linear.py 文件源码

def __init__(self, input_dimensionality, output_dimensionality, scaler='default'):
        """
        Creats a Linear SEF object
        :param input_dimensionality: dimensionality of the input space
        :param output_dimensionality: dimensionality of the target space
        :param learning_rate: learning rate to be used for the optimization
        :param regularizer_weight: the weight of the regularizer
        :param scaler:
        """

        # Call base constructor
        SEF_Base.__init__(self, input_dimensionality, output_dimensionality, scaler)

        # Projection weights variables
        W = np.float32(0.1 * np.random.randn(self.input_dimensionality, output_dimensionality))
        self.W = Variable(torch.from_numpy(W), requires_grad=True)
        self.trainable_params = [self.W]