code: def istft(
      x,
      sequence_length,
      sequence_stride,
      fft_length,
      length=None,
      window="hann",
      center=True,
  ):
      x = _get_complex_tensor_from_tuple(x)
      dtype = np.real(x).dtype
  
      expected_output_len = fft_length + sequence_stride * (
          x.shape[-2] - 1
      )
      l_pad = (fft_length - sequence_length) // 2
      r_pad = fft_length - sequence_length - l_pad
  
      if window is not None:
          if isinstance(window, str):
              win = convert_to_tensor(
                  scipy.signal.get_window(window, sequence_length),
                  dtype=dtype,
              )
          else:
              win = convert_to_tensor(window, dtype=dtype)
          if len(win.shape) != 1 or win.shape[-1] != sequence_length:
              raise ValueError(
                  "The shape of `window` must be equal to [sequence_length]."
                  f"Received: window shape={win.shape}"
              )
          win = np.pad(win, [[l_pad, r_pad]])
      else:
          win = np.ones((sequence_length + l_pad + r_pad), dtype=dtype)
  
      x = scipy.signal.istft(
          x,
          fs=1.0,
          window=win,
          nperseg=(sequence_length + l_pad + r_pad),
          noverlap=(sequence_length + l_pad + r_pad - sequence_stride),
          nfft=fft_length,
          boundary=False,
          time_axis=-2,
          freq_axis=-1,
      )[-1]
  
      # scale
      x = x / win.sum() if window is not None else x / sequence_stride
  
      start = 0 if center is False else fft_length // 2
      if length is not None:
          end = start + length
      elif center is True:
          end = -(fft_length // 2)
      else:
          end = expected_output_len
      return x[..., start:end]
  
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 14 for calling a global function with example usage: istft(x, sequence_length, sequence_stride, fft_length, length, window, center) and returns: x