|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/framework/ops.py#L1699-L1744) | A decorator for registering the gradient function for an op type. #### View aliases **Compat aliases for migration** See [Migration guide](https://www.tensorflow.org/guide/migrate) for more details. [`tf.compat.v1.RegisterGradient`](https://www.tensorflow.org/api_docs/python/tf/RegisterGradient)
tf.RegisterGradient( op_type ) This decorator is only used when defining a new op type. For an op with `m` inputs and `n` outputs, the gradient function is a function that takes the original `Operation` and `n` `Tensor` objects (representing the gradients with respect to each output of the op), and returns `m` `Tensor` objects (representing the partial gradients with respect to each input of the op). For example, assuming that operations of type `"Sub"` take two inputs `x` and `y`, and return a single output `x - y`, the following gradient function would be registered: @tf.RegisterGradient("Sub") def _sub_grad(unused_op, grad): return grad, tf.negative(grad) The decorator argument `op_type` is the string type of an operation. This corresponds to the `OpDef.name` field for the proto that defines the operation.


| ## Args || |---|---| | `op_type` | The string type of an operation. This corresponds to the `OpDef.name` field for the proto that defines the operation. |



| ## Raises || |---|---| | `TypeError` | If `op_type` is not string. |
## Methods ### `__call__` [View source](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/framework/ops.py#L1741-L1744) __call__( f: _T ) -> _T Registers the function `f` as gradient function for `op_type`.