🐛 Fix xgboost error

Author: kaylode

pyproject.toml

@@ -93,7 +93,7 @@ ml = [
   "psycopg2-binary>=2.9.5",
   "gunicorn>=20.1.0",
   "lightgbm>=3.3.3",
-  "xgboost>=1.7.1",
+  "xgboost<=1.7.1",
   "catboost",
   "shap>=0.41.0",
   "lime>=0.2.0.1",

tests/classification/inference.py

@@ -38,7 +38,7 @@ def inference(self):
 
         for idx, batch in enumerate(tqdm(self.dataloader)):
             img_names = batch["img_names"]
-            outputs = self.model.get_prediction(batch)
+            outputs = self.model.predict_step(batch)
             preds = outputs["names"]
             probs = outputs["confidences"]
 

tests/semantic/inference.py

@@ -49,7 +49,7 @@ def inference(self):
             img_names = batch["img_names"]
             ori_sizes = batch["ori_sizes"]
 
-            outputs = self.model.get_prediction(batch)
+            outputs = self.model.predict_step(batch)
             preds = outputs["masks"]
 
             for (inpt, pred, filename, ori_size) in zip(

tests/tabular/test_tablr.py

@@ -10,11 +10,11 @@ def test_train_tblr(override_config):
     train_pipeline.fit()
 
 
-# @pytest.mark.order(2)
-# def test_eval_tblr(override_config):
-#     override_config["global"]["pretrained"] = "runs/pytest_tablr/checkpoints/last"
-#     val_pipeline = MLPipeline(override_config)
-#     val_pipeline.evaluate()
+@pytest.mark.order(2)
+def test_eval_tblr(override_config):
+    override_config["global"]["pretrained"] = "runs/pytest_tablr/checkpoints/last"
+    val_pipeline = MLPipeline(override_config)
+    val_pipeline.evaluate()
 
 
 # @pytest.mark.order(2)

theseus/base/models/wrapper.py

@@ -94,7 +94,7 @@ def validation_step(self, batch, batch_idx):
         self.log_dict(outputs["loss_dict"], prog_bar=True, on_step=True, on_epoch=False)
         return outputs
 
-    def predict_step(self, batch, batch_idx):
+    def predict_step(self, batch, batch_idx=None):
         pred = self.model.get_prediction(batch)
         return pred