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Update use_auth_token -> token in example scripts (#25167)

Browse Source 
* pytorch examples

* tensorflow examples

* flax examples

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-07-28 15:33:45 +02:00
committed by GitHub
parent 3cbc560d03
commit d53b8ad780
38 changed files with 116 additions and 116 deletions
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8
examples/tensorflow/contrastive-image-text/run_clip.py
View File

@@ -362,14 +362,14 @@ def main():
model_args.image_processor_name or model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
with training_args.strategy.scope():
model = TFAutoModel.from_pretrained(
model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
else:
# Load image_processor, in this script we only use this to get the mean and std for normalization.
@@ -377,14 +377,14 @@ def main():
model_args.image_processor_name or model_args.vision_model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
with training_args.strategy.scope():
model = TFVisionTextDualEncoderModel.from_vision_text_pretrained(
vision_model_name_or_path=model_args.vision_model_name_or_path,
text_model_name_or_path=model_args.text_model_name_or_path,
cache_dir=model_args.cache_dir,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
config = model.config

6
examples/tensorflow/image-classification/run_image_classification.py
View File

@@ -309,13 +309,13 @@ def main():
finetuning_task="image-classification",
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
image_processor = AutoImageProcessor.from_pretrained(
model_args.image_processor_name or model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# If we don't have a validation split, split off a percentage of train as validation.
@@ -435,7 +435,7 @@ def main():
from_pt=bool(".bin" in model_path),
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
ignore_mismatched_sizes=model_args.ignore_mismatched_sizes,
)
num_replicas = training_args.strategy.num_replicas_in_sync

6
examples/tensorflow/multiple-choice/run_swag.py
View File

@@ -335,14 +335,14 @@ def main():
config_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=model_args.use_fast_tokenizer,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion
@@ -428,7 +428,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
num_replicas = training_args.strategy.num_replicas_in_sync

6
examples/tensorflow/question-answering/run_qa.py
View File

@@ -338,14 +338,14 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=True,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion
@@ -625,7 +625,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
if training_args.do_train:
training_dataset = model.prepare_tf_dataset(

6
examples/tensorflow/summarization/run_summarization.py
View File

@@ -388,14 +388,14 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=model_args.use_fast_tokenizer,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
prefix = data_args.source_prefix if data_args.source_prefix is not None else ""
@@ -513,7 +513,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# We resize the embeddings only when necessary to avoid index errors. If you are creating a model from scratch

6
examples/tensorflow/text-classification/run_glue.py
View File

@@ -284,14 +284,14 @@ def main():
finetuning_task=data_args.task_name,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=model_args.use_fast_tokenizer,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion
@@ -374,7 +374,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion

8
examples/tensorflow/text-classification/run_text_classification.py
View File

@@ -301,20 +301,20 @@ def main():
num_labels=num_labels,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
else:
config = AutoConfig.from_pretrained(
config_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion
@@ -402,7 +402,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# endregion

6
examples/tensorflow/translation/run_translation.py
View File

@@ -352,14 +352,14 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=model_args.use_fast_tokenizer,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
prefix = data_args.source_prefix if data_args.source_prefix is not None else ""
@@ -466,7 +466,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# We resize the embeddings only when necessary to avoid index errors. If you are creating a model from scratch