cc07095b2f72ff3ba5e5d76900ff17111cf9f177,batchflow/models/tf/unet.py,UNet,build_config,#UNet#Any#,58

Before Change

        if self.config.get("body/filters") is None:
            config["body/filters"] = (2 ** np.arange(config["body/num_blocks"]) * 64).tolist()
        if config.get("head/num_classes") is None:
            config["head/num_classes"] = self.num_classes("targets")
        return config

    @classmethod
    def body(cls, inputs, name="body", **kwargs):

After Change

            config["body/encoder/blocks/filters"] = [128*2**i for i in range(num_stages)]

        if config.get("body/decoder/blocks/filters") is None:
            config["body/decoder/blocks/filters"] = list(reversed([64*2**i for i in range(num_stages)]))

        if config.get("body/decoder/upsample/filters") is None:
            config["body/decoder/upsample/filters"] = list(reversed([128*2**i for i in range(num_stages)]))

Instances