4a28bbf9659d96e15f0f241bcab76381e299097c,pymanopt/autodiff/backends/_tensorflow.py,_TensorFlowBackend,compute_gradient,#_TensorFlowBackend#Any#Any#,69

Before Change

        flattened_arguments = flatten_arguments(arguments)
        gradient = self._gradients(function, flattened_arguments)

        if len(flattened_arguments) == 1:
            (argument,) = flattened_arguments

            def unary_gradient(point):
                feed_dict = {argument: point}
                return self._session.run(gradient[0], feed_dict)
            return unary_gradient

        def nary_gradient(points):
            feed_dict = {
                argument: point

After Change

                for variable, argument in zip(variables, args)
            }
            return self._session.run(gradients, feed_dict)
        if len(variables) == 1:
            return unpack_singleton_iterable_return_value(gradient)
        return gradient

    @staticmethod
    def _hessian_vector_product(function, arguments, vectors):

Instances