blocks.py 文件源码

def eval(self, inp, feed_dict=None, session=None, tolist=False,
           use_while_loop=True):
    """Evaluates this block on `inp` in a TF session.

    Intended for testing and interactive development. If there are any
    uninitialized variables, they will be initialized prior to evaluation.

    Args:
      inp: An input to the block.
      feed_dict: A dictionary that maps `Tensor` objects to feed values.
      session: The TF session to be used. Defaults to the default session.
      tolist: A bool; whether to return (possibly nested) Python lists
        in place of NumPy arrays.
      use_while_loop: A bool; whether to use a `tf.while_loop` in evaluation
        (default) or to unroll the loop. Provided for testing and debugging,
        should not affect the result.

    Returns:
      The result of running the block. If `output_type` is tensor, then a
      NumPy array (or Python list, if `tolist` is true). If a tuple, then a
      tuple. If a sequence, then a list, or an instance of itertools.repeat
      in the case of an infinite sequence. If metrics are defined then `eval`
      returns a `(result, metrics)` tuple, where `metrics` is a dict mapping
      metric names to NumPy arrays.

    Raises:
      ValueError: If `session` is none and no default session is registered.
        If the block contains no TF tensors or ops then a session is not
        required.
    """
    # pylint: disable=protected-access
    return tensorflow_fold.blocks.block_compiler.Compiler._interactive(  # pylint: disable=line-too-long
        self)._eval(inp, feed_dict, session, tolist, use_while_loop)