code: def check_complex_input(input_shape):
      """Check the complex-valued shape for a linear layer.
  
      Arguments
      ---------
      input_shape : tuple
          Expected shape of the input.
      """
      if len(input_shape) not in {2, 3}:
          raise Exception(
              "Complex linear accepts only input of dimension 2 or 3."
              " input.dim = " + str(input.dim())
          )
  
      nb_hidden = input_shape[-1]
  
      if nb_hidden % 1 != 0:
          raise Exception(
              "Complex Tensors must have an even number of hidden dimensions."
              " input.size()[1] = " + str(nb_hidden)
          )
  
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 1 for calling a global function with example usage: check_complex_input(input_shape) without return types