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)
