Method init_from_cfg

inference/ace_plus_diffusers.py:28–39

(self, cfg)

            self.output = {k.lower(): v for k, v in cfg.OUTPUT.items()}

    def init_from_cfg(self, cfg):
        self.max_seq_len = cfg.get("MAX_SEQ_LEN", 4096)
        self.image_processor = ACEPlusImageProcessor(max_seq_len=self.max_seq_len)

        local_folder = FS.get_dir_to_local_dir(cfg.MODEL.PRETRAINED_MODEL)

        self.pipe = FluxFillPipeline.from_pretrained(local_folder, torch_dtype=torch.bfloat16).to(we.device_id)

        tokenizer_2 = T5TokenizerFast.from_pretrained(os.path.join(local_folder, "tokenizer_2"),
                                                      additional_special_tokens=["{image}"])
        self.pipe.tokenizer_2 = tokenizer_2
        self.load_default(cfg.DEFAULT_PARAS)

    def prepare_input(self,
                      image,