code: def get_placeholder(
      *,
      space: Optional[gym.Space] = None,
      value: Optional[Any] = None,
      name: Optional[str] = None,
      time_axis: bool = False,
      flatten: bool = True,
  ) -> "tf1.placeholder":
      """Returns a tf1.placeholder object given optional hints, such as a space.
  
      Note that the returned placeholder will always have a leading batch
      dimension (None).
  
      Args:
          space: An optional gym.Space to hint the shape and dtype of the
              placeholder.
          value: An optional value to hint the shape and dtype of the
              placeholder.
          name: An optional name for the placeholder.
          time_axis: Whether the placeholder should also receive a time
              dimension (None).
          flatten: Whether to flatten the given space into a plain Box space
              and then create the placeholder from the resulting space.
  
      Returns:
          The tf1 placeholder.
      """
      from ray.rllib.models.catalog import ModelCatalog
  
      if space is not None:
          if isinstance(space, (gym.spaces.Dict, gym.spaces.Tuple)):
              if flatten:
                  return ModelCatalog.get_action_placeholder(
                      space, None
                  )
              else:
                  return tree.map_structure_with_path(
                      lambda path, component: get_placeholder(
                          space=component,
                          name=name
                          + "."
                          + ".".join([str(p) for p in path]),
                      ),
                      get_base_struct_from_space(space),
                  )
          return tf1.placeholder(
              shape=(None,)
              + ((None,) if time_axis else ())
              + space.shape,
              dtype=tf.float32
              if space.dtype == np.float64
              else space.dtype,
              name=name,
          )
      else:
          assert value is not None
          shape = value.shape[1:]
          return tf1.placeholder(
              shape=(None,)
              + ((None,) if time_axis else ())
              + (
                  shape
                  if isinstance(shape, tuple)
                  else tuple(shape.as_list())
              ),
              dtype=tf.float32
              if value.dtype == np.float64
              else value.dtype,
              name=name,
          )
  
imports: import logging
  from typing import Any, Callable, List, Optional, Type, TYPE_CHECKING, Union
  import gymnasium
  import numpy
  import tree
  from gymnasium.spaces import Discrete, MultiDiscrete
  from ray.rllib.utils.annotations import PublicAPI, DeveloperAPI
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
  from ray.rllib.utils.typing import LocalOptimizer, ModelGradients, PartialAlgorithmConfigDict, SpaceStruct, TensorStructType, TensorType
label_desc: Use image node_id 5 for calling a global function with example usage: get_placeholder() and returns: tf1, tf1, ModelCatalog, tree