Class Node

torch/fx/node.py:128–669

``Node`` is the data structure that represents individual operations within a ``Graph``. For the most part, Nodes represent callsites to various entities, such as operators, methods, and Modules (some exceptions include nodes that specify function inputs and outputs). Each ``Node``

@compatibility(is_backward_compatible=True)
class Node:
    """
    ``Node`` is the data structure that represents individual operations within
    a ``Graph``. For the most part, Nodes represent callsites to various entities,
    such as operators, methods, and Modules (some exceptions include nodes that
    specify function inputs and outputs). Each ``Node`` has a function specified
    by its ``op`` property. The ``Node`` semantics for each value of ``op`` are as follows:

    - ``placeholder`` represents a function input. The ``name`` attribute specifies the name this value will take on.
      ``target`` is similarly the name of the argument. ``args`` holds either: 1) nothing, or 2) a single argument
      denoting the default parameter of the function input. ``kwargs`` is don't-care. Placeholders correspond to
      the function parameters (e.g. ``x``) in the graph printout.
    - ``get_attr`` retrieves a parameter from the module hierarchy. ``name`` is similarly the name the result of the
      fetch is assigned to. ``target`` is the fully-qualified name of the parameter's position in the module hierarchy.
      ``args`` and ``kwargs`` are don't-care
    - ``call_function`` applies a free function to some values. ``name`` is similarly the name of the value to assign
      to. ``target`` is the function to be applied. ``args`` and ``kwargs`` represent the arguments to the function,
      following the Python calling convention
    - ``call_module`` applies a module in the module hierarchy's ``forward()`` method to given arguments. ``name`` is
      as previous. ``target`` is the fully-qualified name of the module in the module hierarchy to call.
      ``args`` and ``kwargs`` represent the arguments to invoke the module on, *excluding the self argument*.
    - ``call_method`` calls a method on a value. ``name`` is as similar. ``target`` is the string name of the method
      to apply to the ``self`` argument. ``args`` and ``kwargs`` represent the arguments to invoke the module on,
      *including the self argument*
    - ``output`` contains the output of the traced function in its ``args[0]`` attribute. This corresponds to the "return" statement
      in the Graph printout.
    """

    @compatibility(is_backward_compatible=True)
    def __init__(self, graph: 'Graph', name: str, op: str, target: 'Target',
                 args: Tuple['Argument', ...], kwargs: Dict[str, 'Argument'],
                 return_type : Optional[Any] = None) -> None:
        """
        Instantiate an instance of ``Node``. Note: most often, you want to use the
        Graph APIs, i.e. ``Graph.call_module``, ``Graph.call_method``, etc. rather
        than instantiating a ``Node`` directly.

        Args:
            graph (Graph): The ``Graph`` to which this ``Node`` should belong.

            name (str): The name to which the output of this ``Node`` should be assigned

            op (str): The opcode for this ``Node``. Can be one of 'placeholder',
                'call_method', 'call_module', 'call_function', 'get_attr',
                'output'

            target ('Target'): The target this op should call. See the broader
                ``Node`` docstring for more details.

            args (Tuple['Argument']): The args to be passed to ``target``

            kwargs (Dict[str, 'Argument']): The kwargs to be passed to ``target``

            return_type (Optional[Any]): The python type expression representing the
                type of the output of this node. This field can be used for
                annotation of values in the generated code or for other types
                of analyses.
        """