chore: import upstream snapshot with attribution

examples/pyfunc/infer_model_code_paths.py

@@ -0,0 +1,23 @@
+from typing import Any
+
+from custom_code import iris_classes
+
+import mlflow
+
+
+class CustomPredict(mlflow.pyfunc.PythonModel):
+    """Custom pyfunc class used to create customized mlflow models"""
+
+    def predict(self, context, model_input, params: dict[str, Any] | None = None):
+        prediction = [x % 3 for x in model_input]
+        return iris_classes(prediction)
+
+
+with mlflow.start_run(run_name="test_custom_model_with_inferred_code_paths"):
+    # log a custom model
+    model_info = mlflow.pyfunc.log_model(
+        name="artifacts",
+        infer_code_paths=True,
+        python_model=CustomPredict(),
+    )
+    print(f"Model URI: {model_info.model_uri}")