def prepare_task( config: PyTextConfig, dist_init_url: str = None, device_id: int = 0, rank: int = 0, world_size: int = 1, metric_channels: Optional[List[Channel]] = None, metadata: CommonMetadata = None, ) -> Task: if dist_init_url and world_size > 1: assert metadata is not None dist_init(rank, world_size, dist_init_url) print("\nParameters: {}\n".format(config)) _set_cuda(config.use_cuda_if_available, device_id, world_size) set_random_seeds(config.task.random_seed) if config.load_snapshot_path and os.path.isfile(config.load_snapshot_path): task = load(config.load_snapshot_path) else: task = create_task(config.task, metadata=metadata) for mc in metric_channels or []: task.metric_reporter.add_channel(mc) return task
def prepare_task( config: PyTextConfig, dist_init_url: str = None, device_id: int = 0, rank: int = 0, world_size: int = 1, summary_writer: Optional[SummaryWriter] = None, metadata: CommonMetadata = None, ) -> Task: if dist_init_url and world_size > 1: assert metadata is not None dist_init(rank, world_size, dist_init_url) print("\nParameters: {}\n".format(config)) _set_cuda(config.use_cuda_if_available, device_id, world_size) if config.load_snapshot_path and os.path.isfile(config.load_snapshot_path): task = load(config.load_snapshot_path) else: task = create_task(config.task, metadata=metadata) if summary_writer: task.metric_reporter.add_channel( TensorBoardChannel(summary_writer=summary_writer)) return task
def prepare_task( config: PyTextConfig, dist_init_url: str = None, device_id: int = 0, rank: int = 0, world_size: int = 1, ) -> Task: if dist_init_url and world_size > 1: dist_init(rank, world_size, dist_init_url) print("\nParameters: {}\n".format(config)) _set_cuda(config.use_cuda_if_available, device_id, world_size) if config.load_snapshot_path and os.path.isfile(config.load_snapshot_path): return load(config.load_snapshot_path) return create_task(config.task)