def model_provider():
"""Build the model."""
args = get_args()
print_rank_0('building classification model for {} ...'.format(
args.task))
return Classification(num_classes=num_classes, num_tokentypes=2)
def model_provider(pre_process=True, post_process=True):
"""Build the model."""
args = get_args()
print_rank_0('building classification model for {} ...'.format(
args.task))
model = Classification(num_classes=num_classes,
num_tokentypes=2,
pre_process=pre_process,
post_process=post_process)
return model
def model_provider():
"""Build the model."""
args = get_args()
print_rank_0('building classification model for {} ...'.format(
args.task))
if mpu.get_pipeline_model_parallel_world_size() > 1:
# Determine model based on position of stage in pipeline.
if mpu.is_pipeline_first_stage():
model = ClassificationFirstStage(num_classes=num_classes,
num_tokentypes=2)
elif mpu.is_pipeline_last_stage():
model = ClassificationLastStage(num_classes=num_classes,
num_tokentypes=2)
else:
model = ClassificationIntermediateStage(
num_classes=num_classes, num_tokentypes=2)
else:
model = Classification(num_classes=num_classes, num_tokentypes=2)
return model
def model_provider():
return Classification(num_classes=num_classes, num_tokentypes=2)