TensorFlow 2 version | View source on GitHub |
A decorator for registering the gradient function for an op type.
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__
__call__(
f
)
Registers the function f
as gradient function for op_type
.