Backwards compatibility for class_weights (#2469)

ludwig-ai · Sep 10, 2022 · 7870cf7 · 7870cf7
1 parent 877635f
commit 7870cf7
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diff --git a/ludwig/constants.py b/ludwig/constants.py
@@ -41,6 +41,7 @@
 INFER_IMAGE_MAX_WIDTH = "infer_image_max_width"
 INFER_IMAGE_SAMPLE_SIZE = "infer_image_sample_size"
 NUM_CHANNELS = "num_channels"
+CLASS_WEIGHTS = "class_weights"
 LOSS = "loss"
 ROC_AUC = "roc_auc"
 EVAL_LOSS = "eval_loss"

diff --git a/ludwig/utils/backward_compatibility.py b/ludwig/utils/backward_compatibility.py
@@ -20,6 +20,7 @@
 from ludwig.constants import (
     AUDIO,
     BIAS,
+    CLASS_WEIGHTS,
     COLUMN,
     CONV_BIAS,
     CONV_USE_BIAS,
@@ -32,6 +33,7 @@
     EXECUTOR,
     FORCE_SPLIT,
     INPUT_FEATURES,
+    LOSS,
     MISSING_VALUE_STRATEGY,
     NAME,
     NUM_SAMPLES,
@@ -156,6 +158,17 @@ def _traverse_dicts(config: Any, f: Callable[[Dict], None]):
             _traverse_dicts(v, f)
 
 
+@register_config_transformation("0.4", ["output_features"])
+def update_class_weights_in_features(feature: Dict[str, Any]) -> Dict[str, Any]:
+    if LOSS in feature:
+        class_weights = feature[LOSS].get(CLASS_WEIGHTS, None)
+        if not isinstance(class_weights, list):
+            class_weights = None
+        feature[LOSS][CLASS_WEIGHTS] = class_weights
+
+    return feature
+
+
 @register_config_transformation("0.5")
 def rename_training_to_trainer(config: Dict[str, Any]) -> Dict[str, Any]:
     if TRAINING in config:

diff --git a/tests/ludwig/utils/test_backward_compatibility.py b/tests/ludwig/utils/test_backward_compatibility.py
@@ -5,10 +5,12 @@
 
 from ludwig.constants import (
     BFILL,
+    CLASS_WEIGHTS,
     EVAL_BATCH_SIZE,
     EXECUTOR,
     HYPEROPT,
     INPUT_FEATURES,
+    LOSS,
     NUMBER,
     OUTPUT_FEATURES,
     PREPROCESSING,
@@ -494,6 +496,43 @@ def test_update_missing_value_strategy(missing_value_strategy: str):
     assert updated_config == expected_config
 
 
+def test_old_class_weights_default():
+    old_config = {
+        "input_features": [
+            {
+                "name": "input_feature_1",
+                "type": "category",
+            }
+        ],
+        "output_features": [
+            {"name": "output_feature_1", "type": "category", "loss": {"class_weights": 1}},
+        ],
+    }
+
+    new_config = {
+        "input_features": [
+            {
+                "name": "input_feature_1",
+                "type": "category",
+            }
+        ],
+        "output_features": [
+            {"name": "output_feature_1", "type": "category", "loss": {"class_weights": None}},
+        ],
+    }
+
+    upgraded_config = upgrade_to_latest_version(old_config)
+    del upgraded_config["ludwig_version"]
+    assert new_config == upgraded_config
+
+    old_config[OUTPUT_FEATURES][0][LOSS][CLASS_WEIGHTS] = [0.5, 0.8, 1]
+    new_config[OUTPUT_FEATURES][0][LOSS][CLASS_WEIGHTS] = [0.5, 0.8, 1]
+
+    upgraded_config = upgrade_to_latest_version(old_config)
+    del upgraded_config["ludwig_version"]
+    assert new_config == upgraded_config
+
+
 def test_upgrade_model_progress():
     old_model_progress = {
         "batch_size": 64,