parameters: (tensors, feed_dict, graph, session=None)
return_statement: return session.run(tensors, feed_dict)
docstring: Uses the default session to evaluate one or more tensors.
  
    Args:
      tensors: A single Tensor, or a list of Tensor objects.
      feed_dict: A dictionary that maps Tensor objects (or tensor names) to lists,
        numpy ndarrays, TensorProtos, or strings.
      graph: The graph in which the tensors are defined.
      session: (Optional) A different session to use to evaluate "tensors".
  
    Returns:
      Either a single numpy ndarray if "tensors" is a single tensor; or a list
      of numpy ndarrays that each correspond to the respective element in
      "tensors".
  
    Raises:
      ValueError: If no default session is available; the default session
        does not have "graph" as its graph; or if "session" is specified,
        and it does not have "graph" as its graph.
docstring_summary: Uses the default session to evaluate one or more tensors.
docstring_tokens: Uses the default session to evaluate one or more tensors .
function: def _eval_using_default_session(tensors, feed_dict, graph, session=None):
    """Uses the default session to evaluate one or more tensors.
  
    Args:
      tensors: A single Tensor, or a list of Tensor objects.
      feed_dict: A dictionary that maps Tensor objects (or tensor names) to lists,
        numpy ndarrays, TensorProtos, or strings.
      graph: The graph in which the tensors are defined.
      session: (Optional) A different session to use to evaluate "tensors".
  
    Returns:
      Either a single numpy ndarray if "tensors" is a single tensor; or a list
      of numpy ndarrays that each correspond to the respective element in
      "tensors".
  
    Raises:
      ValueError: If no default session is available; the default session
        does not have "graph" as its graph; or if "session" is specified,
        and it does not have "graph" as its graph.
    """
    if session is None:
      session = get_default_session()
      if session is None:
        raise ValueError("Cannot evaluate tensor using `eval()`: No default "
                         "session is registered. Use `with "
                         "sess.as_default()` or pass an explicit session to "
                         "`eval(session=sess)`")
      if session.graph is not graph:
        raise ValueError("Cannot use the default session to evaluate tensor: "
                         "the tensor's graph is different from the session's "
                         "graph. Pass an explicit session to "
                         "`eval(session=sess)`.")
    else:
      if session.graph is not graph:
        raise ValueError("Cannot use the given session to evaluate tensor: "
                         "the tensor's graph is different from the session's "
                         "graph.")
    return session.run(tensors, feed_dict)
function_tokens: def _eval_using_default_session ( tensors , feed_dict , graph , session = None ) : if session is None : session = get_default_session ( ) if session is None : raise ValueError ( "Cannot evaluate tensor using `eval()`: No default " "session is registered. Use `with " "sess.as_default()` or pass an explicit session to " "`eval(session=sess)`" ) if session . graph is not graph : raise ValueError ( "Cannot use the default session to evaluate tensor: " "the tensor's graph is different from the session's " "graph. Pass an explicit session to " "`eval(session=sess)`." ) else : if session . graph is not graph : raise ValueError ( "Cannot use the given session to evaluate tensor: " "the tensor's graph is different from the session's " "graph." ) return session . run ( tensors , feed_dict )