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[fix] fix comment in llama & benchmark

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duanjunwen 2024-10-29 07:35:50 +00:00
parent fa3ccda8ee
commit 982e4ee1f8
2 changed files with 4 additions and 7 deletions
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5
colossalai/shardformer/policies/llama.py
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@ -414,10 +414,7 @@ class LlamaForSequenceClassificationPolicy(LlamaPolicy):
from transformers import LlamaForSequenceClassification from transformers import LlamaForSequenceClassification
policy = super().module_policy() policy = super().module_policy()
if self.pipeline_stage_manager: use_zbv = self.pipeline_stage_manager is not None and self.pipeline_stage_manager.use_zbv
use_zbv = self.pipeline_stage_manager.use_zbv
else:
use_zbv = False
if self.shard_config.enable_tensor_parallelism: if self.shard_config.enable_tensor_parallelism:
# add a new item for sequence classification # add a new item for sequence classification

6
examples/language/llama/benchmark.py
View File

@ -108,6 +108,7 @@ def main():
parser.add_argument("--no_cache", action="store_true") parser.add_argument("--no_cache", action="store_true")
parser.add_argument("--use_fp8_comm", action="store_true", default=False, help="for using fp8 during communication") parser.add_argument("--use_fp8_comm", action="store_true", default=False, help="for using fp8 during communication")
parser.add_argument("--use_fp8", action="store_true", default=False, help="for using fp8 linear") parser.add_argument("--use_fp8", action="store_true", default=False, help="for using fp8 linear")
parser.add_argument("--overlap_p2p", action="store_true", default=True, help="for using overlap p2p")
parser.add_argument("--overlap_allgather", action="store_true") parser.add_argument("--overlap_allgather", action="store_true")
parser.add_argument( parser.add_argument(
"--sp_mode", "--sp_mode",
@ -256,7 +257,6 @@ def main():
use_fp8=args.use_fp8, use_fp8=args.use_fp8,
fp8_communication=args.use_fp8_comm, fp8_communication=args.use_fp8_comm,
scheduler_nodes=scheduler_nodes, scheduler_nodes=scheduler_nodes,
make_vocab_size_divisible_by=1,
**hybrid_kwargs, **hybrid_kwargs,
) )
elif args.plugin == "3d_cpu": elif args.plugin == "3d_cpu":
@ -272,7 +272,7 @@ def main():
microbatch_size=args.mbs, microbatch_size=args.mbs,
initial_scale=2**8, initial_scale=2**8,
precision="bf16", precision="bf16",
overlap_p2p=True, overlap_p2p=args.overlap_p2p,
use_fp8=args.use_fp8, use_fp8=args.use_fp8,
fp8_communication=args.use_fp8_comm, fp8_communication=args.use_fp8_comm,
) )
@ -338,7 +338,7 @@ def main():
torch.set_default_dtype(torch.bfloat16) torch.set_default_dtype(torch.bfloat16)
model, optimizer, _, dataloader, _ = booster.boost(model, optimizer, dataloader=dataloader) model, optimizer, _, dataloader, _ = booster.boost(model, optimizer, dataloader=dataloader)
# torch.set_default_dtype(torch.float) torch.set_default_dtype(torch.float)
coordinator.print_on_master( coordinator.print_on_master(
f"Booster init max CUDA memory: {get_accelerator().max_memory_allocated()/1024**2:.2f} MB" f"Booster init max CUDA memory: {get_accelerator().max_memory_allocated()/1024**2:.2f} MB"
) )