chore: import upstream snapshot with attribution

rdagent/components/coder/data_science/ensemble/test.py

@@ -0,0 +1,58 @@
+"""
+Helper functions for testing the ensemble coder(CoSTEER-based) component.
+"""
+
+import sys
+from pathlib import Path
+
+from rdagent.components.coder.data_science.ensemble import EnsembleCoSTEER
+from rdagent.components.coder.data_science.ensemble.exp import EnsembleTask
+from rdagent.scenarios.data_science.experiment.experiment import DSExperiment
+from rdagent.scenarios.data_science.scen import KaggleScen
+
+# Add the competition folder to path
+COMPETITION_PATH = (
+    Path(__file__).parent.parent.parent.parent.parent
+    / "scenarios"
+    / "kaggle"
+    / "tpl_ex"
+    / "aerial-cactus-identification"
+)
+sys.path.append(str(COMPETITION_PATH))
+
+EnsembleExperiment = DSExperiment
+
+
+def load_ensemble_spec():
+    spec_path = COMPETITION_PATH / "spec" / "ensemble.md"
+    with open(spec_path, "r") as f:
+        return f.read()
+
+
+def develop_one_competition(competition: str):
+    # Initialize scenario and coder
+    scen = KaggleScen(competition=competition)
+    ensemble_coder = EnsembleCoSTEER(scen)
+    # Load ensemble specification
+    ensemble_spec = load_ensemble_spec()
+
+    # Create the ensemble task with actual data context and specification
+    task = EnsembleTask(
+        name="EnsembleTask",
+        description="""
+        Implement ensemble and decision making for model predictions.
+        """,
+    )
+
+    exp = EnsembleExperiment(pending_tasks_list=[task])
+
+    # Injecting the corresponding specification
+    exp.experiment_workspace.inject_files(**{"spec/ensemble.md": ensemble_spec})
+
+    # Develop the experiment
+    exp = ensemble_coder.develop(exp)
+    return exp
+
+
+if __name__ == "__main__":
+    develop_one_competition("aerial-cactus-identification")