code: def get_num_output_padded_to_fit_input(
      num_input: int,
      window_length_in_samp: int,
      window_shift_in_samp: int,
  ) -> int:
      num_output_valid = torch.tensor(
          (num_input - window_length_in_samp) / window_shift_in_samp + 1
      )
      return int(torch.ceil(num_output_valid))
  
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 18 for calling a global function with example usage: get_num_output_padded_to_fit_input(num_input, window_length_in_samp, window_shift_in_samp) and returns: int