Apply ruff linting and formatting

Co-authored-by: manujosephv <10508493+manujosephv@users.noreply.github.com>

Author: Copilot

src/pytorch_tabular/config/config.py

@@ -6,7 +6,7 @@
 import os
 import re
 from dataclasses import MISSING, dataclass, field
-from typing import Any, Dict, Iterable, List, Optional, Union
+from typing import Any, Dict, Iterable, List, Optional
 
 from omegaconf import OmegaConf
 
@@ -192,9 +192,9 @@ class DataConfig:
     )
 
     def __post_init__(self):
-        assert (
-            len(self.categorical_cols) + len(self.continuous_cols) + len(self.date_columns) > 0
-        ), "There should be at-least one feature defined in categorical, continuous, or date columns"
+        assert len(self.categorical_cols) + len(self.continuous_cols) + len(self.date_columns) > 0, (
+            "There should be at-least one feature defined in categorical, continuous, or date columns"
+        )
         _validate_choices(self)
         if os.name == "nt" and self.num_workers != 0:
             print("Windows does not support num_workers > 0. Setting num_workers to 0")
@@ -255,9 +255,9 @@ class InferredConfig:
 
     def __post_init__(self):
         if self.embedding_dims is not None:
-            assert all(
-                (isinstance(t, Iterable) and len(t) == 2) for t in self.embedding_dims
-            ), "embedding_dims must be a list of tuples (cardinality, embedding_dim)"
+            assert all((isinstance(t, Iterable) and len(t) == 2) for t in self.embedding_dims), (
+                "embedding_dims must be a list of tuples (cardinality, embedding_dim)"
+            )
             self.embedded_cat_dim = sum([t[1] for t in self.embedding_dims])
         else:
             self.embedded_cat_dim = 0

tests/test_config.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
 """Tests for config classes."""
 
-import pytest
 from omegaconf import OmegaConf
 
 from pytorch_tabular.config import TrainerConfig
@@ -15,7 +14,7 @@ def test_devices_list_to_devices_conversion(self):
         # Test with a list of devices
         trainer_config = TrainerConfig(devices_list=[0, 1])
         assert trainer_config.devices == [0, 1]
-        
+
         # Wrap with OmegaConf as done in TabularModel
         config = OmegaConf.structured(trainer_config)
         assert config.devices == [0, 1]
@@ -24,31 +23,31 @@ def test_devices_list_multiple_gpus(self):
         """Test devices_list with multiple GPU IDs as documented."""
         trainer_config = TrainerConfig(devices_list=[1, 2, 3, 4])
         assert trainer_config.devices == [1, 2, 3, 4]
-        
+
         config = OmegaConf.structured(trainer_config)
         assert config.devices == [1, 2, 3, 4]
 
     def test_devices_int_value(self):
         """Test that devices accepts integer values."""
         trainer_config = TrainerConfig(devices=2)
         assert trainer_config.devices == 2
-        
+
         config = OmegaConf.structured(trainer_config)
         assert config.devices == 2
 
     def test_devices_default_value(self):
         """Test that devices has default value of -1."""
         trainer_config = TrainerConfig()
         assert trainer_config.devices == -1
-        
+
         config = OmegaConf.structured(trainer_config)
         assert config.devices == -1
 
     def test_devices_list_single_device(self):
         """Test devices_list with a single device."""
         trainer_config = TrainerConfig(devices_list=[0])
         assert trainer_config.devices == [0]
-        
+
         config = OmegaConf.structured(trainer_config)
         assert config.devices == [0]
 
@@ -57,21 +56,18 @@ def test_devices_list_precedence(self):
         # When both are provided, devices_list should take precedence
         trainer_config = TrainerConfig(devices=2, devices_list=[0, 1])
         assert trainer_config.devices == [0, 1]
-        
+
         config = OmegaConf.structured(trainer_config)
         assert config.devices == [0, 1]
 
     def test_omegaconf_merge_compatibility(self):
         """Test that config works correctly with OmegaConf.merge."""
         trainer_config = TrainerConfig(devices_list=[0, 1], max_epochs=10)
         config = OmegaConf.structured(trainer_config)
-        
+
         # Simulate merging as done in TabularModel
-        merged = OmegaConf.merge(
-            OmegaConf.to_container(config),
-            {"accelerator": "gpu"}
-        )
-        
+        merged = OmegaConf.merge(OmegaConf.to_container(config), {"accelerator": "gpu"})
+
         assert merged.devices == [0, 1]
         assert merged.max_epochs == 10
         assert merged.accelerator == "gpu"