class_docstr: Dialect op for IRFFT. Computes the inverse of RFFT. The input is interpreted as a one-sided
  Hermitian signal in the Fourier domain, as produced by rfft(). By the Hermitian property, the
  output will be real-valued.
  
  Parameters
  ----------
  See the ``complex_ifft`` op for details.
  
  Returns
  -------
  tensor<\*V, fp32>
      * The shape is the same as the input except for the ``dim``:
          * If ``n`` is None, the shape at the `dim` is ``V[dim] = 2 * (D[dim] - 1)``.
          * If ``n`` is specified, the shape at the `dim` is ``V[dim]=n``.
  
  Attributes
  ----------
  T: complex64
  
  References
  ----------
  See `torch.fft.irfft <https://pytorch.org/docs/stable/generated/torch.fft.irfft.html>`_.
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code: def default_inputs(self):
      return DefaultInputs(
          n=None,
          dim=-1,
          norm="backward",
      )
  
imports: from typing import Optional, Tuple
  import numpy
  from coremltools.converters.mil.mil import Operation, types
  from coremltools.converters.mil.mil.input_type import DefaultInputs, InputSpec, TensorInputType
  from coremltools.converters.mil.mil.ops.registry import SSAOpRegistry
  from coremltools.converters.mil.mil.types.symbolic import any_symbolic, is_symbolic
  from coremltools.converters.mil.mil.types.type_mapping import infer_complex_dtype, infer_fp_dtype_from_complex
  from coremltools.converters.mil.mil.var import ComplexVar, Var
label_desc: Use image node_id 1 for calling the complex_irfft obj's underlying member method code with example usage: obj.default_inputs() and returns: DefaultInputs