x2 = np.asarray(np.arange(6, dtype=np.float64).reshape(2,3))# checkint gradients for x2 using a special deltaerror = gradient_checker.max_error(*gradient_checker.compute_gradient(lambdax2: math_ops.add(x1, x2), [x2], delta=1e-2)) tf_logging.info("x2 error = %f", ...
err_x = gradient_checker.compute_gradient_error(x, x_shape, y, x_shape) err_scale = gradient_checker.compute_gradient_error(scale, scale_shape, y, x_shape) err_offset = gradient_checker.compute_gradient_error(offset, scale_shape, y, x_shape) err_tolerance =1e-3self....