f1a7ea62b17afd9880e83aae0ff6f3996bc1e71d,dataset/models/tf/refinenet.py,RefineNet,body,#Any#Any#Any#,49

Before Change

        with tf.variable_scope(name):
            x = inputs
            encoder_outputs = [x]
            for i, ifilters in enumerate(filters):
                x = cls.encoder_block(x, ifilters, name="downsampling-"+str(i), **kwargs)
                encoder_outputs.append(x)

            for i, ifilters in enumerate(filters[::-1]):
                x = cls.decoder_block((x, encoder_outputs[-i-2]), ifilters//2, name="upsampling-"+str(i), **kwargs)

        return x

After Change

        tf.Tensor
        
        kwargs = cls.fill_params("body", **kwargs)
        encoder = kwargs.pop("encoder")
        filters = kwargs.pop("filters")

        with tf.variable_scope(name):
            encoder_outputs = cls.make_encoder(inputs, **encoder, **kwargs)

            x = None
            for i, tensor in enumerate(encoder_outputs):
                decoder_inputs = encoder_outputs[-i-1] if x is None else (encoder_outputs[-i-1], x)

Instances