Add model_uuid to Java Model (#5165)

* add model_uuid Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * rename Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * test Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * uncomment Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * add test Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * update tests Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * set model uuid Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> * address comments Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
mlflow · Dec 15, 2021 · 2668809 · 2668809
1 parent f9b5745
commit 2668809
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Showing 5 changed files with 30 additions and 3 deletions.
diff --git a/mlflow/java/scoring/src/main/java/org/mlflow/models/Model.java b/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;
 
   /**
@@ -82,6 +86,11 @@ 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);

diff --git a/mlflow/java/scoring/src/test/java/org/mlflow/ModelTest.java b/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.assertFalse(model.getModelUuid().isPresent());
     } catch (IOException e) {
       e.printStackTrace();
       Assert.fail("Encountered an exception while reading the model from a configuration path!");

diff --git a/mlflow/java/scoring/src/test/resources/org/mlflow/models/sample_model_root/MLmodel b/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

diff --git a/...java/scoring/src/test/resources/org/mlflow/models/sample_model_root/MLmodel.no.model_uuid b/...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
diff --git a/mlflow/mleap.py b/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()