typo/comment following code review.

theano/configdefaults.py

@@ -391,7 +391,7 @@ AddConfigVar('compute_test_value',
 AddConfigVar('compute_test_value_opt',
              ("For debugging Theano optimization only."
               " Same as compute_test_value, but is used"
-              " durint Theano optimizatoin"),
+              " during Theano optimization"),
              EnumStr('off', 'ignore', 'warn', 'raise', 'pdb'),
              in_c_key=False)
 

theano/scalar/basic.py

@@ -183,40 +183,23 @@ class Scalar(Type):
 
     def dtype_specs(self):
         try:
-            # To help debug dtype/typenum problem, here is the list of numpy typenum.
+            # To help debug dtype/typenum problem, here is code to get
+            # the list of numpy typenum.  This list change between 32
+            # and 64 bit platform and probably also also between
+            # Windows and Linux.
+            # NOTE: equivalent type on a platform can have different typenum.
+            #     This is the source of all dtype/typenum problem found up to
+            #     now, as Theano always expect the exact typenum that
+            #     correspond to our supported dtype.
             """
-            for dtype in ['int8','uint8','short','ushort','intc','uintc', 'longlong','ulonglong','single','double','longdouble', 'csingle','cdouble','clongdouble', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64', 'complex64', 'complex128', 'float', 'double', 'int', 'uint']:
+            for dtype in ['int8', 'uint8', 'short', 'ushort', 'intc', 'uintc',
+                          'longlong', 'ulonglong', 'single', 'double',
+                          'longdouble', 'csingle', 'cdouble', 'clongdouble',
+                          'float32', 'float64', 'int8', 'int16', 'int32',
+                          'int64', 'uint8', 'uint16', 'uint32', 'uint64',
+                          'complex64', 'complex128', 'float', 'double',
+                          'int', 'uint']:
                 print dtype, np.zeros(1, dtype=dtype).dtype.num
-int8 1
-uint8 2
-short 3
-ushort 4
-intc 5
-uintc 6
-longlong 9
-ulonglong 10
-single 11
-double 12
-longdouble 13
-csingle 14
-cdouble 15
-clongdouble 16
-float32 11
-float64 12
-int8 1
-int16 3
-int32 5
-int64 7
-uint8 2
-uint16 4
-uint32 6
-uint64 8
-complex64 14
-complex128 15
-float 12
-double 12
-int 7
-uint 8
             """
             return {  # dtype: (py_type, c_type, cls_name)
                     'float32': (numpy.float32, 'npy_float32', 'Float32'),