code: def get_conjugate(input, input_type="linear", channels_axis=1):
      """Returns the conjugate (z = r - xi) of the input complex numbers.
  
      Arguments
      ---------
      input : torch.Tensor
          Input tensor
      input_type : str,
          (convolution, linear) (default "linear")
      channels_axis : int.
          Default 1.
      """
      input_imag = get_imag(input, input_type, channels_axis)
      input_real = get_real(input, input_type, channels_axis)
      if input_type == "linear":
          return torch.cat([input_real, -input_imag], dim=-1)
      elif input_type == "convolution":
          return torch.cat([input_real, -input_imag], dim=channels_axis)
  
file_path: speechbrain/speechbrain/nnet/complex_networks/c_ops.py
imports: import torch
  import torch.nn.functional
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: get_conjugate(input, input_type, channels_axis) and returns: torch, torch