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Use debug for loggers #655

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merged 2 commits into from
Aug 31, 2022
Merged

Use debug for loggers #655

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0560fcc
Use debug for loggers
muellerzr Aug 24, 2022
c60acce
Merge branch 'main' into log
muellerzr Aug 31, 2022
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32 changes: 16 additions & 16 deletions src/accelerate/tracking.py
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Original file line number Diff line number Diff line change
Expand Up @@ -134,8 +134,8 @@ def __init__(self, run_name: str, logging_dir: Optional[Union[str, os.PathLike]]
self.run_name = run_name
self.logging_dir = os.path.join(logging_dir, run_name)
self.writer = tensorboard.SummaryWriter(self.logging_dir, **kwargs)
logger.info(f"Initialized TensorBoard project {self.run_name} logging to {self.logging_dir}")
logger.info(
logger.debug(f"Initialized TensorBoard project {self.run_name} logging to {self.logging_dir}")
logger.debug(
"Make sure to log any initial configurations with `self.store_init_configuration` before training!"
)

Expand Down Expand Up @@ -164,7 +164,7 @@ def store_init_configuration(self, values: dict):
except yaml.representer.RepresenterError:
logger.error("Serialization to store hyperparameters failed")
raise
logger.info("Stored initial configuration hyperparameters to TensorBoard and hparams yaml file")
logger.debug("Stored initial configuration hyperparameters to TensorBoard and hparams yaml file")

def log(self, values: dict, step: Optional[int] = None, **kwargs):
"""
Expand All @@ -188,14 +188,14 @@ def log(self, values: dict, step: Optional[int] = None, **kwargs):
elif isinstance(v, dict):
self.writer.add_scalars(k, v, global_step=step, **kwargs)
self.writer.flush()
logger.info("Successfully logged to TensorBoard")
logger.debug("Successfully logged to TensorBoard")

def finish(self):
"""
Closes `TensorBoard` writer
"""
self.writer.close()
logger.info("TensorBoard writer closed")
logger.debug("TensorBoard writer closed")


class WandBTracker(GeneralTracker):
Expand All @@ -215,8 +215,8 @@ class WandBTracker(GeneralTracker):
def __init__(self, run_name: str, **kwargs):
self.run_name = run_name
self.run = wandb.init(project=self.run_name, **kwargs)
logger.info(f"Initialized WandB project {self.run_name}")
logger.info(
logger.debug(f"Initialized WandB project {self.run_name}")
logger.debug(
"Make sure to log any initial configurations with `self.store_init_configuration` before training!"
)

Expand All @@ -234,7 +234,7 @@ def store_init_configuration(self, values: dict):
`str`, `float`, `int`, or `None`.
"""
wandb.config.update(values)
logger.info("Stored initial configuration hyperparameters to WandB")
logger.debug("Stored initial configuration hyperparameters to WandB")

def log(self, values: dict, step: Optional[int] = None, **kwargs):
"""
Expand All @@ -250,14 +250,14 @@ def log(self, values: dict, step: Optional[int] = None, **kwargs):
Additional key word arguments passed along to the `wandb.log` method.
"""
self.run.log(values, step=step, **kwargs)
logger.info("Successfully logged to WandB")
logger.debug("Successfully logged to WandB")

def finish(self):
"""
Closes `wandb` writer
"""
self.run.finish()
logger.info("WandB run closed")
logger.debug("WandB run closed")


class CometMLTracker(GeneralTracker):
Expand All @@ -279,8 +279,8 @@ class CometMLTracker(GeneralTracker):
def __init__(self, run_name: str, **kwargs):
self.run_name = run_name
self.writer = Experiment(project_name=run_name, **kwargs)
logger.info(f"Initialized CometML project {self.run_name}")
logger.info(
logger.debug(f"Initialized CometML project {self.run_name}")
logger.debug(
"Make sure to log any initial configurations with `self.store_init_configuration` before training!"
)

Expand All @@ -298,7 +298,7 @@ def store_init_configuration(self, values: dict):
`str`, `float`, `int`, or `None`.
"""
self.writer.log_parameters(values)
logger.info("Stored initial configuration hyperparameters to CometML")
logger.debug("Stored initial configuration hyperparameters to CometML")

def log(self, values: dict, step: Optional[int] = None, **kwargs):
"""
Expand All @@ -323,14 +323,14 @@ def log(self, values: dict, step: Optional[int] = None, **kwargs):
self.writer.log_other(k, v, **kwargs)
elif isinstance(v, dict):
self.writer.log_metrics(v, step=step, **kwargs)
logger.info("Successfully logged to CometML")
logger.debug("Successfully logged to CometML")

def finish(self):
"""
Closes `comet-ml` writer
"""
self.writer.end()
logger.info("CometML run closed")
logger.debug("CometML run closed")


LOGGER_TYPE_TO_CLASS = {"tensorboard": TensorBoardTracker, "wandb": WandBTracker, "comet_ml": CometMLTracker}
Expand Down Expand Up @@ -384,6 +384,6 @@ def filter_trackers(
)
loggers.append(log_type)
else:
logger.info(f"Tried adding logger {log_type}, but package is unavailable in the system.")
logger.debug(f"Tried adding logger {log_type}, but package is unavailable in the system.")

return loggers