code: def generate_cf(
      Z: torch.Tensor,
      Y_m: torch.Tensor,
      Y_t: torch.Tensor,
      C: Optional[torch.Tensor],
      encoder: nn.Module,
      decoder: nn.Module,
      actor: nn.Module,
      device: torch.device,
      **kwargs,
  ) -> torch.Tensor:
      """
      Generates counterfactual embedding.
  
      Parameters
      ----------
      Z
          Input embedding tensor.
      Y_m
          Input classification label.
      Y_t
          Target counterfactual classification label.
      C
          Conditional tensor.
      encoder
          Pretrained encoder network.
      decoder
          Pretrained decoder network.
      actor
          Actor network. The model generates the counterfactual embedding.
      device
          Device object to be used.
  
      Returns
      -------
      Z_cf
          Counterfactual embedding.
      """
      # Set autoencoder and actor to evaluation mode.
      encoder.eval()
      decoder.eval()
      actor.eval()
  
      # Send labels, targets and conditional vector to device.
      Y_m = Y_m.float().to(device)
      Y_t = Y_t.float().to(device)
      C = C.float().to(device) if (C is not None) else None
  
      # Concatenate Z_mean, Y_m_ohe, Y_t_ohe to create the input representation for the projection network (actor).
      state = [Z, Y_m, Y_t] + ([C] if (C is not None) else [])
      state = torch.cat(state, dim=1)  # type: ignore
  
      # Pass the new input to the projection network (actor) to get the counterfactual embedding
      Z_cf = actor(state)
      return Z_cf
  
imports: import os
  import random
  from typing import List, Dict, Callable, Union, Optional, TYPE_CHECKING
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader, Dataset
  from alibi.explainers.backends.cfrl_base import CounterfactualRLDataset
  from alibi.models.pytorch.actor_critic import Actor, Critic
label_desc: Use image node_id 10 for calling a global function with example usage: generate_cf(Z, Y_m, Y_t, C, encoder, decoder, actor, device) and returns: Z_cf