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Enforce string-formatting with f-strings (#10980)

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* First third

* Styling and fix mistake

* Quality

* All the rest

* Treat %s and %d

* typo

* Missing )

* Apply suggestions from code review

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
This commit is contained in:
Sylvain Gugger
2021-03-31 10:00:27 -04:00
committed by GitHub
parent d0b3797a3b
commit acc3bd9d2a
224 changed files with 984 additions and 1312 deletions
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14
examples/text-classification/run_tf_glue.py
View File

@@ -160,18 +160,16 @@ def main():
level=logging.INFO,
)
logger.info(
"n_replicas: %s, distributed training: %s, 16-bits training: %s",
training_args.n_replicas,
bool(training_args.n_replicas > 1),
training_args.fp16,
f"n_replicas: {training_args.n_replicas}, distributed training: {bool(training_args.n_replicas > 1)}, "
f"16-bits training: {training_args.fp16}",
)
logger.info("Training/evaluation parameters %s", training_args)
logger.info(f"Training/evaluation parameters {training_args}")
try:
num_labels = glue_tasks_num_labels["mnli" if data_args.task_name == "mnli-mm" else data_args.task_name]
output_mode = glue_output_modes[data_args.task_name]
except KeyError:
raise ValueError("Task not found: %s" % (data_args.task_name))
raise ValueError(f"Task not found: {data_args.task_name}")
# Load pretrained model and tokenizer
#
@@ -255,8 +253,8 @@ def main():
logger.info("***** Eval results *****")
for key, value in result.items():
logger.info(" %s = %s", key, value)
writer.write("%s = %s\n" % (key, value))
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
results.update(result)

12
examples/text-classification/run_tf_text_classification.py
View File

@@ -225,12 +225,10 @@ def main():
level=logging.INFO,
)
logger.info(
"n_replicas: %s, distributed training: %s, 16-bits training: %s",
training_args.n_replicas,
bool(training_args.n_replicas > 1),
training_args.fp16,
f"n_replicas: {training_args.n_replicas}, distributed training: {bool(training_args.n_replicas > 1)}, "
f"16-bits training: {training_args.fp16}"
)
logger.info("Training/evaluation parameters %s", training_args)
logger.info(f"Training/evaluation parameters {training_args}")
# Load pretrained model and tokenizer
#
@@ -300,8 +298,8 @@ def main():
logger.info("***** Eval results *****")
for key, value in result.items():
logger.info(" %s = %s", key, value)
writer.write("%s = %s\n" % (key, value))
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
results.update(result)