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change: Drop the feature to publish from an AutoML Model #663

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change: Drop the feature to publish from an AutoML Model #663

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1c6571b
Deprecating the feature to publish from an AutoML Model
pavelgj Nov 14, 2022
1c5166e
Removed unused import
pavelgj Nov 14, 2022
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33 changes: 0 additions & 33 deletions firebase_admin/ml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -386,9 +386,6 @@ 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:
return TFLiteAutoMlSource(auto_ml_model=auto_ml_model)
return None

@property
Expand Down Expand Up @@ -603,36 +600,6 @@ 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."""

def __init__(self, auto_ml_model, app=None):
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.

Expand Down
62 changes: 0 additions & 62 deletions integration/test_ml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,6 @@

import pytest

import firebase_admin
from firebase_admin import exceptions
from firebase_admin import ml
from tests import testutils
Expand All @@ -35,12 +34,6 @@
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)])
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -388,50 +373,3 @@ 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)
63 changes: 0 additions & 63 deletions tests/test_ml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -122,18 +122,6 @@
}
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,
Expand Down Expand Up @@ -417,14 +405,6 @@ 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)
Expand All @@ -436,17 +416,6 @@ 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")
Expand All @@ -460,13 +429,6 @@ 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
Expand All @@ -477,14 +439,6 @@ 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)
Expand Down Expand Up @@ -570,23 +524,6 @@ 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()
Expand Down