code formatting

examples/pytorch/main.py

@@ -1,5 +1,7 @@
+import torch
+
 import fog_rtx
-import torch 
+
 dataset = fog_rtx.dataset.Dataset(
     name="demo_ds",
     path="/tmp",
@@ -14,5 +16,10 @@
 pytorch_ds = dataset.pytorch_dataset_builder()
 
 # get samples from the dataset
-for data in torch.utils.data.DataLoader(pytorch_ds, batch_size=2, collate_fn=lambda x: x, sampler = torch.utils.data.RandomSampler(pytorch_ds)):
-    print(data)
+for data in torch.utils.data.DataLoader(
+    pytorch_ds,
+    batch_size=2,
+    collate_fn=lambda x: x,
+    sampler=torch.utils.data.RandomSampler(pytorch_ds),
+):
+    print(data)

fog_rtx/database/db_connector.py

@@ -3,15 +3,10 @@
 
 import pandas as pd  # type: ignore
 import sqlalchemy  # type: ignore
+from sqlalchemy import MetaData  # type: ignore
 from sqlalchemy import Table  # type: ignore
 from sqlalchemy import text  # type: ignore
-from sqlalchemy import (
-    Column,
-    Integer,
-    MetaData,  # type: ignore
-    create_engine,
-    inspect,
-)
+from sqlalchemy import Column, Integer, create_engine, inspect
 from sqlalchemy.orm import declarative_base, sessionmaker  # type: ignore
 
 from fog_rtx.database.utils import type_py2sql  # type: ignore

fog_rtx/dataset.py

@@ -158,11 +158,11 @@ def __getitem__(self, idx):
                 # For simplicity, let's assume we're just returning the episode
                 return episode
 
-         # Assume we use get_metadata_as_pandas_df to retrieve episodes metadata
+        # Assume we use get_metadata_as_pandas_df to retrieve episodes metadata
         metadata_df = self.get_metadata_as_pandas_df()
         episodes = self.read_by(metadata_df)
-        
+
         # Initialize the PyTorch dataset with the episodes and features
         pytorch_dataset = PyTorchDataset(episodes, self.features)
-        
-        return pytorch_dataset
+
+        return pytorch_dataset