code: def configure_dims(params):
      env = cached_make_env(params["make_env"])
      env.reset()
      obs, _, _, info = env.step(env.action_space.sample())
  
      dims = {
          "o": obs["observation"].shape[0],
          "u": env.action_space.shape[0],
          "g": obs["desired_goal"].shape[0],
      }
      for key, value in info.items():
          value = np.array(value)
          if value.ndim == 0:
              value = value.reshape(1)
          dims["info_{}".format(key)] = value.shape[0]
      return dims
  
file_path: baselines/baselines/her/experiment/config.py
imports: import os
  import numpy
  import gym
  from baselines import logger
  from baselines.her.ddpg import DDPG
  from baselines.her.her_sampler import make_sample_her_transitions
  from baselines.bench.monitor import Monitor
label_desc: Use image node_id 7 for calling a global function with example usage: configure_dims(params) and returns: dims