code: def default_make_latent(
      num_latents: int,
      latent_size: int,
      device: str | torch.device | None = None,
      non_blocking: bool = False,
      **kwargs: Any,
  ) -> torch.Tensor:
      return torch.randn(num_latents, latent_size).to(
          device=device, non_blocking=non_blocking, **kwargs
      )
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from collections.abc import Callable, Sequence
  from typing import TYPE_CHECKING, Any, cast
  import torch
  from monai.config import IgniteInfo
  from monai.transforms import apply_transform
  from monai.utils import ensure_tuple, min_version, optional_import
  from monai.utils.enums import CommonKeys, GanKeys
label_desc: Use image node_id 3 for calling a global function with example usage: default_make_latent(num_latents, latent_size, device, non_blocking) and returns: torch