Fix formats

d3rlpy/algos/qlearning/base.py

@@ -389,8 +389,9 @@ def fit(
                 the directory name will be `{class name}_{timestamp}`.
             with_timestamp: Flag to add timestamp string to the last of
                 directory name.
-            logging_steps: number of steps to log metrics.
-            logging_strategy: what logging strategy to use.
+            logging_steps: Number of steps to log metrics. This will be ignored
+                if logging_strategy is EPOCH.
+            logging_strategy: Logging strategy to use.
             logger_adapter: LoggerAdapterFactory object.
             show_progress: Flag to show progress bar for iterations.
             save_interval: Interval to save parameters.

d3rlpy/logging/__init__.py

@@ -3,3 +3,4 @@
 from .noop_adapter import *
 from .tensorboard_adapter import *
 from .utils import *
+from .wandb_adapter import *

d3rlpy/logging/wandb_adapter.py

@@ -1,6 +1,6 @@
 from typing import Any, Dict, Optional
-from .logger import LoggerAdapter, LoggerAdapterFactory, SaveProtocol
 
+from .logger import LoggerAdapter, LoggerAdapterFactory, SaveProtocol
 
 __all__ = ["LoggerWanDBAdapter", "WanDBAdapterFactory"]
 
@@ -14,7 +14,11 @@ class LoggerWanDBAdapter(LoggerAdapter):
         experiment_name (str): Name of the experiment.
     """
 
-    def __init__(self, project: Optional[str] = None, experiment_name: Optional[str] = None):
+    def __init__(
+        self,
+        project: Optional[str] = None,
+        experiment_name: Optional[str] = None,
+    ):
         try:
             import wandb
         except ImportError as e:
@@ -29,16 +33,21 @@ def before_write_metric(self, epoch: int, step: int) -> None:
         """Callback executed before writing metric."""
         pass
 
-    def write_metric(self, epoch: int, step: int, name: str, value: float) -> None:
+    def write_metric(
+        self, epoch: int, step: int, name: str, value: float
+    ) -> None:
         """Writes metric to WandB."""
-        self.run.log({name: value, 'epoch': epoch}, step=step)
+        self.run.log({name: value, "epoch": epoch}, step=step)
 
     def after_write_metric(self, epoch: int, step: int) -> None:
         """Callback executed after writing metric."""
         pass
 
     def save_model(self, epoch: int, algo: SaveProtocol) -> None:
-        """Saves models to Weights & Biases. Not implemented for WandB."""
+        """Saves models to Weights & Biases.
+
+        Not implemented for WandB.
+        """
         # Implement saving model to wandb if needed
         pass
 
@@ -50,8 +59,8 @@ def close(self) -> None:
 class WanDBAdapterFactory(LoggerAdapterFactory):
     r"""WandB Logger Adapter Factory class.
 
-    This class creates instances of the WandB Logger Adapter for experiment tracking.
-
+    This class creates instances of the WandB Logger Adapter for experiment
+    tracking.
     """
 
     _project: str
@@ -61,7 +70,6 @@ def __init__(self, project: Optional[str] = None) -> None:
 
         Args:
             project (Optional[str], optional): The name of the WandB project. Defaults to None.
-
         """
         super().__init__()
         self._project = project
@@ -74,6 +82,7 @@ def create(self, experiment_name: str) -> LoggerAdapter:
 
         Returns:
             LoggerAdapter: Instance of the WandB Logger Adapter.
-
         """
-        return LoggerWanDBAdapter(project=self._project, experiment_name=experiment_name)
+        return LoggerWanDBAdapter(
+            project=self._project, experiment_name=experiment_name
+        )