84d517d540204dcaa20237dc05bdd4a63a958923,reagent/models/embedding_bag_concat.py,EmbeddingBagConcat,input_prototype,#EmbeddingBagConcat#,48

Before Change

        return self._output_dim

    def input_prototype(self):
        return rlt.PreprocessedState(
            state=rlt.PreprocessedFeatureVector(
                float_features=torch.randn(1, self.state_dim),
                id_list_features={
                    k: (
                        torch.zeros(1, dtype=torch.long),
                        torch.ones(1, dtype=torch.long),
                    )
                    for k in self.embedding_bags
                },
            )
        )

    def forward(self, input: rlt.PreprocessedState):
        embeddings = [
            m(

After Change

        return self._output_dim

    def input_prototype(self):
        return rlt.FeatureData(
            float_features=torch.randn(1, self.state_dim),
            id_list_features={
                k: (torch.zeros(1, dtype=torch.long), torch.ones(1, dtype=torch.long))
                for k in self.embedding_bags
            },
        )

    def forward(self, state: rlt.FeatureData):
        embeddings = [
            m(state.id_list_features[name][1], state.id_list_features[name][0])

Instances