b53df9d822949027e32e926cb833e05bd381ebcf,pytext/torchscript/module.py,PyTextLayerModuleWithDense,forward,#PyTextLayerModuleWithDense#Any#Any#,1178

Before Change

        texts: List[str],
        dense_feat: List[List[float]],
    ):
        logits = super().forward(texts, dense_feat)
        return self.output_layer(logits)

After Change

        dense_tensor = torch.tensor(dense_feat, dtype=torch.float)
        if self.tensorizer.device != "":
            dense_tensor = dense_tensor.to(self.tensorizer.device)
        logits = self.model(input_tensors, dense_tensor)
        // </>logits = super().forward(texts, dense_feat)
        return self.output_layer(logits)

Instances