625fbd05fef5c015c9b0e9cedbf12f639a6b5a76,keras_rcnn/backend/tensorflow_backend.py,,scatter_add_tensor,#,87

Before Change

        updates = tensorflow.convert_to_tensor(updates, name="updates")

        ref_shape = tensorflow.shape(ref, out_type=indices.dtype, name="ref_shape")

        scattered_updates = tensorflow.scatter_nd(
            indices, updates, ref_shape, name="scattered_updates"
        )

        with tensorflow.control_dependencies(
            [
                tensorflow.assert_equal(
                    ref_shape,
                    tensorflow.shape(scattered_updates, out_type=indices.dtype),
                )
            ]
        ):
            output = tensorflow.add(ref, scattered_updates, name=scope)

        return output


def meshgrid(*args, **kwargs):
    return tensorflow.meshgrid(*args, **kwargs)

After Change

    :return: Same as ref. Returned as a convenience for operations that want
    to use the updated values after the update is done.
    
    return tensorflow.tensor_scatter_nd_add(ref, indices, updates, name)


def meshgrid(*args, **kwargs):
    return tensorflow.compat.v1.meshgrid(*args, **kwargs)

Instances