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refactor: set log level to separate out train args #314

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refactor: set log level to separate out train args #314

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8 changes: 2 additions & 6 deletions tuning/sft_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@
USER_ERROR_EXIT_CODE,
write_termination_log,
)
from tuning.utils.logging import set_log_level
from tuning.utils.logging import set_log_level, set_python_log_level
from tuning.utils.preprocessing_utils import (
format_dataset,
get_data_collator,
Expand Down Expand Up @@ -377,11 +377,7 @@ def save(path: str, trainer: SFTTrainer, log_level="WARNING"):
Optional threshold to set save save logger to, default warning.
"""
logger = logging.getLogger("sft_trainer_save")
# default value from TrainingArguments
if log_level == "passive":
log_level = "WARNING"

logger.setLevel(log_level.upper())
set_python_log_level(log_level, logger)

if not os.path.exists(path):
os.makedirs(path, exist_ok=True)
Expand Down
24 changes: 18 additions & 6 deletions tuning/utils/logging.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,12 +53,24 @@ def set_log_level(train_args, logger_name=None):
else os.environ.get("TRANSFORMERS_VERBOSITY")
)

logging.basicConfig(
format="%(levelname)s:%(filename)s:%(message)s", level=log_level.upper()
)

train_logger = logging.getLogger()
if logger_name:
train_logger = logging.getLogger(logger_name)
else:
train_logger = logging.getLogger()

set_python_log_level(log_level, train_logger)
set_python_log_level(log_level)
Comment on lines +56 to +61
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Nice to have a generic function set_python_log_level to set log level of any logger passed to it from any module of the code. Thank you!

Regarding function set_log_level, according to me, it is called to set root log level in the code based on either CLI using train_argsor ENV variable. Hence, I believe, if we don't want to call set_python_log_level twice in the function set_log_level, we can modify the code in function set_log_level as below:

set_python_log_level(log_level)
train_logger = logging.getLogger()
if logger_name:
    train_logger = logging.getLogger(logger_name)

return train_args, train_logger

Call set_python_log_level(log_level), will set the root log level and train_logger with or without logger_name, will inherit the root log level.

return train_args, train_logger


def set_python_log_level(log_level=None, logger=None):
# Configure Python native logger
# If CLI arg is passed, assign same log level to python native logger
if not log_level:
log_level = os.environ.get("LOG_LEVEL", "WARNING")

if logger:
logger.setLevel(log_level.upper())
else:
logging.basicConfig(
format="%(levelname)s:%(filename)s:%(message)s", level=log_level.upper()
)
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