More backporting

theano/compile/mode.py

 import numpy
 import os
 import scipy.sparse as sp
-from .. import gof
+from theano import gof
 
 def check_equal(x, y):
     """

theano/compile/module.py

@@ -11,10 +11,12 @@ from theano.printing import pprint
 import io, sys
 
 if sys.version_info[:2] >= (2,5):
+  from functools import partial
   from collections import defaultdict
+else:
+  from theano.gof.python25 import any, all, defaultdict, partial
+
 from itertools import chain
-if sys.version_info[:2] >= (2,5):
-  from functools import partial
 
 import function_module as F
 import mode as get_mode

theano/gof/cc.py

@@ -10,6 +10,8 @@ import md5
 if sys.version_info[:2] >= (2,5):
   import hashlib
 
+from theano.gof.python25 import any, all
+
 # weave import
 from scipy import weave
 

theano/gof/toolbox.py

@@ -2,6 +2,8 @@ import sys
 
 if sys.version_info[:2] >= (2,5):
   from functools import partial
+else:
+  from theano.gof.python25 import partial
 
 import graph
 

theano/scalar/basic.py

@@ -6,7 +6,7 @@ import numpy
 
 from theano import gof
 from theano.gof import Op, utils, Variable, Constant, Type, Apply, Env
-from theano.gof.python25 import partial, all
+from theano.gof.python25 import partial, all, any
 
 def upcast(dtype, *dtypes):
     z = numpy.zeros((), dtype = dtype)

theano/tensor/basic.py

@@ -18,7 +18,7 @@ from theano import gradient
 
 import elemwise
 from theano import scalar as scal
-from theano.gof.python25 import partial, any
+from theano.gof.python25 import partial, any, all
 
 from theano import compile, printing
 from theano.printing import pprint, Print

theano/tensor/deprecated/rmodule.py

 """Define RModule, a Module providing random number streams in Theano graphs."""
 __docformat__ = "restructuredtext en"
 import sys
-import functools
-from functools import partial
+if sys.version_info[:2] >= (2,5):
+  from functools import partial
+else:
+  from theano.gof.python25 import partial
+
 from collections import deque
 
 import numpy
 from copy import copy
 
-from ...compile import (SymbolicInputKit, SymbolicInput, 
+from theano.compile import (SymbolicInputKit, SymbolicInput, 
         Module, module, Method, Member, In, Component)
-from ...gof import Container
+from theano.gof import Container
 
-from ...tensor import raw_random
+from theano.tensor import raw_random
 
 class KitComponent(Component):
     """

theano/tensor/elemwise.py

@@ -8,7 +8,7 @@ from theano import scalar
 from theano.scalar import Scalar
 from theano import printing
 from theano.printing import pprint
-from theano.gof.python25 import all
+from theano.gof.python25 import all, any
 from copy import copy, deepcopy
 
 

theano/tensor/nnet.py

@@ -2,15 +2,15 @@
 ## Not all of those ops have been thoroughly tested.
 
 #from theano import tensor, scalar
-from .. import gof
-from .. import scalar
-from .. import printing
-from ..printing import pprint
+from theano import gof
+from theano import scalar
+from theano import printing
+from theano.printing import pprint
 import basic as tensor
 import elemwise
 import numpy
 import opt
-from ..compile import optdb
+from theano.compile import optdb
 
 ############
 #
@@ -404,8 +404,19 @@ def local_softmax_with_bias(node):
             assert non_vectors #not empty
             if vectors:
                 #we're in business...
-                vector_sum = tensor.add(*vectors) if len(vectors)>1 else vectors[0]
-                non_vector_sum = tensor.add(*non_vectors) if len(non_vectors)>1 else non_vectors[0]
+                if len(vectors)>1:
+                  vector_sum = tensor.add(*vectors)
+                else:
+                  vector_sum = vectors[0]
+                #backport
+                #vector_sum = tensor.add(*vectors) if len(vectors)>1 else vectors[0]
+
+                if len(non_vectors)>1:
+                  non_vector_sum = tensor.add(*non_vectors)
+                else:
+                  non_vector_sum = non_vectors[0]
+
+                #non_vector_sum = tensor.add(*non_vectors) if len(non_vectors)>1 else non_vectors[0]
                 try:
                     sm_bias = softmax_with_bias(non_vector_sum, vector_sum)
                 except:
@@ -909,8 +920,14 @@ def categorical_crossentropy(coding_dist, true_dist, axis=1):
     if true_dist.ndim == 2:
         return -theano.sum(true_dist * log(coding_dist), axis=axis)
     else:
+        if axis == 0:
+          retval = coding_dist.T
+        else:
+          retval = coding_dist,
         return categorical_crossentropy_1hot(
-                coding_dist.T if axis == 0 else coding_dist,
+                #backport
+                #coding_dist.T if axis == 0 else coding_dist,
+                retval,
                 true_dist)
 
 

theano/tensor/opt.py

@@ -17,7 +17,7 @@ import sys
 from theano import compile  #to register the optimizer built by this file
 
 from theano.compile.debugmode import _debugprint
-from theano.gof.python25 import any
+from theano.gof.python25 import any, all
 
 # Utilities
 

theano/tests/unittest_tools.py

@@ -18,10 +18,18 @@ def fetch_seed(pseed=None):
     """
      
     seed = pseed or os.getenv("THEANO_UNITTEST_SEED", 666)
-    seed = None if seed=='random' else seed
+    if seed=='random':
+      seed = None
+    #backport
+    #seed = None if seed=='random' else seed
 
     try:
-        seed = int(seed) if seed else None
+        if seed:
+          seed = int(seed)
+        else:
+          seed = None
+        #backport
+        #seed = int(seed) if seed else None
     except ValueError:
         print >> sys.stderr, 'Error: THEANO_UNITTEST_SEED contains '\
                 'invalid seed, using None instead'