text: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  # Copyright 1999-2018 Alibaba Group Holding Ltd.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import numpy as np
  
  from ... import opcodes as OperandDef
  from ..datasource import tensor as astensor
  from .core import TensorRealIFFTNMixin, validate_fftn, TensorRealFFTN
  
  
  class TensorIRFFT2(TensorRealFFTN, TensorRealIFFTNMixin):
      _op_type_ = OperandDef.IRFFT2
  
      def __init__(self, shape=None, axes=None, norm=None, dtype=None, **kw):
          super(TensorIRFFT2, self).__init__(_shape=shape, _axes=axes, _norm=norm,
                                             _dtype=dtype, **kw)
  
  
  def irfft2(a, s=None, axes=(-2, -1), norm=None):
      """
      Compute the 2-dimensional inverse FFT of a real array.
  
      Parameters
      ----------
      a : array_like
          The input tensor
      s : sequence of ints, optional
          Shape of the inverse FFT.
      axes : sequence of ints, optional
          The axes over which to compute the inverse fft.
          Default is the last two axes.
      norm : {None, "ortho"}, optional
          Normalization mode (see `mt.fft`). Default is None.
  
      Returns
      -------
      out : Tensor
          The result of the inverse real 2-D FFT.
  
      See Also
      --------
      irfftn : Compute the inverse of the N-dimensional FFT of real input.
  
      Notes
      -----
      This is really `irfftn` with different defaults.
      For more details see `irfftn`.
  
      """
      if len(axes) != 2:
          raise ValueError("axes length should be 2")
      a = astensor(a)
      axes = validate_fftn(a, s=s, axes=axes, norm=norm)
      op = TensorIRFFT2(shape=s, axes=axes, norm=norm, dtype=np.dtype(np.float_))
      return op(a)
  