code: def _ifft2_tf(a, s=None, axes=(-2, -1), norm=None):
      if axes != (-2, -1):
          raise ValueError(
              "TensorFlow does not support passing axes; the ifft "
              "will always be performed over the inner-most 2 dimensions."
          )
  
      if norm is not None:
          raise ValueError(
              "TensorFlow does not support the 'norm' keyword argument."
          )
      if s is not None:
          raise ValueError(
              "TensorFlow does not support the 's' keyword argument."
          )
  
      # TensorFlow only supports FFT of complex tensors
      if a.dtype not in [_i("tf").complex64, _i("tf").complex128]:
          if a.dtype is _i("tf").float64:
              a = _i("tf").cast(a, dtype=_i("tf").complex128)
          else:
              a = _i("tf").cast(a, dtype=_i("tf").complex64)
  
      return _i("tf").signal.ifft2d(input=a)
  
imports: from importlib import import_module
  import autoray
  import numpy
  import semantic_version
  from scipy.linalg import block_diag
  from .utils import get_deep_interface
label_desc: Use image node_id 13 for calling a global function with example usage: _ifft2_tf(a, s, axes, norm) and returns: _i