code: def irfft(x, fft_length=None):
      complex_input = _get_complex_tensor_from_tuple(x)
      return torch.fft.irfft(
          complex_input, n=fft_length, dim=-1, norm="backward"
      )
  
imports: import math
  import torch
  from keras.backend import standardize_dtype
  from keras.backend.torch.core import convert_to_tensor
  from keras.backend.torch.core import get_device
  from keras.backend.torch.numpy import pad
label_desc: Use image node_id 13 for calling a global function with example usage: irfft(x, fft_length) and returns: torch