code: def split_placeholders(self, placeholder, split):
      inner_placeholder_list = tf.split(
          placeholder, tf.math.reduce_sum(split, axis=1), axis=0
      )
      placeholder_list = []
      for index, split_placeholder in enumerate(inner_placeholder_list):
          placeholder_list.append(
              tf.split(split_placeholder, split[index], axis=0)
          )
      return placeholder_list
  
imports: import logging
  from typing import Dict, List, Type, Union
  from ray.rllib.algorithms.ppo.ppo_tf_policy import validate_config
  from ray.rllib.evaluation.postprocessing import Postprocessing, compute_gae_for_sample_batch
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.tf_action_dist import TFActionDistribution
  from ray.rllib.models.utils import get_activation_fn
  from ray.rllib.policy.dynamic_tf_policy_v2 import DynamicTFPolicyV2
  from ray.rllib.policy.eager_tf_policy_v2 import EagerTFPolicyV2
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.tf_mixins import LocalOptimizer, ModelGradients, ValueNetworkMixin, compute_gradients
  from ray.rllib.utils import try_import_tf
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.typing import TensorType
label_desc: Use image node_id 4 for calling the MAMLLoss obj's underlying member method code with example usage: obj.split_placeholders(placeholder, split) and returns: placeholder_list