Class Operation

tensorflow/python/framework/ops.py:1616–2439

Represents a graph node that performs computation on tensors. An `Operation` is a node in a TensorFlow `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

@tf_export("Operation")
class Operation(object):
  """Represents a graph node that performs computation on tensors.

  An `Operation` is a node in a TensorFlow `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`)
  or `tf.Graph.create_op`.

  For example `c = tf.matmul(a, b)` creates an `Operation` of type
  "MatMul" that takes tensors `a` and `b` as input, and produces `c`
  as output.

  After the graph has been launched in a session, an `Operation` 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)`.
  """

  def __init__(self,
               node_def,
               g,
               inputs=None,
               output_types=None,
               control_inputs=None,
               input_types=None,
               original_op=None,
               op_def=None):
    r"""Creates an `Operation`.

    NOTE: This constructor validates the name of the `Operation` (passed
    as `node_def.name`). Valid `Operation` names match the following
    regular expression:

        [A-Za-z0-9.][A-Za-z0-9_.\\-/]*

    Args:
      node_def: `node_def_pb2.NodeDef`.  `NodeDef` for the `Operation`. Used for
        attributes of `node_def_pb2.NodeDef`, typically `name`, `op`, and
        `device`.  The `input` attribute is irrelevant here as it will be
        computed when generating the model.
      g: `Graph`. The parent graph.
      inputs: list of `Tensor` objects. The inputs to this `Operation`.
      output_types: list of `DType` objects.  List of the types of the `Tensors`
        computed by this operation.  The length of this list indicates the
        number of output endpoints of the `Operation`.
      control_inputs: list of operations or tensors from which to have a control
        dependency.
      input_types: List of `DType` objects representing the types of the tensors
        accepted by the `Operation`.  By default uses `[x.dtype.base_dtype for x
        in inputs]`.  Operations that expect reference-typed inputs must specify
        these explicitly.
      original_op: Optional. Used to associate the new `Operation` with an
        existing `Operation` (for example, a replica with the op that was
        replicated).
      op_def: Optional. The `op_def_pb2.OpDef` proto that describes the op type