code: def _parse_gpu_config(gpu_memory_config: Text) -> Dict[int, int]:
      """Parse GPU configuration variable from a string to a dict.
  
      Args:
          gpu_memory_config: String containing the configuration for GPU usage.
  
      Returns:
          Parsed configuration as a dictionary with GPU IDs as keys and requested memory
          as the value.
      """
      # gpu_config is of format "gpu_id_1:gpu_id_1_memory, gpu_id_2: gpu_id_2_memory"
      # Parse it and store in a dictionary
      parsed_gpu_config: Dict[int, int] = {}
  
      try:
          for instance in gpu_memory_config.split(","):
              instance_gpu_id, instance_gpu_mem = instance.split(":")
              parsed_instance_gpu_id = int(instance_gpu_id)
              parsed_instance_gpu_mem = int(instance_gpu_mem)
  
              parsed_gpu_config[
                  parsed_instance_gpu_id
              ] = parsed_instance_gpu_mem
      except ValueError:
          # Helper explanation of where the error comes from
          raise ValueError(
              f"Error parsing GPU configuration. Please cross-check the format of "
              f"'{ENV_GPU_CONFIG}' at https://rasa.com/docs/rasa/tuning-your-model"
              f"#restricting-absolute-gpu-memory-available ."
          )
  
      return parsed_gpu_config
  
file_path: rasa/rasa/utils/tensorflow/environment.py
imports: import logging
  import os
  from typing import Text, Dict
  import typing
  import rasa.shared.utils.io
  from rasa.constants import ENV_GPU_CONFIG, ENV_CPU_INTER_OP_CONFIG, ENV_CPU_INTRA_OP_CONFIG
  from rasa.utils.tensorflow.constants import TF_DETERMINISTIC_OPS
  from rasa.shared.utils import io
label_desc: Use image node_id 3 for calling a global function with example usage: _parse_gpu_config(gpu_memory_config) and returns: parsed_gpu_config