code: def __init__(
      self, num_actions: Optional[int] = None, recsim_obs: bool = False
  ):
      self.num_actions = num_actions
      self.recsim_obs = recsim_obs
  
imports: import inspect
  import logging
  from typing import Dict, Optional
  import gym
  import numpy
  import reagent.core.types
  import torch
  import torch.nn.functional
  from reagent.core.parameters import CONTINUOUS_TRAINING_ACTION_RANGE
  from reagent.gym.types import Trajectory
  from reagent.preprocessing.types import InputColumn
  from reagent.training.reagent_lightning_module import ReAgentLightningModule
  from reagent.training.utils import rescale_actions
label_desc: Use image node_id 1 to create a new PolicyGradientInputMaker object  with example: obj = PolicyGradientInputMaker(num_actions, recsim_obs)