added tests

Author: mingkang111

tests/unitary/with_extras/model/test_files/custom_score.py

@@ -0,0 +1,76 @@
+# score.py 1.0 generated by ADS 2.8.3-test-custom-scorepy on 20230331_192511
+# THIS IS A CUSTOM SCORE.PY
+import json
+import os
+import cloudpickle
+import pandas as pd
+import numpy as np
+from functools import lru_cache
+
+
+model_name = 'model.pkl'
+
+
+"""
+   Inference script. This script is used for prediction by scoring server when schema is known.
+"""
+
+
+@lru_cache(maxsize=10)
+def load_model(model_file_name=model_name):
+    """
+    Loads model from the serialized format
+
+    Returns
+    -------
+    model:  a model instance on which predict API can be invoked
+    """
+    return model_file_name
+
+def pre_inference(data):
+    """
+    Preprocess data
+
+    Parameters
+    ----------
+    data: Data format as expected by the predict API of the core estimator.
+
+    Returns
+    -------
+    data: Data format after any processing.
+
+    """
+    return data
+
+
+def post_inference(yhat):
+    """
+    Post-process the model results
+
+    Parameters
+    ----------
+    yhat: Data format after calling model.predict.
+
+    Returns
+    -------
+    yhat: Data format after any processing.
+
+    """
+    return yhat
+
+def predict(data, model=load_model()):
+    """
+    Returns prediction given the model and data to predict
+
+    Parameters
+    ----------
+    model: Model instance returned by load_model API
+    data: Data format as expected by the predict API of the core estimator. For eg. in case of sckit models it could be numpy array/List of list/Pandas DataFrame
+
+    Returns
+    -------
+    predictions: Output from scoring server
+        Format: {'prediction': output from model.predict method}
+
+    """
+    return {'prediction': "This is a custom score.py."}

tests/unitary/with_extras/model/test_generic_model.py

@@ -297,6 +297,19 @@ def test_prepare_both_conda_env(self, mock_signer):
             == "3.7"
         )
 
+    @patch("ads.common.auth.default_signer")
+    def test_prepare_with_custom_scorepy(self, mock_signer):
+        """Test prepare a trained model with custom score.py."""
+        self.generic_model.prepare(
+            "oci://service-conda-packs@ociodscdev/service_pack/cpu/General_Machine_Learning_for_CPUs/1.0/mlcpuv1",
+            model_file_name="fake_model_name",
+            score_py_uri=f"{os.path.dirname(os.path.abspath(__file__))}/test_files/custom_score.py"
+        )
+        assert os.path.exists(os.path.join("fake_folder", "score.py"))
+
+        prediction = self.generic_model.verify(data="test")["prediction"]
+        assert prediction == "This is a custom score.py."
+
     @patch("ads.common.auth.default_signer")
     def test_verify_without_reload(self, mock_signer):
         """Test verify input data without reload artifacts."""