raw_random.py 文件源码

def infer_shape(self, node, i_shapes):
        r, shp = node.inputs[0:2]

        # if shp is a constant array of len 0, then it means 'automatic shape'
        unknown_shape = len(getattr(shp, 'data', [0, 1, 2])) == 0

        # if ndim_added == 0 and shape != () then shape
        if self.ndim_added == 0 and not unknown_shape:
            sample_shp = shp
        else:
            # if shape == () then it will depend on args
            # if ndim_added != 0 and shape != () then it will depend on args
            # Use the default infer_shape implementation.
            raise tensor.ShapeError()

        return [None, [sample_shp[i] for i in xrange(node.outputs[1].ndim)]]