tf.RegisterGradient  |  TensorFlow v2.16.1 (original) (raw)

A decorator for registering the gradient function for an op type.

View aliases

Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.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.

Methods

__call__

View source

__call__(
    f: _T
) -> _T

Registers the function f as gradient function for op_type.