subtensor.py 文件源码

def perform(self, node, inp, out_):
        x, i = inp
        out, = out_
        # Copy always implied by numpy advanced indexing semantic.
        if out[0] is not None and out[0].shape == (len(i),) + x.shape[1:]:
            o = out[0]
        else:
            o = None

        # 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.
        # We need to check if values in i can fit in numpy.intp, because
        # if they don't, that should be an error (no array can have that
        # many elements on a 32-bit arch).
        if i.dtype != numpy.intp:
            i_ = theano._asarray(i, dtype=numpy.intp)
            if not numpy.can_cast(i.dtype, numpy.intp):
                # Check if there was actually an incorrect conversion
                if numpy.any(i != i_):
                    raise IndexError(
                        'index contains values that are bigger '
                        'than the maximum array size on this system.', i)
            i = i_

        out[0] = x.take(i, axis=0, out=o)