUp()

theano/tensor/tests/test_merge.py

@@ -33,7 +33,7 @@ class MyOp(Op):
         self.x = x
 
     def make_node(self, *inputs):
-        inputs = map(as_variable, inputs)
+        inputs = list(map(as_variable, inputs))
         for input in inputs:
             if not isinstance(input.type, MyType):
                 raise Exception("Error 1")