def initialize()

in templates/inference-endpoints/postprocessing/1/model.py [0:0]

• 7 lines of code
• 1 McCabe index (conditional complexity)

    def initialize(self, args):
        """`initialize` is called only once when the model is being loaded.
        Implementing `initialize` function is optional. This function allows
        the model to initialize any state associated with this model.
        Parameters
        ----------
        args : dict
          Both keys and values are strings. The dictionary keys and values are:
          * model_config: A JSON string containing the model configuration
          * model_instance_kind: A string containing model instance kind
          * model_instance_device_id: A string containing model instance device ID
          * model_repository: Model repository path
          * model_version: Model version
          * model_name: Model name
        """
        # Parse model configs
        model_config = json.loads(args['model_config'])
        tokenizer_dir = model_config['parameters']['tokenizer_dir']['string_value']

        self.tokenizer = AutoTokenizer.from_pretrained(tokenizer_dir, padding_side='left')
        self.tokenizer.pad_token = self.tokenizer.eos_token

        # Parse model output configs
        output_config = pb_utils.get_output_config_by_name(model_config, "OUTPUT")

        # Convert Triton types to numpy types
        self.output_dtype = pb_utils.triton_string_to_numpy(output_config['data_type'])