Merge pull request #1136 from delallea/minor

theano/gof/sched.py

@@ -3,6 +3,25 @@ from theano.gof.python25 import any, defaultdict
 
 
 ## {{{ http://code.activestate.com/recipes/578231/ (r1)
+# Copyright (c) Oren Tirosh 2012
+# 
+# Permission is hereby granted, free of charge, to any person obtaining a copy of
+# this software and associated documentation files (the "Software"), to deal in
+# the Software without restriction, including without limitation the rights to
+# use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+# of the Software, and to permit persons to whom the Software is furnished to do
+# so, subject to the following conditions:
+# 
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+# 
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
 def memodict(f):
     """ Memoization decorator for a function taking a single argument """
     class memodict(defaultdict):
@@ -12,6 +31,7 @@ def memodict(f):
     return memodict().__getitem__
 ## end of http://code.activestate.com/recipes/578231/ }}}
 
+
 def make_depends():
     @memodict
     def depends((a, b)):

theano/sandbox/cuda/__init__.py

@@ -375,11 +375,11 @@ def use(device,
                 import theano.sandbox.cuda.tests.test_driver
                 theano.sandbox.cuda.tests.test_driver.test_nvidia_driver1()
             if device_properties(use.device_number)["warpSize"] != 32:
-                raise ValueError("Your GPU have a warpSize of 32. Currently"
-                                 " we have code that depend on this. Email"
-                                 " Theano mailing list to tell us about"
+                raise ValueError("Your GPU has a warpSize != 32. Currently"
+                                 " we have code that depends on this. Email"
+                                 " the Theano mailing list to tell us about"
                                  " this new GPU as we don't know any with"
-                                 " this properties")
+                                 " this property")
             if move_shared_float32_to_gpu:
                 handle_shared_float32(True)
 

theano/tensor/basic.py

@@ -1443,7 +1443,7 @@ class _tensor_py_operators:
 
     def __sub__(self, other):
         # See explanation in __add__ for the error catched
-        # adn the return value in that case
+        # and the return value in that case
         try:
             return sub(self, other)
         except (NotImplementedError, TypeError):
@@ -1451,7 +1451,7 @@ class _tensor_py_operators:
 
     def __mul__(self, other):
         # See explanation in __add__ for the error catched
-        # adn the return value in that case
+        # and the return value in that case
         try:
             return mul(self, other)
         except (NotImplementedError, TypeError):
@@ -1459,7 +1459,7 @@ class _tensor_py_operators:
 
     def __div__(self, other):
         # See explanation in __add__ for the error catched
-        # adn the return value in that case
+        # and the return value in that case
         try:
             return div_proxy(self, other)
         except IntegerDivisionError:
@@ -6833,7 +6833,7 @@ def take(a, indices, axis=None, mode='raise'):
     # Reuse advanced_subtensor1 if indices is a vector
     if indices.ndim == 1:
         if mode == 'clip':
-            indices = clip(indices, 0, a.shape[axis]-1)
+            indices = clip(indices, 0, a.shape[axis] - 1)
         elif mode == 'wrap':
             indices = indices % a.shape[axis]
         if axis is None:
@@ -6853,10 +6853,12 @@ def take(a, indices, axis=None, mode='raise'):
         shape = indices.shape
         ndim = indices.ndim
     else:
-        shape = concatenate([a.shape[:axis], indices.shape, a.shape[axis+1:]])
+        shape = concatenate(
+                        [a.shape[:axis], indices.shape, a.shape[axis + 1:]])
         ndim = a.ndim + indices.ndim - 1
     return take(a, indices.flatten(), axis, mode).reshape(shape, ndim)
 
+
 #########################
 # Linalg : Dot
 #########################
@@ -7283,6 +7285,7 @@ def all(x, axis=None, keepdims=False):
         out = makeKeepDims(x, out, axis)
     return out
 
+
 class Diagonal(Op):
     """Return specified diagonals.
 
@@ -7310,7 +7313,7 @@ class Diagonal(Op):
         x = as_tensor_variable(x)
         assert x.ndim >= 2
         return Apply(self, [x], [tensor(dtype=x.dtype,
-                                        broadcastable=[False] * (x.ndim -1))])
+                                        broadcastable=[False] * (x.ndim - 1))])
 
     def perform(self, node, (x,), (z,)):
         z[0] = x.diagonal(self.offset, self.axis1, self.axis2)
@@ -7322,7 +7325,7 @@ class Diagonal(Op):
         in_shape, = shapes
         dim1 = in_shape[self.axis1]
         dim2 = in_shape[self.axis2]
-        out_shape = [d for i,d in enumerate(in_shape)
+        out_shape = [d for i, d in enumerate(in_shape)
                      if i not in (self.axis1, self.axis2)]
         # The following logic is inspired by C code of PyArray_Diagonal().
         offset = self.offset
@@ -7338,12 +7341,14 @@ class Diagonal(Op):
     def __str__(self):
         return self.__class__.__name__
 
+
 def diagonal(a, offset=0, axis1=0, axis2=1):
     if (offset, axis1, axis2) == (0, 0, 1):
         from theano.sandbox.linalg import extract_diag
         return extract_diag(a)
     return Diagonal(offset, axis1, axis2)(a)
 
+
 class Diag(Op):
 
     def __eq__(self, other):
@@ -7371,6 +7376,7 @@ class Diag(Op):
     def __str__(self):
         return self.__class__.__name__
 
+
 def diag(v, k=0):
     if v.ndim == 1:
         assert k == 0, "diagonals other than main are not implemented"

theano/tensor/nnet/nnet.py

@@ -109,7 +109,7 @@ class SoftmaxWithBias(gof.Op):
 
         if (PyArray_NDIM(%(x)s) != 2)
         {
-            PyErr_SetString(PyExc_ValueError, "a not 2d tensor");
+            PyErr_SetString(PyExc_ValueError, "not a 2d tensor");
             %(fail)s;
         }
         if (PyArray_NDIM(%(b)s) != 1)
@@ -120,7 +120,7 @@ class SoftmaxWithBias(gof.Op):
         if ((PyArray_DESCR(%(x)s)->type_num != NPY_DOUBLE) &&
             (PyArray_DESCR(%(x)s)->type_num != NPY_FLOAT))
         {
-            PyErr_SetString(PyExc_TypeError, "a not float");
+            PyErr_SetString(PyExc_TypeError, "not a float");
             %(fail)s;
         }
         if ((PyArray_DESCR(%(b)s)->type_num != NPY_DOUBLE) &&
@@ -401,13 +401,13 @@ class Softmax(gof.Op):
 
         if (%(x)s->nd != 2)
         {
-            PyErr_SetString(PyExc_ValueError, "a not 2d tensor");
+            PyErr_SetString(PyExc_ValueError, "not a 2d tensor");
             %(fail)s;
         }
         if ((%(x)s->descr->type_num != PyArray_DOUBLE) &&
             (%(x)s->descr->type_num != PyArray_FLOAT))
         {
-            PyErr_SetString(PyExc_TypeError, "a not float");
+            PyErr_SetString(PyExc_TypeError, "not a float");
             %(fail)s;
         }