transformers/tests/test_image_processing_utils.py

149 lines
6.0 KiB
Python

# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test
sys.path.append(str(Path(__file__).parent.parent / "utils"))
from test_module.custom_image_processing import CustomImageProcessor # noqa E402
SAMPLE_IMAGE_PROCESSING_CONFIG_DIR = get_tests_dir("fixtures")
class ImageProcessorUtilTester(unittest.TestCase):
def test_cached_files_are_used_when_internet_is_down(self):
# A mock response for an HTTP head request to emulate server down
response_mock = mock.Mock()
response_mock.status_code = 500
response_mock.headers = {}
response_mock.raise_for_status.side_effect = HTTPError
response_mock.json.return_value = {}
# Download this model to make sure it's in the cache.
_ = ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit")
# Under the mock environment we get a 500 error when trying to reach the model.
with mock.patch("requests.Session.request", return_value=response_mock) as mock_head:
_ = ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit")
# This check we did call the fake head request
mock_head.assert_called()
def test_image_processor_from_pretrained_subfolder(self):
with self.assertRaises(OSError):
# config is in subfolder, the following should not work without specifying the subfolder
_ = AutoImageProcessor.from_pretrained("hf-internal-testing/stable-diffusion-all-variants")
config = AutoImageProcessor.from_pretrained(
"hf-internal-testing/stable-diffusion-all-variants", subfolder="feature_extractor"
)
self.assertIsNotNone(config)
@is_staging_test
class ImageProcessorPushToHubTester(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls._token = TOKEN
HfFolder.save_token(TOKEN)
@classmethod
def tearDownClass(cls):
try:
delete_repo(token=cls._token, repo_id="test-image-processor")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="valid_org/test-image-processor-org")
except HTTPError:
pass
try:
delete_repo(token=cls._token, repo_id="test-dynamic-image-processor")
except HTTPError:
pass
def test_push_to_hub(self):
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("test-image-processor", token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained(f"{USER}/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
# Reset repo
delete_repo(token=self._token, repo_id="test-image-processor")
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
image_processor.save_pretrained(
tmp_dir, repo_id="test-image-processor", push_to_hub=True, token=self._token
)
new_image_processor = ViTImageProcessor.from_pretrained(f"{USER}/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
def test_push_to_hub_in_organization(self):
image_processor = ViTImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("valid_org/test-image-processor", token=self._token)
new_image_processor = ViTImageProcessor.from_pretrained("valid_org/test-image-processor")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
# Reset repo
delete_repo(token=self._token, repo_id="valid_org/test-image-processor")
# Push to hub via save_pretrained
with tempfile.TemporaryDirectory() as tmp_dir:
image_processor.save_pretrained(
tmp_dir, repo_id="valid_org/test-image-processor-org", push_to_hub=True, token=self._token
)
new_image_processor = ViTImageProcessor.from_pretrained("valid_org/test-image-processor-org")
for k, v in image_processor.__dict__.items():
self.assertEqual(v, getattr(new_image_processor, k))
def test_push_to_hub_dynamic_image_processor(self):
CustomImageProcessor.register_for_auto_class()
image_processor = CustomImageProcessor.from_pretrained(SAMPLE_IMAGE_PROCESSING_CONFIG_DIR)
image_processor.push_to_hub("test-dynamic-image-processor", token=self._token)
# This has added the proper auto_map field to the config
self.assertDictEqual(
image_processor.auto_map,
{"AutoImageProcessor": "custom_image_processing.CustomImageProcessor"},
)
new_image_processor = AutoImageProcessor.from_pretrained(
f"{USER}/test-dynamic-image-processor", trust_remote_code=True
)
# Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
self.assertEqual(new_image_processor.__class__.__name__, "CustomImageProcessor")