




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 AutoFeatureExtractor, WavaVecaFeatureExtractor
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_feature_extraction import CustomFeatureExtractor  # noqa E402


lowerCamelCase__			:       Dict         =							get_tests_dir('fixtures')





class 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 def 				lowerCAmelCase_  (							self  :		Any						):
       # A mock response for an HTTP head request to emulate server down
       SCREAMING_SNAKE_CASE_     						=      mock.Mock()
       SCREAMING_SNAKE_CASE_     						=      500
       SCREAMING_SNAKE_CASE_     						=      {}
       SCREAMING_SNAKE_CASE_     						=      HTTPError
       SCREAMING_SNAKE_CASE_     						=      {}

       # Download this model to make sure it's in the cache.
       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'						)
       # Under the mock environment we get a 500 error when trying to reach the model.
       with mock.patch('requests.Session.request'    ,    return_value=_lowerCAmelCase						) as mock_head:
             SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained('hf-internal-testing/tiny-random-wav2vec2'						)
             # This check we did call the fake head request
             mock_head.assert_called()




 def 				lowerCAmelCase_  (							self  :		Optional[Any]						):
       # This test is for deprecated behavior and can be removed in v5
       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained(
           'https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json'						)





@is_staging_test
class 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 @classmethod
 def 				lowerCAmelCase_  (							cls  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      TOKEN
       HfFolder.save_token(_lowerCAmelCase						)



 @classmethod
 def 				lowerCAmelCase_  (							cls  :		str						):
       try:
             delete_repo(token=cls._token    ,    repo_id='test-feature-extractor'						)
       except HTTPError:
             pass

       try:
             delete_repo(token=cls._token    ,    repo_id='valid_org/test-feature-extractor-org'						)
       except HTTPError:
             pass

       try:
             delete_repo(token=cls._token    ,    repo_id='test-dynamic-feature-extractor'						)
       except HTTPError:
             pass



 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained(_lowerCAmelCase						)
       feature_extractor.push_to_hub('test-feature-extractor'    ,    use_auth_token=self._token						)

       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained(F"{USER}/test-feature-extractor"						)
       for k, v in feature_extractor.__dict__.items():
             self.assertEqual(_lowerCAmelCase    ,    getattr(_lowerCAmelCase    ,    _lowerCAmelCase						)						)

       # Reset repo
       delete_repo(token=self._token    ,    repo_id='test-feature-extractor'						)

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
             feature_extractor.save_pretrained(
                 _lowerCAmelCase    ,    repo_id='test-feature-extractor'    ,    push_to_hub=_lowerCAmelCase    ,    use_auth_token=self._token						)

       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained(F"{USER}/test-feature-extractor"						)
       for k, v in feature_extractor.__dict__.items():
             self.assertEqual(_lowerCAmelCase    ,    getattr(_lowerCAmelCase    ,    _lowerCAmelCase						)						)



 def 				lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained(_lowerCAmelCase						)
       feature_extractor.push_to_hub('valid_org/test-feature-extractor'    ,    use_auth_token=self._token						)

       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor'						)
       for k, v in feature_extractor.__dict__.items():
             self.assertEqual(_lowerCAmelCase    ,    getattr(_lowerCAmelCase    ,    _lowerCAmelCase						)						)

       # Reset repo
       delete_repo(token=self._token    ,    repo_id='valid_org/test-feature-extractor'						)

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
             feature_extractor.save_pretrained(
                 _lowerCAmelCase    ,    repo_id='valid_org/test-feature-extractor-org'    ,    push_to_hub=_lowerCAmelCase    ,    use_auth_token=self._token						)

       SCREAMING_SNAKE_CASE_     						=      WavaVecaFeatureExtractor.from_pretrained('valid_org/test-feature-extractor-org'						)
       for k, v in feature_extractor.__dict__.items():
             self.assertEqual(_lowerCAmelCase    ,    getattr(_lowerCAmelCase    ,    _lowerCAmelCase						)						)




 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       CustomFeatureExtractor.register_for_auto_class()
       SCREAMING_SNAKE_CASE_     						=      CustomFeatureExtractor.from_pretrained(_lowerCAmelCase						)

       feature_extractor.push_to_hub('test-dynamic-feature-extractor'    ,    use_auth_token=self._token						)

       # This has added the proper auto_map field to the config
       self.assertDictEqual(
           feature_extractor.auto_map    ,    {'AutoFeatureExtractor': 'custom_feature_extraction.CustomFeatureExtractor'}    ,    )

       SCREAMING_SNAKE_CASE_     						=      AutoFeatureExtractor.from_pretrained(
           F"{USER}/test-dynamic-feature-extractor"    ,    trust_remote_code=_lowerCAmelCase						)
       # Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
       self.assertEqual(new_feature_extractor.__class__.__name__    ,    'CustomFeatureExtractor'						)











import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowerCamelCase__			:       Dict         =							logging.get_logger(__name__)





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 def __init__(							self  :		List[Any]    ,    *_lowerCAmelCase  :		List[str]    ,    **_lowerCAmelCase  :		Optional[int]						):
       warnings.warn(
           'The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use LayoutLMv2ImageProcessor instead.'    ,    _lowerCAmelCase    ,    )
       super().__init__(*_lowerCAmelCase    ,    **_lowerCAmelCase						)