class_docstr: Agents than plays through a torch neural network
class_docstr_tok: ["Agents","than","plays","through","a","torch","neural","network"]
code: def load_state_dict(
      self, state_dict: tp.Dict[str, np.ndarray]
  ) -> None:
      # pylint: disable=not-callable
      self.module.load_state_dict(
          {
              x: torch.tensor(y.astype(np.float32))
              for x, y in state_dict.items()
          }
      )
  
imports: import warnings
  import operator
  import copy
  import typing
  import gym
  import numpy
  from nevergrad.common.tools import pytorch_import_fix
  from nevergrad.parametrization import parameter
  from ..base import ExperimentFunction
  from .None import base
  from .None import envs
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.utils.data import WeightedRandomSampler
label_desc: Use image node_id 5 for calling the TorchAgent obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types