SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Act on deprecations in Accelerate no_trainer examples (#24053)

Browse Source 
Act on deprecation
This commit is contained in:
Zachary Mueller
2023-06-06 13:04:38 -04:00
committed by GitHub
parent ff4c0fc7d2
commit 072188d638
12 changed files with 14 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
examples/pytorch/image-classification/run_image_classification_no_trainer.py
View File

@@ -210,7 +210,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/image-pretraining/run_mim_no_trainer.py
View File

@@ -378,7 +378,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(
gradient_accumulation_steps=args.gradient_accumulation_steps,

2
examples/pytorch/language-modeling/run_clm_no_trainer.py
View File

@@ -261,7 +261,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/language-modeling/run_mlm_no_trainer.py
View File

@@ -270,7 +270,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/multiple-choice/run_swag_no_trainer.py
View File

@@ -288,7 +288,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py
View File

@@ -303,7 +303,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/question-answering/run_qa_no_trainer.py
View File

@@ -341,7 +341,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py
View File

@@ -330,7 +330,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)

2
examples/pytorch/summarization/run_summarization_no_trainer.py
View File

@@ -325,7 +325,7 @@ def main():
if args.with_tracking:
accelerator_log_kwargs["log_with"] = args.report_to
accelerator_log_kwargs["logging_dir"] = args.output_dir
accelerator_log_kwargs["project_dir"] = args.output_dir
accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps, **accelerator_log_kwargs)
if args.source_prefix is None and args.model_name_or_path in [

2
examples/pytorch/token-classification/run_ner_no_trainer.py
View File

@@ -271,7 +271,7 @@ def main():
# If we're using tracking, we also need to initialize it here and it will by default pick up all supported trackers
# in the environment
accelerator = (
Accelerator(log_with=args.report_to, logging_dir=args.output_dir) if args.with_tracking else Accelerator()
Accelerator(log_with=args.report_to, project_dir=args.output_dir) if args.with_tracking else Accelerator()
)
# Make one log on every process with the configuration for debugging.
logging.basicConfig(

2
examples/pytorch/translation/run_translation_no_trainer.py
View File

@@ -316,7 +316,7 @@ def main():
# If we're using tracking, we also need to initialize it here and it will by default pick up all supported trackers
# in the environment
accelerator = (
Accelerator(log_with=args.report_to, logging_dir=args.output_dir) if args.with_tracking else Accelerator()
Accelerator(log_with=args.report_to, project_dir=args.output_dir) if args.with_tracking else Accelerator()
)
# Make one log on every process with the configuration for debugging.

4
examples/research_projects/codeparrot/scripts/codeparrot_training.py
View File

@@ -7,6 +7,7 @@ from pathlib import Path
import datasets
import torch
from accelerate import Accelerator, DistributedType
from accelerate.utils import ProjectConfiguration
from arguments import TrainingArguments
from datasets import load_dataset
from huggingface_hub import Repository
@@ -195,7 +196,8 @@ parser = HfArgumentParser(TrainingArguments)
args = parser.parse_args()
# Accelerator
accelerator = Accelerator(log_with=["wandb", "tensorboard"], logging_dir=f"{args.save_dir}/log")
config = ProjectConfiguration(project_dir=args.save_dir, logging_dir="log")
accelerator = Accelerator(log_with=["wandb", "tensorboard"], project_config=config)
acc_state = {str(k): str(v) for k, v in accelerator.state.__dict__.items()}
args = Namespace(**vars(args), **acc_state)