code: def irfft(x, fft_length=None):
      complex_input = _get_complex_tensor_from_tuple(x)
      # numpy always outputs float64, so we need to recast the dtype
      return np.fft.irfft(
          complex_input, n=fft_length, axis=-1, norm="backward"
      ).astype(x[0].dtype)
  
imports: import numpy
  from keras.backend import standardize_dtype
  from keras.backend.jax.math import fft
  from keras.backend.jax.math import fft2
  from keras.backend.numpy.core import convert_to_tensor
  from keras.utils.module_utils import scipy
label_desc: Use image node_id 12 for calling a global function with example usage: irfft(x, fft_length) and returns: np