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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_classifier(output_nonlin=nn.Softmax(dim=-1), **kwargs):
 """Return a multi-layer perceptron to be used with NeuralNetClassifier. 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, output_nonlin=output_nonlin, **kwargs)