def put_model()

in eland/ml/pytorch/_pytorch_model.py [0:0]

• 20 lines of code
• 4 McCabe index (conditional complexity)

    def put_model(self, model_path: str, chunk_size: int = DEFAULT_CHUNK_SIZE) -> None:
        model_size = os.stat(model_path).st_size
        total_parts = math.ceil(model_size / chunk_size)

        def model_file_chunk_generator() -> Iterable[str]:
            with open(model_path, "rb") as f:
                while True:
                    data = f.read(chunk_size)
                    if not data:
                        break
                    yield base64.b64encode(data).decode()

        for i, data in tqdm(
            enumerate(model_file_chunk_generator()), unit=" parts", total=total_parts
        ):
            self._client.ml.put_trained_model_definition_part(
                model_id=self.model_id,
                part=i,
                total_definition_length=model_size,
                total_parts=total_parts,
                definition=data,
            )