2fd10474faf8b1c519d00d1215956f417cea01ed,batchflow/models/tf/encoder_decoder.py,EncoderDecoder,body,#Any#Any#Any#,133

Before Change

            encoder_outputs = cls.encoder(inputs, **encoder, **kwargs)

            // Bottleneck: working with compressed representation
            x = cls.embedding(encoder_outputs[-1], **embedding, **kwargs)
            encoder_outputs.append(x)

            // Decoder: transition up
            x = cls.decoder(encoder_outputs, **decoder, **kwargs)

After Change

        kwargs = cls.fill_params("body", **kwargs)
        encoder = kwargs.pop("encoder")
        embedding_common = kwargs.pop("embedding_common")
        embedding_order = kwargs.pop("embedding_order") or [name for name in kwargs
                                                            if "embedding" in name]
        decoder = kwargs.pop("decoder")

        with tf.variable_scope(name):
            // Encoder: transition down
            encoder_args = {**kwargs, **encoder}
            encoder_outputs = cls.encoder(inputs, name="encoder", **encoder_args)
            x = encoder_outputs[-1]

            // Bottleneck: working with compressed representation via multiple steps of processing
            for embedding_name in embedding_order:
                embedding_args = kwargs.pop(embedding_name)
                if embedding_args:
                    embedding_args = {**kwargs, **embedding_common, **embedding_args}
                    x = cls.embedding(x, name=embedding_name, **embedding_args)

            encoder_outputs.append(x)

            // Decoder: transition up
            decoder_args = {**kwargs, **decoder}

Instances