Merge pull request #1464 from delallea/minor

doc/install.txt

@@ -850,7 +850,7 @@ You can then proceed to the :ref:`windows_basic` or the :ref:`windows_bleeding_e
 Alternative: Canopy
 ###################
 
-Another software from Enthought that install all Theano dependancy.
+Another software from Enthought that installs all Theano dependencies.
 If you are affiliated with a university (as student or employee), you
 can download the installation for free.
 
@@ -863,8 +863,8 @@ can download the installation for free.
 - In Canopy Package Manager, search and install packages "mingw 4.5.2" and "libpython 1.2"
 - (Needed only for Theano 0.6rc3 or earlier)
   The "libpython 1.2" package installs files `libpython27.a` and `libmsvcr90.a` to
-  `C:\Users\<USER>\AppData\Local\Enthought\Canopy\User\libs`. Copy the two files to
-  `C:\Users\<USER>\AppData\Local\Enthought\Canopy\App\appdata\canopy-1.0.0.1160.win-x86_64\libs`.
+  `C:\\Users\\<USER>\\AppData\\Local\\Enthought\\Canopy\\User\\libs`. Copy the two files to
+  `C:\\Users\\<USER>\\AppData\\Local\\Enthought\\Canopy\\App\\appdata\\canopy-1.0.0.1160.win-x86_64\libs`.
 - (Needed only for Theano 0.6rc3 or earlier) Set the Theano flags
   ``blas.ldflags=-LC:\Users\<USER>\AppData\Local\Enthought\Canopy\App\appdata\canopy-1.0.0.1160.win-x86_64\Scripts -lmk2_core -lmk2_intel_thread -lmk2_rt``.
 

doc/tutorial/debug_faq.txt

@@ -288,12 +288,12 @@ can be achieved as follows:
 
 To help understand what is happening in your graph, you can
 disable the ``local_elemwise_fusion`` and all ``inplace``
-optimizations. The first is a speed optimization that merge elemwise
-operations together. This make it harder to know which particular
-elemwise cause the problem. The second optimization make some ops
-output overwrite its input. So, if an op create a bad output, you
-won't be able see the input that was overwriten in the ``post_fun``
-function. To disable those optimization (with a Theano version after
+optimizations. The first is a speed optimization that merges elemwise
+operations together. This makes it harder to know which particular
+elemwise causes the problem. The second optimization makes some ops'
+outputs overwrite their inputs. So, if an op creates a bad output, you
+will not be able to see the input that was overwriten in the ``post_func``
+function. To disable those optimizations (with a Theano version after
 0.6rc3), define the MonitorMode like this:
 
 .. code-block:: python
@@ -311,7 +311,7 @@ function. To disable those optimization (with a Theano version after
     mode with MonitorMode, as you need to define what you monitor.
 
 To be sure all inputs of the node are available during the call to
-``post_func``, you also must disable the garbage collector. Otherwise,
+``post_func``, you must also disable the garbage collector. Otherwise,
 the execution of the node can garbage collect its inputs that aren't
 needed anymore by the Theano function. This can be done with the Theano
 flag:

theano/compile/monitormode.py

@@ -37,14 +37,14 @@ class MonitorMode(Mode):
         :param optimizer: The optimizer to use. One may use for instance
             'fast_compile' to skip optimizations.
 
-        :param linker: DO NOT USE. This mode use its own linker.
+        :param linker: DO NOT USE. This mode uses its own linker.
             The parameter is needed to allow selecting optimizers to use.
         """
         self.pre_func = pre_func
         self.post_func = post_func
         wrap_linker = theano.gof.WrapLinkerMany([theano.gof.OpWiseCLinker()],
                                                 [self.eval])
-        if optimizer is 'default':
+        if optimizer == 'default':
             optimizer = theano.config.optimizer
         if (linker is not None and
             not isinstance(linker.mode, MonitorMode)):

theano/compile/pfunc.py

@@ -442,7 +442,8 @@ def pfunc(params, outputs=None, mode=None, updates=None, givens=None,
     if len(updates) > 0 and any(isinstance(v, Variable)
                                 for v in iter_over_pairs(updates)):
         raise ValueError(
-            "The updates parameter must an OrderedDict/dict or a list of list/tuple with 2 elements")
+            "The updates parameter must be an OrderedDict/dict or a list of "
+            "lists/tuples with 2 elements")
 
     # transform params into theano.compile.In objects.
     inputs = [_pfunc_param_to_in(p, allow_downcast=allow_input_downcast)

theano/gof/cmodule.py

@@ -1457,7 +1457,7 @@ def std_lib_dirs_and_libs():
         # directories.
         python_lib_dirs = [os.path.join(os.path.dirname(python_inc), 'libs')]
         if "Canopy" in python_lib_dirs[0]:
-            # Canopy store libpython27.a and libmsccr90.a in this directory.
+            # Canopy stores libpython27.a and libmsccr90.a in this directory.
             # For some reason, these files are needed when compiling Python
             # modules, even when libpython27.lib and python27.dll are
             # available, and the *.a files have to be found earlier than
@@ -1467,7 +1467,7 @@ def std_lib_dirs_and_libs():
             for f, lib in [('libpython27.a', 'libpython 1.2'),
                            ('libmsvcr90.a', 'mingw 4.5.2')]:
                 if not os.path.exists(os.path.join(libdir, f)):
-                    print ("Your python version is from Canopy. " +
+                    print ("Your Python version is from Canopy. " +
                            "You need to install the package '" + lib +
                            "' from Canopy package manager."
                            )