change(ml): Drop AutoML model support (#894)

Author: jonathanedey

firebase_admin/ml.py

@@ -24,7 +24,6 @@
 import time
 import os
 from urllib import parse
-import warnings
 
 import requests
 
@@ -33,14 +32,14 @@
 from firebase_admin import _utils
 from firebase_admin import exceptions
 
-# pylint: disable=import-error,no-name-in-module
+# pylint: disable=import-error,no-member
 try:
     from firebase_admin import storage
     _GCS_ENABLED = True
 except ImportError:
     _GCS_ENABLED = False
 
-# pylint: disable=import-error,no-name-in-module
+# pylint: disable=import-error,no-member
 try:
     import tensorflow as tf
     _TF_ENABLED = True
@@ -54,9 +53,6 @@
 _TAG_PATTERN = re.compile(r'^[A-Za-z0-9_-]{1,32}$')
 _GCS_TFLITE_URI_PATTERN = re.compile(
     r'^gs://(?P<bucket_name>[a-z0-9_.-]{3,63})/(?P<blob_name>.+)$')
-_AUTO_ML_MODEL_PATTERN = re.compile(
-    r'^projects/(?P<project_id>[a-z0-9-]{6,30})/locations/(?P<location_id>[^/]+)/' +
-    r'models/(?P<model_id>[A-Za-z0-9]+)$')
 _RESOURCE_NAME_PATTERN = re.compile(
     r'^projects/(?P<project_id>[a-z0-9-]{6,30})/models/(?P<model_id>[A-Za-z0-9_-]{1,60})$')
 _OPERATION_NAME_PATTERN = re.compile(
@@ -388,11 +384,6 @@ def _init_model_source(data):
         gcs_tflite_uri = data.pop('gcsTfliteUri', None)
         if gcs_tflite_uri:
             return TFLiteGCSModelSource(gcs_tflite_uri=gcs_tflite_uri)
-        auto_ml_model = data.pop('automlModel', None)
-        if auto_ml_model:
-            warnings.warn('AutoML model support is deprecated and will be removed in the next '
-                          'major version.', DeprecationWarning)
-            return TFLiteAutoMlSource(auto_ml_model=auto_ml_model)
         return None
 
     @property
@@ -606,42 +597,6 @@ def as_dict(self, for_upload=False):
 
         return {'gcsTfliteUri': self._gcs_tflite_uri}
 
-
-class TFLiteAutoMlSource(TFLiteModelSource):
-    """TFLite model source representing a tflite model created with AutoML.
-
-    AutoML model support is deprecated and will be removed in the next major version.
-    """
-
-    def __init__(self, auto_ml_model, app=None):
-        warnings.warn('AutoML model support is deprecated and will be removed in the next '
-                      'major version.', DeprecationWarning)
-        self._app = app
-        self.auto_ml_model = auto_ml_model
-
-    def __eq__(self, other):
-        if isinstance(other, self.__class__):
-            return self.auto_ml_model == other.auto_ml_model
-        return False
-
-    def __ne__(self, other):
-        return not self.__eq__(other)
-
-    @property
-    def auto_ml_model(self):
-        """Resource name of the model, created by the AutoML API or Cloud console."""
-        return self._auto_ml_model
-
-    @auto_ml_model.setter
-    def auto_ml_model(self, auto_ml_model):
-        self._auto_ml_model = _validate_auto_ml_model(auto_ml_model)
-
-    def as_dict(self, for_upload=False):
-        """Returns a serializable representation of the object."""
-        # Upload is irrelevant for auto_ml models
-        return {'automlModel': self._auto_ml_model}
-
-
 class ListModelsPage:
     """Represents a page of models in a Firebase project.
 
@@ -786,11 +741,6 @@ def _validate_gcs_tflite_uri(uri):
         raise ValueError('GCS TFLite URI format is invalid.')
     return uri
 
-def _validate_auto_ml_model(model):
-    if not _AUTO_ML_MODEL_PATTERN.match(model):
-        raise ValueError('Model resource name format is invalid.')
-    return model
-
 
 def _validate_model_format(model_format):
     if not isinstance(model_format, ModelFormat):

integration/test_ml.py

@@ -22,25 +22,18 @@
 
 import pytest
 
-import firebase_admin
 from firebase_admin import exceptions
 from firebase_admin import ml
 from tests import testutils
 
 
-# pylint: disable=import-error,no-name-in-module
+# pylint: disable=import-error, no-member
 try:
     import tensorflow as tf
     _TF_ENABLED = True
 except ImportError:
     _TF_ENABLED = False
 
-try:
-    from google.cloud import automl_v1
-    _AUTOML_ENABLED = True
-except ImportError:
-    _AUTOML_ENABLED = False
-
 def _random_identifier(prefix):
     #pylint: disable=unused-variable
     suffix = ''.join([random.choice(string.ascii_letters + string.digits) for n in range(8)])
@@ -159,14 +152,6 @@ def check_tflite_gcs_format(model, validation_error=None):
         assert model.model_hash is not None
 
 
-def check_tflite_automl_format(model):
-    assert model.validation_error is None
-    assert model.published is False
-    assert model.model_format.model_source.auto_ml_model.startswith('projects/')
-    # Automl models don't have validation errors since they are references
-    # to valid automl models.
-
-
 @pytest.mark.parametrize('firebase_model', [NAME_AND_TAGS_ARGS], indirect=True)
 def test_create_simple_model(firebase_model):
     check_model(firebase_model, NAME_AND_TAGS_ARGS)
@@ -392,50 +377,3 @@ def test_from_saved_model(saved_model_dir):
         assert created_model.validation_error is None
     finally:
         _clean_up_model(created_model)
-
-
-# Test AutoML functionality if AutoML is enabled.
-#'pip install google-cloud-automl' in the environment if you want _AUTOML_ENABLED = True
-# You will also need a predefined AutoML model named 'admin_sdk_integ_test1' to run the
-# successful test. (Test is skipped otherwise)
-
-@pytest.fixture
-def automl_model():
-    assert _AUTOML_ENABLED
-
-    # It takes > 20 minutes to train a model, so we expect a predefined AutoMl
-    # model named 'admin_sdk_integ_test1' to exist in the project, or we skip
-    # the test.
-    automl_client = automl_v1.AutoMlClient()
-    project_id = firebase_admin.get_app().project_id
-    parent = automl_client.location_path(project_id, 'us-central1')
-    models = automl_client.list_models(parent, filter_="display_name=admin_sdk_integ_test1")
-    # Expecting exactly one. (Ok to use last one if somehow more than 1)
-    automl_ref = None
-    for model in models:
-        automl_ref = model.name
-
-    # Skip if no pre-defined model. (It takes min > 20 minutes to train a model)
-    if automl_ref is None:
-        pytest.skip("No pre-existing AutoML model found. Skipping test")
-
-    source = ml.TFLiteAutoMlSource(automl_ref)
-    tflite_format = ml.TFLiteFormat(model_source=source)
-    ml_model = ml.Model(
-        display_name=_random_identifier('TestModel_automl_'),
-        tags=['test_automl'],
-        model_format=tflite_format)
-    model = ml.create_model(model=ml_model)
-    yield model
-    _clean_up_model(model)
-
-@pytest.mark.skipif(not _AUTOML_ENABLED, reason='AutoML is required for this test.')
-def test_automl_model(automl_model):
-  # This test looks for a predefined automl model with display_name = 'admin_sdk_integ_test1'
-    automl_model.wait_for_unlocked()
-
-    check_model(automl_model, {
-        'display_name': automl_model.display_name,
-        'tags': ['test_automl'],
-    })
-    check_tflite_automl_format(automl_model)

tests/test_ml.py

@@ -121,18 +121,6 @@
 }
 TFLITE_FORMAT_2 = ml.TFLiteFormat.from_dict(TFLITE_FORMAT_JSON_2)
 
-AUTOML_MODEL_NAME = 'projects/111111111111/locations/us-central1/models/ICN7683346839371803263'
-AUTOML_MODEL_SOURCE = ml.TFLiteAutoMlSource(AUTOML_MODEL_NAME)
-TFLITE_FORMAT_JSON_3 = {
-    'automlModel': AUTOML_MODEL_NAME,
-    'sizeBytes': '3456789'
-}
-TFLITE_FORMAT_3 = ml.TFLiteFormat.from_dict(TFLITE_FORMAT_JSON_3)
-
-AUTOML_MODEL_NAME_2 = 'projects/2222222222/locations/us-central1/models/ICN2222222222222222222'
-AUTOML_MODEL_NAME_JSON_2 = {'automlModel': AUTOML_MODEL_NAME_2}
-AUTOML_MODEL_SOURCE_2 = ml.TFLiteAutoMlSource(AUTOML_MODEL_NAME_2)
-
 CREATED_UPDATED_MODEL_JSON_1 = {
     'name': MODEL_NAME_1,
     'displayName': DISPLAY_NAME_1,
@@ -423,14 +411,6 @@ def test_model_keyword_based_creation_and_setters(self):
             'tfliteModel': TFLITE_FORMAT_JSON_2
         }
 
-        model.model_format = TFLITE_FORMAT_3
-        assert model.as_dict() == {
-            'displayName': DISPLAY_NAME_2,
-            'tags': TAGS_2,
-            'tfliteModel': TFLITE_FORMAT_JSON_3
-        }
-
-
     def test_gcs_tflite_model_format_source_creation(self):
         model_source = ml.TFLiteGCSModelSource(gcs_tflite_uri=GCS_TFLITE_URI)
         model_format = ml.TFLiteFormat(model_source=model_source)
@@ -442,17 +422,6 @@ def test_gcs_tflite_model_format_source_creation(self):
             }
         }
 
-    def test_auto_ml_tflite_model_format_source_creation(self):
-        model_source = ml.TFLiteAutoMlSource(auto_ml_model=AUTOML_MODEL_NAME)
-        model_format = ml.TFLiteFormat(model_source=model_source)
-        model = ml.Model(display_name=DISPLAY_NAME_1, model_format=model_format)
-        assert model.as_dict() == {
-            'displayName': DISPLAY_NAME_1,
-            'tfliteModel': {
-                'automlModel': AUTOML_MODEL_NAME
-            }
-        }
-
     def test_source_creation_from_tflite_file(self):
         model_source = ml.TFLiteGCSModelSource.from_tflite_model_file(
             "my_model.tflite", "my_bucket")
@@ -466,13 +435,6 @@ def test_gcs_tflite_model_source_setters(self):
         assert model_source.gcs_tflite_uri == GCS_TFLITE_URI_2
         assert model_source.as_dict() == GCS_TFLITE_URI_JSON_2
 
-    def test_auto_ml_tflite_model_source_setters(self):
-        model_source = ml.TFLiteAutoMlSource(AUTOML_MODEL_NAME)
-        model_source.auto_ml_model = AUTOML_MODEL_NAME_2
-        assert model_source.auto_ml_model == AUTOML_MODEL_NAME_2
-        assert model_source.as_dict() == AUTOML_MODEL_NAME_JSON_2
-
-
     def test_model_format_setters(self):
         model_format = ml.TFLiteFormat(model_source=GCS_TFLITE_MODEL_SOURCE)
         model_format.model_source = GCS_TFLITE_MODEL_SOURCE_2
@@ -483,14 +445,6 @@ def test_model_format_setters(self):
             }
         }
 
-        model_format.model_source = AUTOML_MODEL_SOURCE
-        assert model_format.model_source == AUTOML_MODEL_SOURCE
-        assert model_format.as_dict() == {
-            'tfliteModel': {
-                'automlModel': AUTOML_MODEL_NAME
-            }
-        }
-
     def test_model_as_dict_for_upload(self):
         model_source = ml.TFLiteGCSModelSource(gcs_tflite_uri=GCS_TFLITE_URI)
         model_format = ml.TFLiteFormat(model_source=model_source)
@@ -576,23 +530,6 @@ def test_gcs_tflite_source_validation_errors(self, uri, exc_type):
             ml.TFLiteGCSModelSource(gcs_tflite_uri=uri)
         check_error(excinfo, exc_type)
 
-    @pytest.mark.parametrize('auto_ml_model, exc_type', [
-        (123, TypeError),
-        ('abc', ValueError),
-        ('/projects/123456/locations/us-central1/models/noLeadingSlash', ValueError),
-        ('projects/123546/models/ICN123456', ValueError),
-        ('projects//locations/us-central1/models/ICN123456', ValueError),
-        ('projects/123456/locations//models/ICN123456', ValueError),
-        ('projects/123456/locations/us-central1/models/', ValueError),
-        ('projects/ABC/locations/us-central1/models/ICN123456', ValueError),
-        ('projects/123456/locations/us-central1/models/@#$%^&', ValueError),
-        ('projects/123456/locations/us-cent/ral1/models/ICN123456', ValueError),
-    ])
-    def test_auto_ml_tflite_source_validation_errors(self, auto_ml_model, exc_type):
-        with pytest.raises(exc_type) as excinfo:
-            ml.TFLiteAutoMlSource(auto_ml_model=auto_ml_model)
-        check_error(excinfo, exc_type)
-
     def test_wait_for_unlocked_not_locked(self):
         model = ml.Model(display_name="not_locked")
         model.wait_for_unlocked()