def forward(self, X):
return self.sparse_linear(X[<NUM_LIT:0>], X[<NUM_LIT:1>])<EOL>
Run forward pass.

:param X: The input (batch) of the model contains features and feature weights.
:type X: For features: torch.Tensor of shape (batch_size, sparse_feature_size).
    For feature weights: torch.Tensor of shape
    (batch_size, sparse_feature_size).
:return: The output of sparse Logistic Regression layer.
:rtype: torch.Tensor of shape (batch_size, num_classes)