Act on deprecations in Accelerate no_trainer examples (#24053)

Act on deprecation

examples/pytorch/image-classification/run_image_classification_no_trainer.py

@@ -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)
 

examples/pytorch/image-pretraining/run_mim_no_trainer.py

@@ -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,

examples/pytorch/language-modeling/run_clm_no_trainer.py

@@ -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)
 

examples/pytorch/language-modeling/run_mlm_no_trainer.py

@@ -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)
 

examples/pytorch/multiple-choice/run_swag_no_trainer.py

@@ -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)
 

examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py

@@ -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)
 

examples/pytorch/question-answering/run_qa_no_trainer.py

@@ -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)
 

examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py

@@ -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)
 

examples/pytorch/summarization/run_summarization_no_trainer.py

@@ -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 [

examples/pytorch/token-classification/run_ner_no_trainer.py

@@ -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(

examples/pytorch/translation/run_translation_no_trainer.py

@@ -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.

examples/research_projects/codeparrot/scripts/codeparrot_training.py

@@ -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)