5dba00c0cb0ae461cc98c5ad98c9ef87624c5ca1,baseline/tf/classify/model.py,FineTuneModelClassifier,init_embed,#FineTuneModelClassifier#Any#,536

Before Change

        :return: The output of the embedding stack followed by its reduction.  This will typically be an output
          with an additional dimension which is the hidden representation of the input
        
        return EmbeddingsStack(embeddings, reduction=kwargs.get("embeddings_reduction", "concat"))

    def init_stacked(self, input_dim: int, **kwargs) -> BaseLayer:
        Produce a stacking operation that will be used in the model

After Change

        :return: The output of the embedding stack followed by its reduction.  This will typically be an output
          with an additional dimension which is the hidden representation of the input
        
        reduction = kwargs.get("embeddings_reduction", "concat")
        embeddings_dropout = float(kwargs.get("embeddings_dropout", 0.0))
        name = kwargs.get("embeddings_name")
        return EmbeddingsStack(embeddings, embeddings_dropout, reduction=reduction, name=name)

    def init_stacked(self, input_dim: int, **kwargs) -> BaseLayer:
        Produce a stacking operation that will be used in the model

Instances