def build_layers()

in mmf/models/mmf_transformer.py [0:0]

• 54 lines of code
• 4 McCabe index (conditional complexity)

    def build_layers(self):

        for modality in self.model_config.modalities:
            layer_norm_eps = getattr(
                modality, "layer_norm_eps", self.transformer_config.layer_norm_eps
            )
            if modality.type == "text":
                setattr(
                    self,
                    modality.key + "_embedding",
                    nn.Embedding(
                        self.transformer_config.vocab_size,
                        self.transformer_config.hidden_size,
                        padding_idx=self.transformer_config.pad_token_id,
                    ),
                )
            elif modality.type == "image":
                setattr(
                    self,
                    modality.key + "_embedding",
                    nn.Sequential(
                        nn.Linear(
                            modality.embedding_dim, self.transformer_config.hidden_size
                        ),
                        torch.nn.LayerNorm(
                            self.transformer_config.hidden_size, eps=layer_norm_eps
                        ),
                    ),
                )

            # Set the position embeddings
            position_dim = getattr(
                modality,
                "position_dim",
                self.transformer_config.max_position_embeddings,
            )
            setattr(
                self,
                modality.key + "_pos_embedding",
                nn.Embedding(position_dim, self.transformer_config.hidden_size),
            )

            # Layer norm
            setattr(
                self,
                modality.key + "_layer_norm",
                torch.nn.LayerNorm(
                    self.transformer_config.hidden_size, eps=layer_norm_eps
                ),
            )

            # Dropout
            hidden_dropout_prob = getattr(
                modality,
                "hidden_dropout_prob",
                self.transformer_config.hidden_dropout_prob,
            )
            setattr(self, modality.key + "_dropout", nn.Dropout(hidden_dropout_prob))

        self.token_type_embeddings = nn.Embedding(
            len(self.model_config.modalities), self.transformer_config.hidden_size
        )