More python 3.x fixes:

theano/gof/cc.py

@@ -17,9 +17,13 @@ if sys.version_info[:2] >= (3, 0):
     import hashlib
 
     def hash_from_code(msg):
+        # hashlib.md5() requires an object that supports buffer interface,
+        # but Python 3 (unicode) strings don't.
+        if isinstance(msg, str):
+            msg = msg.encode()
         # Python 3 does not like module names that start with
         # a digit.
-        return 'm' + hashlib.md5(msg.encode()).hexdigest()
+        return 'm' + hashlib.md5(msg).hexdigest()
 
 elif sys.version_info[:2] >= (2, 5):
     import hashlib

theano/scalar/basic.py

@@ -18,6 +18,7 @@ from copy import copy
 from itertools import imap
 from textwrap import dedent
 
+from six import PY3
 import numpy
 
 import theano
@@ -515,8 +516,12 @@ class _scalar_py_operators:
     def __mul__(self, other):
         return mul(self, other)
 
-    def __div__(self, other):
-        return div_proxy(self, other)
+    if PY3:
+        def __truediv__(self, other):
+            return div_proxy(self, other)
+    else:
+        def __div__(self, other):
+            return div_proxy(self, other)
 
     def __floordiv__(self, other):
         return int_div(self, other)

theano/tensor/basic.py

@@ -6,6 +6,7 @@ import sys
 import warnings
 from itertools import izip
 
+from six import PY3
 import numpy
 #from copy import copy as python_copy
 
@@ -1513,6 +1514,8 @@ class _tensor_py_operators:
             raise
         except (NotImplementedError, TypeError):
             return NotImplemented
+    if PY3:
+        __truediv__ = __div__
 
     def __pow__(self, other):
         # See explanation in __add__ for the error catched

theano/tensor/elemwise.py

@@ -123,7 +123,9 @@ class DimShuffle(Op):
 
         for i, j in enumerate(new_order):
             if j != 'x':
-                if not isinstance(j, int):
+                # There is a bug in numpy that results in isinstance(x, int) returning False for numpy integers.
+                # See <http://projects.scipy.org/numpy/ticket/2235>.
+                if not isinstance(j, (int, numpy.integer)):
                     raise TypeError(
                             "DimShuffle indices must be python ints.")
                 if j >= len(input_broadcastable):
@@ -1177,7 +1179,9 @@ class CAReduce(Op):
 
         if axis is None:
             self.axis = axis
-        elif isinstance(axis, int):
+        # There is a bug in numpy that results in isinstance(x, int) returning False for numpy integers.
+        # See <http://projects.scipy.org/numpy/ticket/2235>.
+        elif isinstance(axis, (int, numpy.integer)):
             self.axis = (axis,)
         else:
             self.axis = list(set(axis))

theano/tensor/opt.py

@@ -224,8 +224,8 @@ def inplace_elemwise_optimizer_op(OP):
                         candidate_output].type:
                         continue
 
-                    inplace_pattern = dict(baseline, **{candidate_output:
-                                                            candidate_input})
+                    inplace_pattern = dict(baseline)
+                    inplace_pattern[candidate_output] = candidate_input
                     try:
                         if hasattr(op.scalar_op, "make_new_inplace"):
                             new_scal = op.scalar_op.make_new_inplace(
@@ -510,7 +510,7 @@ class MakeVector(T.Op):
                     "The upcast of the inputs to MakeVector should match the "
                     "dtype given in __init__.")
             if not all(self.dtype == T.cast(i, dtype=dtype).dtype
-                       for a in inputs):
+                       for i in inputs):
                 raise TypeError("MakeVector.make_node expected inputs"
                                 " upcastable to %s. got %s" % (
                         self.dtype,

theano/tensor/tests/test_basic.py

@@ -13,6 +13,12 @@ from itertools import izip
 import __builtin__
 builtin_min = __builtin__.min
 
+from six import PY3
+if PY3:
+    operator_div = operator.truediv
+else:
+    operator_div = operator.div
+
 from nose.plugins.skip import SkipTest
 import numpy
 from numpy.testing import dec, assert_array_equal, assert_allclose
@@ -4420,7 +4426,7 @@ class t_dot(unittest.TestCase):
                          == ['Incompatible', 'shapes', 'for', 'gemv'] or
                     # Reported by Theano when 'exception_verbosity' is set
                     # to 'high'.
-                    e[0].split()[0:3] == ['dot', 'product', 'failed.'],
+                    e.args[0].split()[0:3] == ['dot', 'product', 'failed.'],
                     e)
         finally:
             _logger.setLevel(oldlevel)
@@ -5891,7 +5897,7 @@ class test_arithmetic_cast(unittest.TestCase):
             for cfg in ('numpy+floatX', ):  # Used to test 'numpy' as well.
                 config.cast_policy = cfg
                 for op in (operator.add, operator.sub, operator.mul,
-                           operator.div, operator.floordiv):
+                           operator_div, operator.floordiv):
                     for a_type in dtypes:
                         for b_type in dtypes:
                             # Note that we do not test division between
@@ -5899,7 +5905,7 @@ class test_arithmetic_cast(unittest.TestCase):
                             # Theano deals with integer division in its own
                             # special way (depending on `config.int_division`).
                             is_int_division = (
-                                    op is operator.div and
+                                    op is operator_div and
                                     a_type in tensor.discrete_dtypes and
                                     b_type in tensor.discrete_dtypes)
                             # We will test all meaningful combinations of
@@ -5982,12 +5988,12 @@ class test_arithmetic_cast(unittest.TestCase):
                                     config.int_division == 'floatX'):
                                     assert theano_dtype == config.floatX
                                     continue
-                                numpy_version =numpy.__version__.split('.')[:2]
+                                numpy_version = numpy.__version__.split('.')[:2]
                                 if (cfg == 'numpy+floatX' and
                                     a_type == 'complex128' and
                                     b_type == 'float32' and
                                     combo == ('scalar', 'array') and
-                                    bool(numpy_version >= [1, 6]) and
+                                    bool(numpy_version >= ['1', '6']) and
                                     theano_dtype == 'complex128' and
                                     numpy_dtypes == ['complex64',
                                                      'complex64']):