From f0aedda2c37feedf46599fe6935c6d4cfd568a50 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 27 Nov 2019 23:45:23 -0500
Subject: [PATCH 01/15] Firebase ML Kit Modify Operation Handling to not
 require a name for Done Operations

---
 firebase_admin/mlkit.py | 40 +++++++++++++++++++--------------
 tests/test_mlkit.py     | 49 +++++++++++------------------------------
 2 files changed, 37 insertions(+), 52 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index a135d2d7f..72a34395e 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -810,28 +810,36 @@ def handle_operation(self, operation, wait_for_operation=False, max_time_seconds
         """
         if not isinstance(operation, dict):
             raise TypeError('Operation must be a dictionary.')
-        op_name = operation.get('name')
-        _, model_id = _validate_and_parse_operation_name(op_name)
-
-        current_attempt = 0
-        start_time = datetime.datetime.now()
-        stop_time = (None if max_time_seconds is None else
-                     start_time + datetime.timedelta(seconds=max_time_seconds))
-        while wait_for_operation and not operation.get('done'):
-            # We just got this operation. Wait before getting another
-            # so we don't exceed the GetOperation maximum request rate.
-            self._exponential_backoff(current_attempt, stop_time)
-            operation = self.get_operation(op_name)
-            current_attempt += 1
 
         if operation.get('done'):
+            # Operations which are immediately done don't have an operation name
             if operation.get('response'):
                 return operation.get('response')
             elif operation.get('error'):
                 raise _utils.handle_operation_error(operation.get('error'))
-
-        # If the operation is not complete or timed out, return a (locked) model instead
-        return get_model(model_id).as_dict()
+            raise exceptions.UnknownError(message='Internal Error: Malformed Operation.')
+        else:
+            op_name = operation.get('name')
+            _, model_id = _validate_and_parse_operation_name(op_name)
+            current_attempt = 0
+            start_time = datetime.datetime.now()
+            stop_time = (None if max_time_seconds is None else
+                        start_time + datetime.timedelta(seconds=max_time_seconds))
+            while wait_for_operation and not operation.get('done'):
+                # We just got this operation. Wait before getting another
+                # so we don't exceed the GetOperation maximum request rate.
+                self._exponential_backoff(current_attempt, stop_time)
+                operation = self.get_operation(op_name)
+                current_attempt += 1
+
+            if operation.get('done'):
+                if operation.get('response'):
+                    return operation.get('response')
+                elif operation.get('error'):
+                    raise _utils.handle_operation_error(operation.get('error'))
+
+            # If the operation is not complete or timed out, return a (locked) model instead
+            return get_model(model_id).as_dict()
 
 
     def create_model(self, model):
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 26afdfa99..fbe31aec4 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -158,23 +158,21 @@
 }
 
 OPERATION_DONE_MODEL_JSON_1 = {
-    'name': OPERATION_NAME_1,
     'done': True,
     'response': CREATED_UPDATED_MODEL_JSON_1
 }
 OPERATION_MALFORMED_JSON_1 = {
-    'name': OPERATION_NAME_1,
     'done': True,
     # if done is true then either response or error should be populated
 }
 OPERATION_MISSING_NAME = {
+    # Name is required if the operation is not done.
     'done': False
 }
 OPERATION_ERROR_CODE = 400
 OPERATION_ERROR_MSG = "Invalid argument"
 OPERATION_ERROR_EXPECTED_STATUS = 'INVALID_ARGUMENT'
 OPERATION_ERROR_JSON_1 = {
-    'name': OPERATION_NAME_1,
     'done': True,
     'error': {
         'code': OPERATION_ERROR_CODE,
@@ -609,17 +607,10 @@ def test_operation_error(self):
         check_operation_error(excinfo, OPERATION_ERROR_EXPECTED_STATUS, OPERATION_ERROR_MSG)
 
     def test_malformed_operation(self):
-        recorder = instrument_mlkit_service(
-            status=[200, 200],
-            payload=[OPERATION_MALFORMED_RESPONSE, LOCKED_MODEL_2_RESPONSE])
-        expected_model = mlkit.Model.from_dict(LOCKED_MODEL_JSON_2)
-        model = mlkit.create_model(MODEL_1)
-        assert model == expected_model
-        assert len(recorder) == 2
-        assert recorder[0].method == 'POST'
-        assert recorder[0].url == TestCreateModel._url(PROJECT_ID)
-        assert recorder[1].method == 'GET'
-        assert recorder[1].url == TestCreateModel._get_url(PROJECT_ID, MODEL_ID_1)
+        instrument_mlkit_service(status=200, payload=OPERATION_MALFORMED_RESPONSE)
+        with pytest.raises(Exception) as excinfo:
+            mlkit.create_model(MODEL_1)
+        check_error(excinfo, exceptions.UnknownError, 'Internal Error: Malformed Operation.')
 
     def test_rpc_error_create(self):
         create_recorder = instrument_mlkit_service(
@@ -708,17 +699,10 @@ def test_operation_error(self):
         check_operation_error(excinfo, OPERATION_ERROR_EXPECTED_STATUS, OPERATION_ERROR_MSG)
 
     def test_malformed_operation(self):
-        recorder = instrument_mlkit_service(
-            status=[200, 200],
-            payload=[OPERATION_MALFORMED_RESPONSE, LOCKED_MODEL_2_RESPONSE])
-        expected_model = mlkit.Model.from_dict(LOCKED_MODEL_JSON_2)
-        model = mlkit.update_model(MODEL_1)
-        assert model == expected_model
-        assert len(recorder) == 2
-        assert recorder[0].method == 'PATCH'
-        assert recorder[0].url == TestUpdateModel._url(PROJECT_ID, MODEL_ID_1)
-        assert recorder[1].method == 'GET'
-        assert recorder[1].url == TestUpdateModel._url(PROJECT_ID, MODEL_ID_1)
+        instrument_mlkit_service(status=200, payload=OPERATION_MALFORMED_RESPONSE)
+        with pytest.raises(Exception) as excinfo:
+            mlkit.update_model(MODEL_1)
+        check_error(excinfo, exceptions.UnknownError, 'Internal Error: Malformed Operation.')
 
     def test_rpc_error(self):
         create_recorder = instrument_mlkit_service(
@@ -824,17 +808,10 @@ def test_operation_error(self, publish_function):
 
     @pytest.mark.parametrize('publish_function', PUBLISH_UNPUBLISH_FUNCS)
     def test_malformed_operation(self, publish_function):
-        recorder = instrument_mlkit_service(
-            status=[200, 200],
-            payload=[OPERATION_MALFORMED_RESPONSE, LOCKED_MODEL_2_RESPONSE])
-        expected_model = mlkit.Model.from_dict(LOCKED_MODEL_JSON_2)
-        model = publish_function(MODEL_ID_1)
-        assert model == expected_model
-        assert len(recorder) == 2
-        assert recorder[0].method == 'PATCH'
-        assert recorder[0].url == TestPublishUnpublish._url(PROJECT_ID, MODEL_ID_1)
-        assert recorder[1].method == 'GET'
-        assert recorder[1].url == TestPublishUnpublish._url(PROJECT_ID, MODEL_ID_1)
+        instrument_mlkit_service(status=200, payload=OPERATION_MALFORMED_RESPONSE)
+        with pytest.raises(Exception) as excinfo:
+            publish_function(MODEL_ID_1)
+        check_error(excinfo, exceptions.UnknownError, 'Internal Error: Malformed Operation.')
 
     @pytest.mark.parametrize('publish_function', PUBLISH_UNPUBLISH_FUNCS)
     def test_rpc_error(self, publish_function):

From 8939ed60c991ce27c2d38bd57e1718e0a580b2e6 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Thu, 28 Nov 2019 00:00:25 -0500
Subject: [PATCH 02/15] fixed lint

---
 firebase_admin/mlkit.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 72a34395e..da8bda3c8 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -824,7 +824,7 @@ def handle_operation(self, operation, wait_for_operation=False, max_time_seconds
             current_attempt = 0
             start_time = datetime.datetime.now()
             stop_time = (None if max_time_seconds is None else
-                        start_time + datetime.timedelta(seconds=max_time_seconds))
+                         start_time + datetime.timedelta(seconds=max_time_seconds))
             while wait_for_operation and not operation.get('done'):
                 # We just got this operation. Wait before getting another
                 # so we don't exceed the GetOperation maximum request rate.

From 7078cb6a61d1fc2d06a84803d117cc12b15bf56d Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Mon, 2 Dec 2019 14:29:12 -0500
Subject: [PATCH 03/15] Adding support for TensorFlow 2.x

---
 firebase_admin/mlkit.py | 36 +++++++++++++++++++++++++-----------
 1 file changed, 25 insertions(+), 11 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index da8bda3c8..5d5c47a47 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -495,12 +495,30 @@ def from_tflite_model_file(cls, model_file_name, bucket_name=None, app=None):
         return TFLiteGCSModelSource(gcs_tflite_uri=gcs_uri, app=app)
 
     @staticmethod
-    def _assert_tf_version_1_enabled():
+    def _assert_tf_enabled():
         if not _TF_ENABLED:
             raise ImportError('Failed to import the tensorflow library for Python. Make sure '
                               'to install the tensorflow module.')
-        if not tf.VERSION.startswith('1.'):
-            raise ImportError('Expected tensorflow version 1.x, but found {0}'.format(tf.VERSION))
+        if not tf.version.VERSION.startswith('1.') and not tf.Version.startswith('2.'):
+            raise ImportError('Expected tensorflow version 1.x or 2.x, but found {0}'
+                              .format(tf.version.VERSION))
+
+    @staticmethod
+    def _tf_convert_from_saved_model(saved_model_dir):
+        # Same for both v1.x and v2.x
+        converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
+        return converter.convert()
+
+    @staticmethod
+    def _tf_convert_from_keras_model(keras_model):
+        if tf.version.VERSION.startswith('1.'):
+            keras_file = 'firebase_keras_model.h5'
+            tf.keras.models.save_model(keras_model, keras_file)
+            converter = tf.lite.TFLiteConverter.from_keras_model_file(keras_file)
+            return converter.convert()
+        else:
+            converter = tf.lite.TFLiteConverter.from_keras_model(keras_model)
+            return converter.convert()
 
     @classmethod
     def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
@@ -518,9 +536,8 @@ def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
         Raises:
             ImportError: If the Tensor Flow or Cloud Storage Libraries have not been installed.
         """
-        TFLiteGCSModelSource._assert_tf_version_1_enabled()
-        converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)
-        tflite_model = converter.convert()
+        TFLiteGCSModelSource._assert_tf_enabled()
+        tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
         open('firebase_mlkit_model.tflite', 'wb').write(tflite_model)
         return TFLiteGCSModelSource.from_tflite_model_file(
             'firebase_mlkit_model.tflite', bucket_name, app)
@@ -541,11 +558,8 @@ def from_keras_model(cls, keras_model, bucket_name=None, app=None):
         Raises:
             ImportError: If the Tensor Flow or Cloud Storage Libraries have not been installed.
         """
-        TFLiteGCSModelSource._assert_tf_version_1_enabled()
-        keras_file = 'keras_model.h5'
-        tf.keras.models.save_model(keras_model, keras_file)
-        converter = tf.lite.TFLiteConverter.from_keras_model_file(keras_file)
-        tflite_model = converter.convert()
+        TFLiteGCSModelSource._assert_tf_enabled()
+        tflite_model = TFLiteGCSModelSource._tf_convert_from_keras_model(keras_model)
         open('firebase_mlkit_model.tflite', 'wb').write(tflite_model)
         return TFLiteGCSModelSource.from_tflite_model_file(
             'firebase_mlkit_model.tflite', bucket_name, app)

From d88a66b4cb920861200d6258dccd6b830796efd2 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Mon, 2 Dec 2019 14:37:34 -0500
Subject: [PATCH 04/15] fix typo

---
 firebase_admin/mlkit.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 5d5c47a47..580f29d4c 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -499,7 +499,7 @@ def _assert_tf_enabled():
         if not _TF_ENABLED:
             raise ImportError('Failed to import the tensorflow library for Python. Make sure '
                               'to install the tensorflow module.')
-        if not tf.version.VERSION.startswith('1.') and not tf.Version.startswith('2.'):
+        if not tf.version.VERSION.startswith('1.') and not tf.version.VERSION.startswith('2.'):
             raise ImportError('Expected tensorflow version 1.x or 2.x, but found {0}'
                               .format(tf.version.VERSION))
 

From 8b5a6b34a01a58b16f800a5c6b116f0d96fd59cb Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Mon, 2 Dec 2019 14:44:01 -0500
Subject: [PATCH 05/15] remove extraneous @type from operations

---
 firebase_admin/mlkit.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 580f29d4c..027786400 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -200,6 +200,7 @@ def from_dict(cls, data, app=None):
         data_copy = dict(data)
         tflite_format = None
         tflite_format_data = data_copy.pop('tfliteModel', None)
+        data_copy.pop('@type', None)  # Returned by Operations. (Not needed)
         if tflite_format_data:
             tflite_format = TFLiteFormat.from_dict(tflite_format_data)
         model = Model(model_format=tflite_format)

From 7ee369d9d573723f37af10c4a942b4d781110e93 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 14:29:20 -0500
Subject: [PATCH 06/15] send updateMask in query parameter

---
 firebase_admin/mlkit.py |  6 +++---
 tests/test_mlkit.py     | 16 ++++++++++------
 2 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 027786400..b89fa5fdf 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -867,12 +867,12 @@ def create_model(self, model):
 
     def update_model(self, model, update_mask=None):
         _validate_model(model, update_mask)
-        data = {'model': model.as_dict(for_upload=True)}
+        path = 'models/{0}'.format(model.model_id)
         if update_mask is not None:
-            data['updateMask'] = update_mask
+            path = path + '?updateMask={0}'.format(update_mask)
         try:
             return self.handle_operation(
-                self._client.body('patch', url='models/{0}'.format(model.model_id), json=data))
+                self._client.body('patch', url=path, json=model.as_dict(for_upload=True)))
         except requests.exceptions.RequestException as error:
             raise _utils.handle_platform_error_from_requests(error)
 
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index fbe31aec4..8b0816b0a 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -763,7 +763,12 @@ def teardown_class(cls):
         testutils.cleanup_apps()
 
     @staticmethod
-    def _url(project_id, model_id):
+    def _update_url(project_id, model_id):
+        update_url = 'projects/{0}/models/{1}?updateMask=state.published'
+        return BASE_URL + update_url.format(project_id, model_id)
+
+    @staticmethod
+    def _get_url(project_id, model_id):
         return BASE_URL + 'projects/{0}/models/{1}'.format(project_id, model_id)
 
     @staticmethod
@@ -778,10 +783,9 @@ def test_immediate_done(self, publish_function, published):
         assert model == CREATED_UPDATED_MODEL_1
         assert len(recorder) == 1
         assert recorder[0].method == 'PATCH'
-        assert recorder[0].url == TestPublishUnpublish._url(PROJECT_ID, MODEL_ID_1)
+        assert recorder[0].url == TestPublishUnpublish._update_url(PROJECT_ID, MODEL_ID_1)
         body = json.loads(recorder[0].body.decode())
-        assert body.get('model', {}).get('state', {}).get('published', None) is published
-        assert body.get('updateMask', {}) == 'state.published'
+        assert body.get('state', {}).get('published', None) is published
 
     @pytest.mark.parametrize('publish_function', PUBLISH_UNPUBLISH_FUNCS)
     def test_returns_locked(self, publish_function):
@@ -794,9 +798,9 @@ def test_returns_locked(self, publish_function):
         assert model == expected_model
         assert len(recorder) == 2
         assert recorder[0].method == 'PATCH'
-        assert recorder[0].url == TestPublishUnpublish._url(PROJECT_ID, MODEL_ID_1)
+        assert recorder[0].url == TestPublishUnpublish._update_url(PROJECT_ID, MODEL_ID_1)
         assert recorder[1].method == 'GET'
-        assert recorder[1].url == TestPublishUnpublish._url(PROJECT_ID, MODEL_ID_1)
+        assert recorder[1].url == TestPublishUnpublish._get_url(PROJECT_ID, MODEL_ID_1)
 
     @pytest.mark.parametrize('publish_function', PUBLISH_UNPUBLISH_FUNCS)
     def test_operation_error(self, publish_function):

From d1a993335fe8eceb22612487597b389176b69df5 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 15:22:21 -0500
Subject: [PATCH 07/15] send list filters etc in query parameters

---
 firebase_admin/mlkit.py | 13 ++++++++-----
 tests/test_mlkit.py     | 10 ++++------
 2 files changed, 12 insertions(+), 11 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index b89fa5fdf..6e204029d 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -899,15 +899,18 @@ def list_models(self, list_filter, page_size, page_token):
         _validate_list_filter(list_filter)
         _validate_page_size(page_size)
         _validate_page_token(page_token)
-        payload = {}
+        path = 'models'
+        joiner = '?'
         if list_filter:
-            payload['list_filter'] = list_filter
+            path = path + joiner + 'listFilter=\'{0}\''.format(list_filter)
+            joiner = '&'
         if page_size:
-            payload['page_size'] = page_size
+            path = path + joiner + 'pageSize={0}'.format(page_size)
+            joiner = '&'
         if page_token:
-            payload['page_token'] = page_token
+            path = path + joiner + 'pageToken={0}'.format(page_token)
         try:
-            return self._client.body('get', url='models', json=payload)
+            return self._client.body('get', url=path)
         except requests.exceptions.RequestException as error:
             raise _utils.handle_platform_error_from_requests(error)
 
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 8b0816b0a..577e5b420 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -977,12 +977,10 @@ def test_list_models_with_all_args(self):
             page_token=PAGE_TOKEN)
         assert len(recorder) == 1
         assert recorder[0].method == 'GET'
-        assert recorder[0].url == TestListModels._url(PROJECT_ID)
-        assert json.loads(recorder[0].body.decode()) == {
-            'list_filter': 'display_name=displayName3',
-            'page_size': 10,
-            'page_token': PAGE_TOKEN
-        }
+        assert recorder[0].url == (
+            TestListModels._url(PROJECT_ID) +
+            '?listFilter=\'display_name=displayName3\'&pageSize=10&pageToken={0}'
+            .format(PAGE_TOKEN))
         assert isinstance(models_page, mlkit.ListModelsPage)
         assert len(models_page.models) == 1
         assert models_page.models[0] == MODEL_3

From 68ebe7732f1f254ff9356c963cbf1687e5851a06 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 17:16:14 -0500
Subject: [PATCH 08/15] fix typo

---
 firebase_admin/mlkit.py | 6 +++---
 tests/test_mlkit.py     | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 6e204029d..624a4000d 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -902,13 +902,13 @@ def list_models(self, list_filter, page_size, page_token):
         path = 'models'
         joiner = '?'
         if list_filter:
-            path = path + joiner + 'listFilter=\'{0}\''.format(list_filter)
+            path = path + joiner + 'list_filter=\'{0}\''.format(list_filter)
             joiner = '&'
         if page_size:
-            path = path + joiner + 'pageSize={0}'.format(page_size)
+            path = path + joiner + 'page_size={0}'.format(page_size)
             joiner = '&'
         if page_token:
-            path = path + joiner + 'pageToken={0}'.format(page_token)
+            path = path + joiner + 'page_token={0}'.format(page_token)
         try:
             return self._client.body('get', url=path)
         except requests.exceptions.RequestException as error:
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 577e5b420..8926be6dc 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -979,7 +979,7 @@ def test_list_models_with_all_args(self):
         assert recorder[0].method == 'GET'
         assert recorder[0].url == (
             TestListModels._url(PROJECT_ID) +
-            '?listFilter=\'display_name=displayName3\'&pageSize=10&pageToken={0}'
+            '?list_filter=\'display_name=displayName3\'&page_size=10&page_token={0}'
             .format(PAGE_TOKEN))
         assert isinstance(models_page, mlkit.ListModelsPage)
         assert len(models_page.models) == 1

From 5633b9f32e9a198519107d095f5df1360a4b7838 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 17:21:26 -0500
Subject: [PATCH 09/15] fix typo

---
 firebase_admin/mlkit.py | 2 +-
 tests/test_mlkit.py     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 624a4000d..17d15989f 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -902,7 +902,7 @@ def list_models(self, list_filter, page_size, page_token):
         path = 'models'
         joiner = '?'
         if list_filter:
-            path = path + joiner + 'list_filter=\'{0}\''.format(list_filter)
+            path = path + joiner + 'filter=\'{0}\''.format(list_filter)
             joiner = '&'
         if page_size:
             path = path + joiner + 'page_size={0}'.format(page_size)
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 8926be6dc..5f12dcb7e 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -979,7 +979,7 @@ def test_list_models_with_all_args(self):
         assert recorder[0].method == 'GET'
         assert recorder[0].url == (
             TestListModels._url(PROJECT_ID) +
-            '?list_filter=\'display_name=displayName3\'&page_size=10&page_token={0}'
+            '?filter=\'display_name=displayName3\'&page_size=10&page_token={0}'
             .format(PAGE_TOKEN))
         assert isinstance(models_page, mlkit.ListModelsPage)
         assert len(models_page.models) == 1

From d715628543d73000c1f7f803cdc418c653a52840 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 17:49:10 -0500
Subject: [PATCH 10/15] fix typo

---
 firebase_admin/mlkit.py | 2 +-
 tests/test_mlkit.py     | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 17d15989f..050a1ffba 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -902,7 +902,7 @@ def list_models(self, list_filter, page_size, page_token):
         path = 'models'
         joiner = '?'
         if list_filter:
-            path = path + joiner + 'filter=\'{0}\''.format(list_filter)
+            path = path + joiner + 'filter={0}'.format(list_filter)
             joiner = '&'
         if page_size:
             path = path + joiner + 'page_size={0}'.format(page_size)
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 5f12dcb7e..0daec946b 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -979,7 +979,7 @@ def test_list_models_with_all_args(self):
         assert recorder[0].method == 'GET'
         assert recorder[0].url == (
             TestListModels._url(PROJECT_ID) +
-            '?filter=\'display_name=displayName3\'&page_size=10&page_token={0}'
+            '?filter=display_name=displayName3&page_size=10&page_token={0}'
             .format(PAGE_TOKEN))
         assert isinstance(models_page, mlkit.ListModelsPage)
         assert len(models_page.models) == 1

From b63a4feca17dd52b0c808c7cbcdcbabbc328219d Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 18:15:35 -0500
Subject: [PATCH 11/15] urlEncode filter string

---
 firebase_admin/mlkit.py | 16 +++++++++-------
 tests/test_mlkit.py     |  2 +-
 2 files changed, 10 insertions(+), 8 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index 050a1ffba..b75dd2233 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -27,6 +27,7 @@
 import six
 
 
+from six.moves import urllib
 from firebase_admin import _http_client
 from firebase_admin import _utils
 from firebase_admin import exceptions
@@ -899,16 +900,17 @@ def list_models(self, list_filter, page_size, page_token):
         _validate_list_filter(list_filter)
         _validate_page_size(page_size)
         _validate_page_token(page_token)
-        path = 'models'
-        joiner = '?'
+        params = {}
         if list_filter:
-            path = path + joiner + 'filter={0}'.format(list_filter)
-            joiner = '&'
+            params['filter'] = list_filter
         if page_size:
-            path = path + joiner + 'page_size={0}'.format(page_size)
-            joiner = '&'
+            params['page_size'] = page_size
         if page_token:
-            path = path + joiner + 'page_token={0}'.format(page_token)
+            params['page_token'] = page_token
+        path = 'models'
+        if params != {}:
+            param_str = urllib.parse.urlencode(sorted(params.items()), True)
+            path = path + '?' + param_str
         try:
             return self._client.body('get', url=path)
         except requests.exceptions.RequestException as error:
diff --git a/tests/test_mlkit.py b/tests/test_mlkit.py
index 0daec946b..3198eff34 100644
--- a/tests/test_mlkit.py
+++ b/tests/test_mlkit.py
@@ -979,7 +979,7 @@ def test_list_models_with_all_args(self):
         assert recorder[0].method == 'GET'
         assert recorder[0].url == (
             TestListModels._url(PROJECT_ID) +
-            '?filter=display_name=displayName3&page_size=10&page_token={0}'
+            '?filter=display_name%3DdisplayName3&page_size=10&page_token={0}'
             .format(PAGE_TOKEN))
         assert isinstance(models_page, mlkit.ListModelsPage)
         assert len(models_page.models) == 1

From 71e6705464b5e5645ed8cdfd85a575cc2647d228 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Wed, 4 Dec 2019 19:49:09 -0500
Subject: [PATCH 12/15] adding optional file names to conversion functions
 (start)

---
 firebase_admin/mlkit.py | 17 +++++++++++++----
 1 file changed, 13 insertions(+), 4 deletions(-)

diff --git a/firebase_admin/mlkit.py b/firebase_admin/mlkit.py
index b75dd2233..f810a55da 100644
--- a/firebase_admin/mlkit.py
+++ b/firebase_admin/mlkit.py
@@ -51,6 +51,7 @@
 _MODEL_ID_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
 _DISPLAY_NAME_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
 _TAG_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
+_MODEL_FILE_NAME_PATTERN = re.compile(r'^[A-Za-z0-9_]{1,60}.tflite$')
 _GCS_TFLITE_URI_PATTERN = re.compile(
     r'^gs://(?P<bucket_name>[a-z0-9_.-]{3,63})/(?P<blob_name>.+)$')
 _RESOURCE_NAME_PATTERN = re.compile(
@@ -522,12 +523,19 @@ def _tf_convert_from_keras_model(keras_model):
             converter = tf.lite.TFLiteConverter.from_keras_model(keras_model)
             return converter.convert()
 
+    @staticmethod
+    def _validate_model_file_name(file_name):
+        if not _MODEL_FILE_NAME_PATTERN.match(file_name):
+            raise ValueError('Model file name format is invalid.')
+        return file_name
+
     @classmethod
-    def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
+    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_mlkit_model.tflite', bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the saved model, and uploads the model to GCS.
 
         Args:
             saved_model_dir: The saved model directory.
+            model_file_name: The name that the tflite model will be saved as in Cloud Storage.
             bucket_name: The name of an existing bucket. None to use the default bucket configured
                 in the app.
             app: Optional. A Firebase app instance (or None to use the default app)
@@ -538,11 +546,11 @@ def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
         Raises:
             ImportError: If the Tensor Flow or Cloud Storage Libraries have not been installed.
         """
+        file_name = TFLiteGCSModelSource._validate_model_file_name(model_file_name)
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
-        open('firebase_mlkit_model.tflite', 'wb').write(tflite_model)
-        return TFLiteGCSModelSource.from_tflite_model_file(
-            'firebase_mlkit_model.tflite', bucket_name, app)
+        open(file_name, 'wb').write(tflite_model)
+        return TFLiteGCSModelSource.from_tflite_model_file(file_name, bucket_name, app)
 
     @classmethod
     def from_keras_model(cls, keras_model, bucket_name=None, app=None):
@@ -909,6 +917,7 @@ def list_models(self, list_filter, page_size, page_token):
             params['page_token'] = page_token
         path = 'models'
         if params != {}:
+            # pylint: disable=too-many-function-args
             param_str = urllib.parse.urlencode(sorted(params.items()), True)
             path = path + '?' + param_str
         try:

From d24e7420d63a86a42d986efed4ff67fb010561aa Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Fri, 13 Dec 2019 15:32:17 -0500
Subject: [PATCH 13/15] adding File naming capability for ModelSource

---
 firebase_admin/ml.py | 22 +++++++---------------
 1 file changed, 7 insertions(+), 15 deletions(-)

diff --git a/firebase_admin/ml.py b/firebase_admin/ml.py
index 540be1520..61dfedd80 100644
--- a/firebase_admin/ml.py
+++ b/firebase_admin/ml.py
@@ -51,7 +51,6 @@
 _MODEL_ID_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
 _DISPLAY_NAME_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
 _TAG_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,60}$')
-_MODEL_FILE_NAME_PATTERN = re.compile(r'^[A-Za-z0-9_]{1,60}.tflite$')
 _GCS_TFLITE_URI_PATTERN = re.compile(
     r'^gs://(?P<bucket_name>[a-z0-9_.-]{3,63})/(?P<blob_name>.+)$')
 _RESOURCE_NAME_PATTERN = re.compile(
@@ -524,14 +523,8 @@ def _tf_convert_from_keras_model(keras_model):
             converter = tf.lite.TFLiteConverter.from_keras_model(keras_model)
             return converter.convert()
 
-    @staticmethod
-    def _validate_model_file_name(file_name):
-        if not _MODEL_FILE_NAME_PATTERN.match(file_name):
-            raise ValueError('Model file name format is invalid.')
-        return file_name
-
     @classmethod
-    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_mlkit_model.tflite', bucket_name=None, app=None):
+    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tflite', bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the saved model, and uploads the model to GCS.
 
         Args:
@@ -547,18 +540,18 @@ def from_saved_model(cls, saved_model_dir, model_file_name='firebase_mlkit_model
         Raises:
             ImportError: If the Tensor Flow or Cloud Storage Libraries have not been installed.
         """
-        file_name = TFLiteGCSModelSource._validate_model_file_name(model_file_name)
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
-        open(file_name, 'wb').write(tflite_model)
-        return TFLiteGCSModelSource.from_tflite_model_file(file_name, bucket_name, app)
+        open(model_file_name, 'wb').write(tflite_model)
+        return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @classmethod
-    def from_keras_model(cls, keras_model, bucket_name=None, app=None):
+    def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite', bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the keras model, and uploads the model to GCS.
 
         Args:
             keras_model: A tf.keras model.
+            model_file_name: The name that the tflite model will be saved as in Cloud Storage.
             bucket_name: The name of an existing bucket. None to use the default bucket configured
                 in the app.
             app: Optional. A Firebase app instance (or None to use the default app)
@@ -571,9 +564,8 @@ def from_keras_model(cls, keras_model, bucket_name=None, app=None):
         """
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_keras_model(keras_model)
-        open('firebase_ml_model.tflite', 'wb').write(tflite_model)
-        return TFLiteGCSModelSource.from_tflite_model_file(
-            'firebase_ml_model.tflite', bucket_name, app)
+        open(model_file_name, 'wb').write(tflite_model)
+        return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @property
     def gcs_tflite_uri(self):

From 0233bfac96bb5b329b87ef8dd60d5e394e08a164 Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Fri, 13 Dec 2019 15:42:45 -0500
Subject: [PATCH 14/15] fixed lint

---
 firebase_admin/ml.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/firebase_admin/ml.py b/firebase_admin/ml.py
index 61dfedd80..f49c43f10 100644
--- a/firebase_admin/ml.py
+++ b/firebase_admin/ml.py
@@ -524,7 +524,8 @@ def _tf_convert_from_keras_model(keras_model):
             return converter.convert()
 
     @classmethod
-    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tflite', bucket_name=None, app=None):
+    def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tflite',
+                         bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the saved model, and uploads the model to GCS.
 
         Args:
@@ -546,7 +547,8 @@ def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tf
         return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @classmethod
-    def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite', bucket_name=None, app=None):
+    def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite',
+                         bucket_name=None, app=None):
         """Creates a Tensor Flow Lite model from the keras model, and uploads the model to GCS.
 
         Args:

From 7230667cae575b4cf23d9e1c37008d3063282b6e Mon Sep 17 00:00:00 2001
From: ifielker <ifielker@gmail.com>
Date: Fri, 13 Dec 2019 16:14:25 -0500
Subject: [PATCH 15/15] fixed file descriptor leak

---
 firebase_admin/ml.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/firebase_admin/ml.py b/firebase_admin/ml.py
index f49c43f10..c6720f081 100644
--- a/firebase_admin/ml.py
+++ b/firebase_admin/ml.py
@@ -543,7 +543,8 @@ def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tf
         """
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
-        open(model_file_name, 'wb').write(tflite_model)
+        with open(model_file_name, 'wb') as model_file:
+            model_file.write(tflite_model)
         return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @classmethod
@@ -566,7 +567,8 @@ def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite
         """
         TFLiteGCSModelSource._assert_tf_enabled()
         tflite_model = TFLiteGCSModelSource._tf_convert_from_keras_model(keras_model)
-        open(model_file_name, 'wb').write(tflite_model)
+        with open(model_file_name, 'wb') as model_file:
+            model_file.write(tflite_model)
         return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)
 
     @property