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[LLM] relocate tensor_parallel_output to avoid conflict (#8419) #8533

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Jun 3, 2024
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[LLM] relocate tensor_parallel_output to avoid conflict (#8419) #8533

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5 changes: 5 additions & 0 deletions llm/finetune_generation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
import sys
from dataclasses import dataclass, field
from functools import partial
from typing import Optional

import paddle
from argument import (
Expand Down Expand Up @@ -66,6 +67,10 @@ class FinetuneArguments(TrainingArguments):
default=0,
metadata={"help": "The steps use to control the learing rate."},
)
tensor_parallel_output: Optional[bool] = field(
default=False,
metadata={"help": "whether to output logits in distributed status"},
)


def read_local_dataset(path):
Expand Down
2 changes: 1 addition & 1 deletion llm/utils.py
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Expand Up @@ -212,7 +212,7 @@ def prediction_step(
if isinstance(logits, (list, tuple)):
logits = logits[0]
# all gather logits when enabling tensor_parallel_output
if self.args.tensor_parallel_degree > 1 and self.args.tensor_parallel_output:
if self.args.tensor_parallel_degree > 1 and getattr(self.args, "tensor_parallel_output", False):
hcg = fleet.get_hybrid_communicate_group()
model_parallel_group = hcg.get_model_parallel_group()
gathered_logits = []
Expand Down
4 changes: 0 additions & 4 deletions paddlenlp/trainer/training_args.py
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Expand Up @@ -787,10 +787,6 @@ class TrainingArguments:
default=False,
metadata={"help": "whether to run distributed training in auto parallel mode"},
)
tensor_parallel_output: Optional[bool] = field(
default=False,
metadata={"help": "whether to output logits in distributed status"},
)
use_expert_parallel: Optional[bool] = field(
default=False,
metadata={"help": "Enable MoE (Mixture of Experts) expert parallel training"},
Expand Down
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