Class RegisterGradient
Defined in tensorflow/python/framework/ops.py
.
A decorator for registering the gradient function for an 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.
__init__
__init__(op_type)
Creates a new decorator with op_type
as the Operation type.
Args:
op_type
: The string type of an operation. This corresponds to theOpDef.name
field for the proto that defines the operation.
Methods
tf.RegisterGradient.__call__
__call__(f)
Registers the function f
as gradient function for op_type
.