def search(self, prefix="", suffix="") -> Tuple[List[str], List[datetime.datetime]]: paths = [] timestamps = [] timestamp_map = {} for key, ts in self._get_matching_s3_keys_generator(prefix, suffix): timestamp_map[key] = ts filtered_keys = util.remove_non_empty_directory_paths( list(timestamp_map.keys())) for key in filtered_keys: paths.append(key) timestamps.append(timestamp_map[key]) return paths, timestamps
def model_downloader( predictor_type: PredictorType, bucket_provider: str, bucket_name: str, model_name: str, model_version: str, model_path: str, temp_dir: str, model_dir: str, ) -> Optional[datetime.datetime]: """ Downloads model to disk. Validates the cloud model path and the downloaded model as well. Args: predictor_type: The predictor type as implemented by the API. bucket_provider: Provider for the bucket. Can be "s3" or "gs". bucket_name: Name of the bucket where the model is stored. model_name: Name of the model. Is part of the model's local path. model_version: Version of the model. Is part of the model's local path. model_path: Model prefix of the versioned model. temp_dir: Where to temporarily store the model for validation. model_dir: The top directory of where all models are stored locally. Returns: The model's timestamp. None if the model didn't pass the validation, if it doesn't exist or if there are not enough permissions. """ logger().info( f"downloading from bucket {bucket_name}/{model_path}, model {model_name} of version {model_version}, temporarily to {temp_dir} and then finally to {model_dir}" ) if bucket_provider == "s3": client = S3(bucket_name) if bucket_provider == "gs": client = GCS(bucket_name) # validate upstream cloud model sub_paths, ts = client.search(model_path) try: validate_model_paths(sub_paths, predictor_type, model_path) except CortexException: logger().info( f"failed validating model {model_name} of version {model_version}") return None # download model to temp dir temp_dest = os.path.join(temp_dir, model_name, model_version) try: client.download_dir_contents(model_path, temp_dest) except CortexException: logger().info( f"failed downloading model {model_name} of version {model_version} to temp dir {temp_dest}" ) shutil.rmtree(temp_dest) return None # validate model model_contents = glob.glob(temp_dest + "*/**", recursive=True) model_contents = util.remove_non_empty_directory_paths(model_contents) try: validate_model_paths(model_contents, predictor_type, temp_dest) except CortexException: logger().info( f"failed validating model {model_name} of version {model_version} from temp dir" ) shutil.rmtree(temp_dest) return None # move model to dest dir model_top_dir = os.path.join(model_dir, model_name) ondisk_model_version = os.path.join(model_top_dir, model_version) logger().info( f"moving model {model_name} of version {model_version} to final dir {ondisk_model_version}" ) if os.path.isdir(ondisk_model_version): shutil.rmtree(ondisk_model_version) shutil.move(temp_dest, ondisk_model_version) return max(ts)