def determine_decode_and_evaluate_context(args: argparse.Namespace,
exit_stack: ExitStack,
train_context: List[mx.Context]) -> Tuple[int, Optional[mx.Context]]:
"""
Determine the number of sentences to decode and the context we should run on (CPU or GPU).
:param args: Arguments as returned by argparse.
:param exit_stack: An ExitStack from contextlib.
:param train_context: Context for training.
:return: The number of sentences to decode and a list with the context(s) to run on.
"""
num_to_decode = args.decode_and_evaluate
if args.optimized_metric == C.BLEU and num_to_decode == 0:
logger.info("You chose BLEU as the optimized metric, will turn on BLEU monitoring during training. "
"To control how many validation sentences are used for calculating bleu use "
"the --decode-and-evaluate argument.")
num_to_decode = -1
if num_to_decode == 0:
return 0, None
if args.use_cpu or args.decode_and_evaluate_use_cpu:
context = mx.cpu()
elif args.decode_and_evaluate_device_id is not None:
# decode device is defined from the commandline
num_gpus = utils.get_num_gpus()
check_condition(num_gpus >= 1,
"No GPUs found, consider running on the CPU with --use-cpu "
"(note: check depends on nvidia-smi and this could also mean that the nvidia-smi "
"binary isn't on the path).")
if args.disable_device_locking:
context = utils.expand_requested_device_ids([args.decode_and_evaluate_device_id])
else:
context = exit_stack.enter_context(utils.acquire_gpus([args.decode_and_evaluate_device_id],
lock_dir=args.lock_dir))
context = mx.gpu(context[0])
else:
# default decode context is the last training device
context = train_context[-1]
logger.info("Decode and Evaluate Device(s): %s", context)
return num_to_decode, context
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