-- reduced reduntant tst cases

-- included fast_dev_run in testruns

Author: manujosephv

tests/test_autoint.py

@@ -21,12 +21,11 @@
             "Latitude",
             "Longitude",
         ],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"], []])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"]])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 @pytest.mark.parametrize("target_range", [True, False])
 @pytest.mark.parametrize("deep_layers", [True, False])
 @pytest.mark.parametrize("batch_norm_continuous_input", [True, False])
@@ -70,7 +69,7 @@ def test_regression(
         model_config_params["attention_pooling"] = attention_pooling
         model_config = AutoIntConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -93,12 +92,11 @@ def test_regression(
     "continuous_cols",
     [
         [f"feature_{i}" for i in range(54)],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"], []])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"]])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 @pytest.mark.parametrize("deep_layers", [True, False])
 @pytest.mark.parametrize("batch_norm_continuous_input", [True, False])
 def test_classification(
@@ -126,7 +124,7 @@ def test_classification(
         model_config_params["batch_norm_continuous_input"] = batch_norm_continuous_input
         model_config = AutoIntConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 

tests/test_categorical_embedding.py

@@ -80,7 +80,7 @@ def test_regression(
             model_config_params["target_range"] = _target_range
         model_config = CategoryEmbeddingModelConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -138,7 +138,7 @@ def test_classification(
         model_config_params = dict(task="classification")
         model_config = CategoryEmbeddingModelConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -174,7 +174,7 @@ def test_embedding_transformer(regression_data):
     model_config_params = dict(task="regression")
     model_config = CategoryEmbeddingModelConfig(**model_config_params)
     trainer_config = TrainerConfig(
-        max_epochs=1, checkpoints=None, early_stopping=None, gpus=0
+        max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
     )
     optimizer_config = OptimizerConfig()
 

tests/test_common.py

@@ -70,7 +70,7 @@ def test_save_load(
     model_config_params = dict(task="regression")
     model_config = model_config_class(**model_config_params)
     trainer_config = TrainerConfig(
-        max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+        max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
     )
     optimizer_config = OptimizerConfig()
 
@@ -133,7 +133,7 @@ def test_feature_extractor(
     model_config_params = dict(task="regression")
     model_config = model_config_class(**model_config_params)
     trainer_config = TrainerConfig(
-        max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+        max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
     )
     optimizer_config = OptimizerConfig()
 

tests/test_mdn.py

@@ -54,7 +54,7 @@ def test_regression(
         model_config_params['mdn_config'] = mdn_config
         model_config = variant(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -108,7 +108,7 @@ def test_classification(
         model_config_params['mdn_config'] = mdn_config
         model_config = CategoryEmbeddingMDNConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=3, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
         with pytest.raises(AssertionError):

tests/test_node.py

@@ -20,13 +20,12 @@
             "Latitude",
             "Longitude",
         ],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"], []])
+@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"]])
 @pytest.mark.parametrize("embed_categorical", [True, False])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 @pytest.mark.parametrize("target_range", [True, False])
 def test_regression(
     regression_data,
@@ -67,7 +66,7 @@ def test_regression(
             model_config_params["target_range"] = _target_range
         model_config = NodeConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=1, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -89,13 +88,12 @@ def test_regression(
     "continuous_cols",
     [
         [f"feature_{i}" for i in range(54)],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"], []])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
+@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"]])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
 @pytest.mark.parametrize("embed_categorical", [True, False])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 def test_classification(
     classification_data,
     continuous_cols,
@@ -123,7 +121,7 @@ def test_classification(
         )
         model_config = NodeConfig(**model_config_params)
         trainer_config = TrainerConfig(
-            max_epochs=1, checkpoints=None, early_stopping=None, gpus=0
+            max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
         )
         optimizer_config = OptimizerConfig()
 
@@ -160,7 +158,7 @@ def test_embedding_transformer(regression_data):
     )
     model_config = NodeConfig(**model_config_params)
     trainer_config = TrainerConfig(
-        max_epochs=1, checkpoints=None, early_stopping=None, gpus=0
+        max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True
     )
     optimizer_config = OptimizerConfig()
 

tests/test_tabnet.py

@@ -20,12 +20,11 @@
             "Latitude",
             "Longitude",
         ],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"], []])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"]])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 @pytest.mark.parametrize("target_range", [True, False])
 def test_regression(
     regression_data,
@@ -59,7 +58,7 @@ def test_regression(
                 )
             model_config_params["target_range"] = _target_range
         model_config = TabNetModelConfig(**model_config_params)
-        trainer_config = TrainerConfig(max_epochs=1, checkpoints=None, early_stopping=None, gpus=0)
+        trainer_config = TrainerConfig(max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True)
         optimizer_config = OptimizerConfig()
 
         tabular_model = TabularModel(
@@ -80,12 +79,11 @@ def test_regression(
     "continuous_cols",
     [
         [f"feature_{i}" for i in range(54)],
-        [],
     ],
 )
-@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"], []])
-@pytest.mark.parametrize("continuous_feature_transform", [None, "yeo-johnson"])
-@pytest.mark.parametrize("normalize_continuous_features", [True, False])
+@pytest.mark.parametrize("categorical_cols", [["feature_0_cat"]])
+@pytest.mark.parametrize("continuous_feature_transform", [None])
+@pytest.mark.parametrize("normalize_continuous_features", [True])
 def test_classification(
     classification_data,
     continuous_cols,
@@ -106,7 +104,7 @@ def test_classification(
         )
         model_config_params = dict(task="regression")
         model_config = TabNetModelConfig(**model_config_params)
-        trainer_config = TrainerConfig(max_epochs=1, checkpoints=None, early_stopping=None, gpus=0)
+        trainer_config = TrainerConfig(max_epochs=1, checkpoints=None, early_stopping=None, gpus=0, fast_dev_run=True)
         optimizer_config = OptimizerConfig()
 
         tabular_model = TabularModel(