Few init updates
@@ -32,7 +32,7 @@ class WandBLogger(StrategyLogger):
External storage for W&B Artifacts (for instance - AWS S3 and GCS
buckets) uri are supported.
- The wandb log files are placed by default in "./wandb/".
+ The wandb log files are placed by default in "./wandb/" unless specified.
.. note::
TensorBoard can be synced on to the W&B dedicated dashboard.
@@ -43,7 +43,7 @@ class WandBLogger(StrategyLogger):
path: str = "Checkpoints", checkpoint: str = "Model.pth",
uri: str = None, sync_tfboard: bool = False,
save_code: bool = True, config: object = None,
- params: dict = None):
+ dir: str = None, params: dict = None):
"""
Creates an instance of the `WandBLogger`.
:param project_name: Name of the W&B project.
@@ -55,6 +55,7 @@ class WandBLogger(StrategyLogger):
:param sync_tfboard: Syncs TensorBoard to the W&B dashboard UI.
:param save_code: Saves the main training script to W&B.
:param config: Syncs hyper-parameters and config values used to W&B.
+ :param dir: Path to the local log directory for W&B logs to be saved at.
:param params: All arguments for wandb.init() function call.
Visit https://docs.wandb.ai/ref/python/init to learn about all
wand.init() parameters.
@@ -70,6 +71,7 @@ class WandBLogger(StrategyLogger):
self.sync_tfboard = sync_tfboard
self.save_code = save_code
self.config = config
+ self.dir = dir
self.params = params
self.args_parse()
self.before_run()
@@ -85,7 +87,8 @@ class WandBLogger(StrategyLogger):
def args_parse(self):
self.init_kwargs = {"project": self.project_name, "name": self.run_name,
"sync_tensorboard": self.sync_tfboard,
- "save_code": self.save_code, "config": self.config}
+ "dir": self.dir, "save_code": self.save_code,
+ "config": self.config}
if self.params:
self.init_kwargs.update(self.params)
