tf.Operation     View source on GitHub    Represents a graph node that performs computation on tensors.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.Operation  
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).
 


 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 that this Operation represents.   
 


 Raises
  TypeError   if control inputs are not Operations or Tensors, or if node_def is not a NodeDef, or if g is not a Graph, or if inputs are not tensors, or if inputs and input_types are incompatible.  
  ValueError   if the node_def name is not valid.   
 


 Attributes
  control_inputs   The Operation objects on which this op has a control dependency. Before this op is executed, TensorFlow will ensure that the operations in self.control_inputs have finished executing. This mechanism can be used to run ops sequentially for performance reasons, or to ensure that the side effects of an op are observed in the correct order. 
 
  device   The name of the device to which this op has been assigned, if any.  
  graph   The Graph that contains this operation.  
  inputs   The sequence of Tensor objects representing the data inputs of this op.  
  name   The full name of this operation.  
  node_def   Returns the NodeDef representation of this operation.  
  op_def   Returns the OpDef proto that represents the type of this op.  
  outputs   The list of Tensor objects representing the outputs of this op.  
  traceback   Returns the call stack from when this operation was constructed.  
  type   The type of the op (e.g. "MatMul").    Methods colocation_groups View source 
colocation_groups()
 Returns the list of colocation groups of the op. get_attr View source 
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 View source 
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. 
Note: Before invoking Operation.run(), its graph must have been launched in a session, and either a default session must be available, or session must be specified explicitly.

 


 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 View source 
values()
 DEPRECATED: Use outputs.