Cast indices to intp rather than intc.

The intent was correctly described in the comment - to cast to int32 on 32-bit machines and to int64 on 64-bit. However, numpy.intc is not correct type to achieve that because it has the size of C int and is 32-bit always. The correct type is numpy.intp which is defined as "large enough to fit a pointer." See http://docs.scipy.org/doc/numpy/reference/arrays.scalars.html .

Cast indices to intp rather than intc.
0566d22b · abalkin · ace3920c · 0566d22b
--- a/theano/tensor/basic.py
+++ b/theano/tensor/basic.py
@@ -6531,12 +6531,12 @@ class AdvancedSubtensor1(Op):
        else:
            o = None
-        # If i.dtype is more precise than numpy.intc (int32 on 32-bit machines,
+        # If i.dtype is more precise than numpy.intp (int32 on 32-bit machines,
        # int64 on 64-bit machines), numpy may raise the following error:
        # TypeError: array cannot be safely cast to required type.
        # Since we will probably not have an array with more than 2**31 items
-        # on a 32-bit arch, I suppose it is safe to cast i into intc.
+        # on a 32-bit arch, I suppose it is safe to cast i into intp.
-        i = theano._asarray(i, dtype=numpy.intc)
+        i = theano._asarray(i, dtype=numpy.intp)
        out[0] = x.take(i, axis=0, out=o)