class_docstr: Represents a variable-length list of items from spaces.Repeated.
  
  RepeatedValues are created when you use spaces.Repeated, and are
  accessible as part of input_dict["obs"] in ModelV2 forward functions.
  
  Example:
      Suppose the gym space definition was:
          Repeated(Repeated(Box(K), N), M)
  
      Then in the model forward function, input_dict["obs"] is of type:
          RepeatedValues(RepeatedValues(<Tensor shape=(B, M, N, K)>))
  
      The tensor is accessible via:
          input_dict["obs"].values.values
  
      And the actual data lengths via:
          # outer repetition, shape [B], range [0, M]
          input_dict["obs"].lengths
              -and-
          # inner repetition, shape [B, M], range [0, N]
          input_dict["obs"].values.lengths
  
  Attributes:
      values: The padded data tensor of shape [B, max_len, ..., sz],
          where B is the batch dimension, max_len is the max length of this
          list, followed by any number of sub list max lens, followed by the
          actual data size.
      lengths (List[int]): Tensor of shape [B, ...] that represents the
          number of valid items in each list. When the list is nested within
          other lists, there will be extra dimensions for the parent list
          max lens.
      max_len: The max number of items allowed in each list.
  
  TODO(ekl): support conversion to tf.RaggedTensor.
code: def __str__(self):
      return repr(self)
  
file_path: ray/rllib/models/repeated_values.py
imports: from typing import List
  from ray.rllib.utils.annotations import PublicAPI
  from ray.rllib.utils.typing import TensorType, TensorStructType
label_desc: Use image node_id 5 for calling the RepeatedValues obj's underlying member method code with example usage: obj.__str__() and returns: repr