code: def get_window(
      window_type: str,
      window_length_in_samp: int,
      device: Optional[torch.device] = None,
  ) -> torch.Tensor:
      # Increase precision in order to achieve parity with scipy.signal.windows.get_window implementation
      if window_type == "bartlett":
          return torch.bartlett_window(
              window_length_in_samp,
              periodic=False,
              dtype=torch.float64,
              device=device,
          ).to(torch.float32)
      elif window_type == "blackman":
          return torch.blackman_window(
              window_length_in_samp,
              periodic=False,
              dtype=torch.float64,
              device=device,
          ).to(torch.float32)
      elif window_type == "hamming":
          return torch.hamming_window(
              window_length_in_samp,
              periodic=False,
              dtype=torch.float64,
              device=device,
          ).to(torch.float32)
      elif window_type == "hann":
          return torch.hann_window(
              window_length_in_samp,
              periodic=False,
              dtype=torch.float64,
              device=device,
          ).to(torch.float32)
      else:
          raise ValueError(f"Unknown window type: {window_type}")
  
imports: import functools
  import logging
  from io import BytesIO
  from typing import Any, List, Optional, Union
  import torch
  import torch.nn.functional
  import torchaudio
  from packaging import version
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import DEFAULT_AUDIO_TENSOR_LENGTH
  from ludwig.utils.types import TorchAudioTuple
label_desc: Use image node_id 19 for calling a global function with example usage: get_window(window_type, window_length_in_samp, device) and returns: torch, torch, torch, torch