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Represents a graph node that performs computation on tensors.
tf.Operation(
node_def,
g,
inputs=None,
output_types=None,
control_inputs=None,
input_types=None,
original_op=None,
op_def=None
)
An Operation
is a node in a tf.Graph
that takes zero or more Tensor
objects as input, and produces zero or more Tensor
objects as output.
Objects of type Operation
are created by calling a Python op constructor
(such as tf.matmul
) within a tf.function
or under a tf.Graph.as_default
context manager.
For example, within a tf.function
, c = tf.matmul(a, b)
creates an
Operation
of type "MatMul" that takes tensors a
and b
as input, and
produces c
as output.
If a tf.compat.v1.Session
is used, an Operation
of a tf.Graph
can be
executed by passing it to tf.Session.run
. op.run()
is a shortcut for
calling tf.compat.v1.get_default_session().run(op)
.
Methods
colocation_groups
colocation_groups()
Returns the list of colocation groups of the op.
experimental_set_type
experimental_set_type(
type_proto
)
Sets the corresponding node's experimental_type
field.
See the description of NodeDef.experimental_type
for more info.
Args | |
---|---|
type_proto
|
A FullTypeDef proto message. The root type_if of this object
must be TFT_PRODUCT , even for ops which only have a singlre return
value.
|
get_attr
get_attr(
name
)
Returns the value of the attr of this op with the given name
.
Args | |
---|---|
name
|
The name of the attr to fetch. |
Returns | |
---|---|
The value of the attr, as a Python object. |
Raises | |
---|---|
ValueError
|
If this op does not have an attr with the given name .
|
run
run(
feed_dict=None, session=None
)
Runs this operation in a Session
.
Calling this method will execute all preceding operations that produce the inputs needed for this operation.
Args | |
---|---|
feed_dict
|
A dictionary that maps Tensor objects to feed values. See
tf.Session.run for a description of the valid feed values.
|
session
|
(Optional.) The Session to be used to run to this operation. If
none, the default session will be used.
|
values
values()