code: def make_binary_classifier(squeeze_output=True, **kwargs):
      """Return a multi-layer perceptron to be used with
      NeuralNetBinaryClassifier.
  
      Parameters
      ----------
      input_units : int (default=20)
        Number of input units.
  
      output_units : int (default=2)
        Number of output units.
  
      hidden_units : int (default=10)
        Number of units in hidden layers.
  
      num_hidden : int (default=1)
        Number of hidden layers.
  
      nonlin : torch.nn.Module instance (default=torch.nn.ReLU())
        Non-linearity to apply after hidden layers.
  
      dropout : float (default=0)
        Dropout rate. Dropout is applied between layers.
  
      """
      return partial(MLPModule, squeeze_output=squeeze_output, **kwargs)
  
file_path: skorch/skorch/toy.py
imports: from functools import partial
  from torch import nn
label_desc: Use image node_id 2 for calling a global function with example usage: make_binary_classifier(squeeze_output) and returns: partial