Function func_graph_from_py_func

tensorflow/python/framework/func_graph.py:736–961

Returns a `FuncGraph` generated from `python_func`. Args: name: an identifier for the function. python_func: the Python function to trace. args: the positional args with which the Python function should be called; ignored if a signature is provided. kwargs: the keyword args

(name,
                            python_func,
                            args,
                            kwargs,
                            signature=None,
                            func_graph=None,
                            autograph=False,
                            autograph_options=None,
                            add_control_dependencies=True,
                            arg_names=None,
                            op_return_value=None,
                            collections=None,
                            capture_by_value=None,
                            override_flat_arg_shapes=None)

def func_graph_from_py_func(name,
                            python_func,
                            args,
                            kwargs,
                            signature=None,
                            func_graph=None,
                            autograph=False,
                            autograph_options=None,
                            add_control_dependencies=True,
                            arg_names=None,
                            op_return_value=None,
                            collections=None,
                            capture_by_value=None,
                            override_flat_arg_shapes=None):
  """Returns a `FuncGraph` generated from `python_func`.

  Args:
    name: an identifier for the function.
    python_func: the Python function to trace.
    args: the positional args with which the Python function should be called;
      ignored if a signature is provided.
    kwargs: the keyword args with which the Python function should be called;
      ignored if a signature is provided.
    signature: a possibly nested sequence of `TensorSpecs` specifying the shapes
      and dtypes of the arguments. When a signature is provided, `args` and
      `kwargs` are ignored, and `python_func` is traced with Tensors conforming
      to `signature`. If `None`, the shapes and dtypes are inferred from the
      inputs.
    func_graph: Optional. An instance of FuncGraph. If provided, we will use
      this graph else a new one is built and returned.
    autograph: whether to use autograph to compile `python_func`.
      See https://www.tensorflow.org/guide/autograph for more information.
    autograph_options: additional knobs to control when `autograph=True`.
      See https://www.tensorflow.org/guide/autograph for more information.
    add_control_dependencies: If True, automatically adds control dependencies
      to ensure program order matches execution order and stateful ops always
      execute.
    arg_names: Optional list of argument names, used to give input placeholders
      recognizable names.
    op_return_value: Optional. A Tensor. If set and `python_func` returns
      Operations, those return values will be replaced with this value. If not
      set, returning an Operation triggers an error.
    collections: a dictionary of collections this FuncGraph should start
      with. If not specified (None), the FuncGraph will read (but not write to)
      the outer graph's collections that are not whitelisted, and both
      read and write to the outer graph's collections that are whitelisted.
      The current whitelisted collections are the global variables, the
      local variables, and the trainable variables.
      Defaults to None.
    capture_by_value: An optional boolean. If True, the func graph will capture
      Variables by value instead of reference. By default inherit from outer
      graphs, and failing that will default to False.
    override_flat_arg_shapes: An optional list of instances that are either
      `None` or `TensorShape`.  The length must match that of
      `nest.flatten((args, kwargs), expand_composites=True)`.  The entries
      containing value `None` must match entries in flattened arguments
      containing non-tensors, while entries containing a `TensorShape` must
      match entries in the flattened arguments containing tensors.