Add online prediction instructions and print friendly msg in console. (…

…kubeflow#914)

component_sdk/python/kfp_component/core/_display.py

@@ -42,6 +42,8 @@ def display(obj):
     if '_repr_kfpmetadata_' in obj_dir:
         display_kfpmetadata(obj)
 
+    logging.info(str(obj))
+
 def display_markdown(obj):
     """Display markdown representation to KFP UI.
     """
@@ -63,7 +65,6 @@ def display_kfpmetadata(obj):
     _output_ui_metadata(kfp_metadata)
 
 def _output_ui_metadata(output):
-    logging.info('Dumping metadata: {}'.format(output))
     with _OUTPUT_FILE_LOCK:
         metadata = {}
         if os.path.isfile(_OUTPUT_PATH):
@@ -85,6 +86,9 @@ def __init__(self, data):
     def _repr_markdown_(self):
         return self._data
 
+    def __repr__(self):
+        return self._data
+
 class Tensorboard(object):
     """Class to hold tensorboard metadata.
     """
@@ -97,9 +101,17 @@ def _repr_kfpmetadata_(self):
             'source': self._job_dir
         }
 
+    def __repr__(self):
+        return 'Open Tensorboard at: {}'.format(self._job_dir)
+
 class Link(Markdown):
     """Class to hold an markdown hyperlink data.
     """
     def __init__(self, href, text):
         super(Link, self).__init__(
-            '## [{}]({})'.format(text, href))
+            '## [{}]({})'.format(text, href))
+        self._href = href
+        self._text = text
+
+    def __repr__(self):
+        return '{}: {}'.format(self._text, self._href)

component_sdk/python/kfp_component/google/ml_engine/_create_version.py

@@ -68,7 +68,7 @@ def __init__(self, model_name, version,
         replace_existing, wait_interval):
         self._ml = MLEngineClient()
         self._model_name = model_name
-        self._project_id, self._model_short_name = self._parse_model_name(model_name)
+        self._project_id, self._model_id = self._parse_model_name(model_name)
         # The name of the version resource, which is in the format 
         # of projects/*/models/*/versions/*
         self._version_name = None
@@ -164,9 +164,28 @@ def _handle_completed_version(self, version):
     def _dump_metadata(self):
         display.display(display.Link(
             'https://console.cloud.google.com/mlengine/models/{}/versions/{}?project={}'.format(
-                self._model_short_name, self._version_id, self._project_id),
+                self._model_id, self._version_id, self._project_id),
             'Version Details'
         ))
+        display.display(display.Markdown('''
+## Online Prediction
+
+### REST endpoint
+The REST endpoint for online prediction is as follows:
+```
+POST https://ml.googleapis.com/v1/{}:predict
+```
+Try the REST endpoint in [Google OAuth 2.0 Playgound](https://developers.google.com/oauthplayground/#step3\
+&apisSelect=https://www.googleapis.com/auth/cloud-platform&postData={{"instances":[]}}\
+&url=https://ml.googleapis.com/v1/{}:predict&content_type=application/json&http_method=POST).
+
+### GCloud command
+```bash
+gcloud ml-engine predict --model {}  \
+                   --version {} \
+                   --json-instances instances.json
+```
+        '''.format(self._version_name, self._version_name, self._model_id, self._version_id)))
 
     def _dump_version(self, version):
         logging.info('Dumping version: {}'.format(version))

component_sdk/python/tests/core/test__display.py

@@ -83,3 +83,10 @@ def test_display_link(self, mock_open, mock_os, mock_json):
                 'storage': 'inline'
             }]
         }, mock.ANY)
+
+    def test___repr__(self, mock_open, mock_os, mock_json):
+        self.assertEqual('# Title', str(display.Markdown('# Title')))
+        self.assertEqual('Open Tensorboard at: gs://trained/model/', 
+            str(display.Tensorboard('gs://trained/model/')))
+        self.assertEqual('title: https://test/uri', 
+            str(display.Link('https://test/uri', 'title')))