Add model_uuid to Java Model

mlflow/java/scoring/src/main/java/org/mlflow/models/Model.java

@@ -6,6 +6,7 @@
 import java.io.IOException;
 import java.util.Map;
 import java.util.Optional;
+import java.util.UUID;
 import org.mlflow.Flavor;
 import org.mlflow.utils.FileUtils;
 import org.mlflow.utils.SerializationUtils;
@@ -41,6 +42,9 @@ public static class Signature {
   @JsonProperty("input_example")
   private Map<String, Object> input_example;
 
+  @JsonProperty("model_uuid")
+  private String modelUuid;
+
   private String rootPath;
 
   /**
@@ -61,6 +65,11 @@ public static Model fromRootPath(String modelRootPath) throws IOException {
   public static Model fromConfigPath(String configPath) throws IOException {
     File configFile = new File(configPath);
     Model model = SerializationUtils.parseYamlFromFile(configFile, Model.class);
+    // Set the model uuid if it's absent.
+    if (!model.getModelUuid().isPresent()) {
+      String uuid = UUID.randomUUID().toString().replace("-", "");
+      model.setModelUuid(uuid);
+    }
     // Set the root path to the directory containing the configuration file.
     // This will be used to create an absolute path to the serialized model
     model.setRootPath(configFile.getParentFile().getAbsolutePath());
@@ -82,6 +91,11 @@ public Optional<String> getRunId() {
     return Optional.ofNullable(this.runId);
   }
 
+    /** @return The MLflow model's uuid */
+  public Optional<String> getModelUuid() {
+    return Optional.ofNullable(this.modelUuid);
+  }
+
   /** @return The path to the root directory of the MLflow model */
   public Optional<String> getRootPath() {
     return Optional.ofNullable(this.rootPath);
@@ -104,4 +118,8 @@ public <T extends Flavor> Optional<T> getFlavor(String flavorName, Class<T> flav
   private void setRootPath(String rootPath) {
     this.rootPath = rootPath;
   }
+
+  private void setModelUuid(String modelUuid) {
+    this.modelUuid = modelUuid;
+  }
 }

mlflow/java/scoring/src/test/java/org/mlflow/ModelTest.java

@@ -17,6 +17,19 @@ public void testModelIsLoadedFromYamlUsingConfigPathCorrectly() {
       Model model = Model.fromConfigPath(configPath);
       Assert.assertTrue(model.getFlavor(MLeapFlavor.FLAVOR_NAME, MLeapFlavor.class).isPresent());
       Assert.assertTrue(model.getUtcTimeCreated().isPresent());
+      Assert.assertTrue(model.getModelUuid().isPresent());
+    } catch (IOException e) {
+      e.printStackTrace();
+      Assert.fail("Encountered an exception while reading the model from a configuration path!");
+    }
+  }
+
+  @Test
+  public void testModelIsLoadedCorrectlyWhenModelUuidDoesNotExist() {
+    String configPath = getClass().getResource("sample_model_root/MLmodel.no.model_uuid").getFile();
+    try {
+      Model model = Model.fromConfigPath(configPath);
+      Assert.assertTrue(model.getModelUuid().isPresent());
     } catch (IOException e) {
       e.printStackTrace();
       Assert.fail("Encountered an exception while reading the model from a configuration path!");

mlflow/java/scoring/src/test/resources/org/mlflow/models/sample_model_root/MLmodel

@@ -5,7 +5,7 @@ flavors:
 utc_time_created: '2018-08-10 18:34:28.720095'
 run_id: c228016dea284522882b657d91eeffa6
 artifact_path: model
-
+model_uuid: 4ab08bf9d91e4535bc2719f9210840c3
 signature:
   inputs: '[{"name": "fixed acidity", "type": "double"}, {"name": "volatile acidity",
     "type": "double"}, {"name": "citric acid", "type": "double"}, {"name": "residual

mlflow/java/scoring/src/test/resources/org/mlflow/models/sample_model_root/MLmodel.no.model_uuid

@@ -0,0 +1,7 @@
+flavors:
+  mleap:
+    mleap_version: 0.8.1
+    model_data: mleap/model
+utc_time_created: "2018-08-10 18:34:28.720095"
+run_id: c228016dea284522882b657d91eeffa6
+artifact_path: model

mlflow/mleap.py

@@ -182,8 +182,6 @@ def save_model(
                           model. The given example will be converted to a Pandas DataFrame and then
                           serialized to json using the Pandas split-oriented format. Bytes are
                           base64-encoded.
-
-
     """
     if mlflow_model is None:
         mlflow_model = Model()

tests/models/test_model.py

@@ -164,3 +164,24 @@ def test_model_log_with_input_example_succeeds():
         # date column will get deserialized into string
         input_example["d"] = input_example["d"].apply(lambda x: x.isoformat())
         assert x.equals(input_example)
+
+
+def test_model_can_be_loaded_without_model_uuid(tmpdir):
+    ml_model_file = tmpdir.join("MLmodel")
+    ml_model_file.write(
+        """
+artifact_path: model
+flavors:
+  python_function:
+    env: conda.yaml
+    loader_module: mlflow.sklearn
+    model_path: model.pkl
+    python_version: 3.7.9
+  sklearn:
+    pickled_model: model.pkl
+    serialization_format: cloudpickle
+    sklearn_version: 0.24.1
+"""
+    )
+    model = Model.load(ml_model_file)
+    assert model.model_uuid is not None