Merge pull request #280 from delallea/minor

DESCRIPTION.txt

@@ -3,7 +3,7 @@ Theano is a Python library that allows you to define, optimize, and efficiently
  * **tight integration with NumPy:** a similar interface to NumPy's. numpy.ndarrays are also used internally in Theano-compiled functions.
  * **transparent use of a GPU:** perform data-intensive computations up to 140x faster than on a CPU (support for float32 only).
  * **efficient symbolic differentiation:** Theano can compute derivatives for functions of one or many inputs.
- * **speed and stability optimizations:** avoid nasty bugs when computing expressions such as log(1+ exp(x) ) for large values of x.
+ * **speed and stability optimizations:** avoid nasty bugs when computing expressions such as log(1 + exp(x)) for large values of x.
  * **dynamic C code generation:** evaluate expressions faster.
  * **extensive unit-testing and self-verification:** includes tools for detecting and diagnosing bugs and/or potential problems.
 

README.txt

@@ -33,8 +33,10 @@ Theano (current directory) is the distribution directory.
         * sparse depends upon tensor
         * sandbox can depend on everything else
     * Theano/examples are copies of the example on the wiki
-    * Theano/benchmark, Theano/bin and Theano/examples are in the distribution,
-      but not in the python package
+    * Theano/benchmark and Theano/examples are in the distribution, but not in
+      the Python package
+    * Theano/bin contains executable scripts that are copied to the bin folder
+      when the Python package is installed
     * Tests are distributed and are part of the package, i.e. fall in
       the appropriate submodules
     * Theano/doc contains files and scripts used to generate the documentation

theano/gof/graph.py

@@ -443,7 +443,7 @@ def stack_search(start, expand, mode='bfs', build_inv = False):
     return rval_list
 
 
-def ancestors(variable_list, blockers = None):
+def ancestors(variable_list, blockers=None):
     """Return the variables that contribute to those in variable_list (inclusive).
 
     :type variable_list: list of `Variable` instances
@@ -464,7 +464,7 @@ def ancestors(variable_list, blockers = None):
     return dfs_variables
 
 
-def inputs(variable_list, blockers = None):
+def inputs(variable_list, blockers=None):
     """Return the inputs required to compute the given Variables.
 
     :type variable_list: list of `Variable` instances

theano/misc/do_nightly_build

@@ -23,9 +23,10 @@ fi
 
 echo "Number of elements in the compiledir:"
 ls ${COMPILEDIR}|wc -l
-# We don't want warning for fixed error in the buildbot
+# We don't want warnings in the buildbod for errors already fixed.
 FLAGS=${THEANO_FLAGS},warn.argmax_pushdown_bug=False,warn.gpusum_01_011_0111_bug=False,warn.sum_sum_bug=False,warn.sum_div_dimshuffle_bug=False,$FLAGS
-# We want to see correctly optimization error, so make make them raise an error
+# We want to see correctly optimization errors, so make make them raise an
+# error.
 FLAGS=on_opt_error=raise,$FLAGS
 # Ignore user device and floatX config, because:
 #   1. Tests are intended to be run with device=cpu.

theano/tensor/blas.py

@@ -907,7 +907,7 @@ def _as_scalar(res, dtype=None):
             # If dtype is float64, we will cast int64 to float64.
             # This is valid when res is a scalar used as input to a dot22
             # as the cast of the scalar can be done before or after the dot22
-            #  and this will give the same result.
+            # and this will give the same result.
             if theano.scalar.upcast(res.dtype, dtype) == dtype:
                 return T.cast(rval, dtype)
             else: