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Disable nvfuser for gpt #3845

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Mar 16, 2022
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Original file line number Diff line number Diff line change
Expand Up @@ -106,7 +106,7 @@ model:
splits_string: 900,50,50
seq_length: ${model.encoder_seq_length}
skip_warmup: True
num_workers: 0
num_workers: 2
dataloader_type: single # cyclic
reset_position_ids: False # Reset position ids after end-of-document token
reset_attention_mask: False # Reset attention mask after end-of-document token
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Original file line number Diff line number Diff line change
Expand Up @@ -106,7 +106,7 @@ def __init__(self, cfg: DictConfig, trainer: Trainer):
self._validate_trainer()

# used in NVIDIA NGC PyTorch containers
self._enable_nvidia_optimizations()
# self._enable_nvidia_optimizations()

if self.cfg.get('use_cpu_initialization', False) is False:
torch.cuda.set_device(trainer.local_rank)
Expand Down Expand Up @@ -558,9 +558,8 @@ def build_train_valid_test_datasets(self):
return

logging.info('Building GPT datasets.')
global_batch_size = self.trainer.world_size * self.cfg.micro_batch_size / self.cfg.tensor_model_parallel_size
# Compute trianing micro-batch steps: total_global_batch_steps x grad_acumms_per_global_batch
max_train_steps = self.trainer.max_steps * self.trainer.accumulate_grad_batches
global_batch_size = self.cfg.global_batch_size
max_train_steps = self.trainer.max_steps
eval_iters = (max_train_steps // self.trainer.val_check_interval + 1) * self.trainer.limit_val_batches
test_iters = self.trainer.limit_test_batches

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