Try to understand and apply Sylvain's comments (#8458)

examples/adversarial/run_hans.py

@@ -23,6 +23,7 @@ from typing import Dict, List, Optional
 import numpy as np
 import torch
 
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForSequenceClassification,
@@ -33,6 +34,7 @@ from transformers import (
     default_data_collator,
     set_seed,
 )
+from transformers.trainer_utils import is_main_process
 from utils_hans import HansDataset, InputFeatures, hans_processors, hans_tasks_num_labels
 
 
@@ -124,6 +126,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed

examples/bert-loses-patience/run_glue_with_pabee.py

@@ -29,6 +29,7 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, Tenso
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from pabee.modeling_pabee_albert import AlbertForSequenceClassificationWithPabee
 from pabee.modeling_pabee_bert import BertForSequenceClassificationWithPabee
 from transformers import (
@@ -44,6 +45,7 @@ from transformers import glue_compute_metrics as compute_metrics
 from transformers import glue_convert_examples_to_features as convert_examples_to_features
 from transformers import glue_output_modes as output_modes
 from transformers import glue_processors as processors
+from transformers.trainer_utils import is_main_process
 
 
 try:
@@ -630,7 +632,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
-
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     # Set seed
     set_seed(args)
 

examples/bertology/run_bertology.py

@@ -30,6 +30,7 @@ from torch.utils.data import DataLoader, SequentialSampler, Subset
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm
 
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForSequenceClassification,
@@ -41,6 +42,7 @@ from transformers import (
     glue_processors,
     set_seed,
 )
+from transformers.trainer_utils import is_main_process
 
 
 logger = logging.getLogger(__name__)
@@ -368,6 +370,11 @@ def main():
     # Setup logging
     logging.basicConfig(level=logging.INFO if args.local_rank in [-1, 0] else logging.WARN)
     logger.info("device: {} n_gpu: {}, distributed: {}".format(args.device, args.n_gpu, bool(args.local_rank != -1)))
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
 
     # Set seeds
     set_seed(args.seed)

examples/contrib/legacy/run_language_modeling.py

@@ -29,6 +29,7 @@ from typing import Optional
 
 from torch.utils.data import ConcatDataset
 
+import transformers
 from transformers import (
     CONFIG_MAPPING,
     MODEL_WITH_LM_HEAD_MAPPING,
@@ -47,6 +48,7 @@ from transformers import (
     TrainingArguments,
     set_seed,
 )
+from transformers.trainer_utils import is_main_process
 
 
 logger = logging.getLogger(__name__)
@@ -219,6 +221,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed

examples/contrib/mm-imdb/run_mmimdb.py

@@ -31,6 +31,7 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from transformers import (
     WEIGHTS_NAME,
     AdamW,
@@ -41,6 +42,7 @@ from transformers import (
     MMBTForClassification,
     get_linear_schedule_with_warmup,
 )
+from transformers.trainer_utils import is_main_process
 from utils_mmimdb import ImageEncoder, JsonlDataset, collate_fn, get_image_transforms, get_mmimdb_labels
 
 
@@ -476,7 +478,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
-
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     # Set seed
     set_seed(args)
 

examples/contrib/run_swag.py

@@ -31,8 +31,10 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, Tenso
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from transformers import WEIGHTS_NAME, AdamW, AutoConfig, AutoTokenizer, get_linear_schedule_with_warmup
 from transformers.modeling_auto import AutoModelForMultipleChoice
+from transformers.trainer_utils import is_main_process
 
 
 try:
@@ -620,6 +622,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
 
     # Set seed
     set_seed(args)

examples/deebert/run_glue_deebert.py

@@ -13,6 +13,7 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, Tenso
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from src.modeling_highway_bert import DeeBertForSequenceClassification
 from src.modeling_highway_roberta import DeeRobertaForSequenceClassification
 from transformers import (
@@ -28,6 +29,7 @@ from transformers import glue_compute_metrics as compute_metrics
 from transformers import glue_convert_examples_to_features as convert_examples_to_features
 from transformers import glue_output_modes as output_modes
 from transformers import glue_processors as processors
+from transformers.trainer_utils import is_main_process
 
 
 try:
@@ -580,7 +582,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
-
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     # Set seed
     set_seed(args)
 

examples/distillation/run_squad_w_distillation.py

@@ -30,6 +30,7 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from transformers import (
     WEIGHTS_NAME,
     AdamW,
@@ -57,6 +58,7 @@ from transformers.data.metrics.squad_metrics import (
     squad_evaluate,
 )
 from transformers.data.processors.squad import SquadResult, SquadV1Processor, SquadV2Processor
+from transformers.trainer_utils import is_main_process
 
 
 try:
@@ -745,7 +747,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
-
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     # Set seed
     set_seed(args)
 

examples/language-modeling/run_clm.py

@@ -168,6 +168,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed before initializing model.

examples/language-modeling/run_mlm.py

@@ -179,6 +179,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed before initializing model.

examples/language-modeling/run_mlm_wwm.py

@@ -186,6 +186,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed before initializing model.

examples/language-modeling/run_plm.py

@@ -176,6 +176,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed before initializing model.

examples/multiple-choice/run_multiple_choice.py

@@ -23,6 +23,7 @@ from typing import Dict, Optional
 
 import numpy as np
 
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForMultipleChoice,
@@ -33,6 +34,7 @@ from transformers import (
     TrainingArguments,
     set_seed,
 )
+from transformers.trainer_utils import is_main_process
 from utils_multiple_choice import MultipleChoiceDataset, Split, processors
 
 
@@ -115,6 +117,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed

examples/multiple-choice/run_tf_multiple_choice.py

@@ -33,9 +33,15 @@ from transformers import (
     TFTrainingArguments,
     set_seed,
 )
+from transformers.utils import logging as hf_logging
 from utils_multiple_choice import Split, TFMultipleChoiceDataset, processors
 
 
+hf_logging.set_verbosity_info()
+hf_logging.enable_default_handler()
+hf_logging.enable_explicit_format()
+
+
 logger = logging.getLogger(__name__)
 
 

examples/question-answering/run_squad.py

@@ -29,6 +29,7 @@ from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
+import transformers
 from transformers import (
     MODEL_FOR_QUESTION_ANSWERING_MAPPING,
     WEIGHTS_NAME,
@@ -45,6 +46,7 @@ from transformers.data.metrics.squad_metrics import (
     squad_evaluate,
 )
 from transformers.data.processors.squad import SquadResult, SquadV1Processor, SquadV2Processor
+from transformers.trainer_utils import is_main_process
 
 
 try:
@@ -712,7 +714,11 @@ def main():
         bool(args.local_rank != -1),
         args.fp16,
     )
-
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     # Set seed
     set_seed(args)
 

examples/question-answering/run_squad_trainer.py

@@ -22,9 +22,11 @@ import sys
 from dataclasses import dataclass, field
 from typing import Optional
 
+import transformers
 from transformers import AutoConfig, AutoModelForQuestionAnswering, AutoTokenizer, HfArgumentParser, SquadDataset
 from transformers import SquadDataTrainingArguments as DataTrainingArguments
 from transformers import Trainer, TrainingArguments
+from transformers.trainer_utils import is_main_process
 
 
 logger = logging.getLogger(__name__)
@@ -91,6 +93,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Prepare Question-Answering task

examples/question-answering/run_tf_squad.py

@@ -33,6 +33,12 @@ from transformers import (
     squad_convert_examples_to_features,
 )
 from transformers.data.processors.squad import SquadV1Processor, SquadV2Processor
+from transformers.utils import logging as hf_logging
+
+
+hf_logging.set_verbosity_info()
+hf_logging.enable_default_handler()
+hf_logging.enable_explicit_format()
 
 
 logger = logging.getLogger(__name__)

examples/seq2seq/finetune_trainer.py

@@ -4,10 +4,11 @@ import sys
 from dataclasses import dataclass, field
 from typing import Optional
 
+import transformers
 from seq2seq_trainer import Seq2SeqTrainer
 from seq2seq_training_args import Seq2SeqTrainingArguments
 from transformers import AutoConfig, AutoModelForSeq2SeqLM, AutoTokenizer, HfArgumentParser, MBartTokenizer, set_seed
-from transformers.trainer_utils import EvaluationStrategy
+from transformers.trainer_utils import EvaluationStrategy, is_main_process
 from utils import (
     Seq2SeqDataCollator,
     Seq2SeqDataset,
@@ -131,6 +132,11 @@ def main():
         bool(training_args.local_rank != -1),
         training_args.fp16,
     )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info("Training/evaluation parameters %s", training_args)
 
     # Set seed

examples/text-classification/run_glue.py

@@ -171,6 +171,8 @@ def main():
     # Set the verbosity to info of the Transformers logger (on main process only):
     if is_main_process(training_args.local_rank):
         transformers.utils.logging.set_verbosity_info()
+        transformers.utils.logging.enable_default_handler()
+        transformers.utils.logging.enable_explicit_format()
     logger.info(f"Training/evaluation parameters {training_args}")
 
     # Set seed before initializing model.

examples/text-classification/run_tf_glue.py

@@ -27,6 +27,12 @@ from transformers import (
     glue_processors,
     glue_tasks_num_labels,
 )
+from transformers.utils import logging as hf_logging
+
+
+hf_logging.set_verbosity_info()
+hf_logging.enable_default_handler()
+hf_logging.enable_explicit_format()
 
 
 class Split(Enum):