



'''simple docstring'''



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


lowerCAmelCase	:		Optional[int]				=   get_tests_dir('''fixtures''')






class 					UpperCAmelCase__	(		unittest.TestCase ):



					def        UpperCAmelCase_ (    self     )     ->			Optional[int]:
						# A mock response for an HTTP head request to emulate server down
						__lowerCAmelCase												=  mock.Mock()
						__lowerCAmelCase												=  500
						__lowerCAmelCase												=  {}
						__lowerCAmelCase												=  HTTPError
						__lowerCAmelCase												=  {}

						# Download this model to make sure it's in the cache.
						__lowerCAmelCase												=  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=UpperCamelCase     ) as mock_head:
							__lowerCAmelCase												=  ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit"     )
							# This check we did call the fake head request
							mock_head.assert_called()



					def        UpperCAmelCase_ (    self     )     ->			Any:
						# This test is for deprecated behavior and can be removed in v5
						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained(
						    "https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json"     )



					def        UpperCAmelCase_ (    self     )     ->			str:
						with self.assertRaises(UpperCamelCase     ):
							# config is in subfolder, the following should not work without specifying the subfolder
							__lowerCAmelCase												=  AutoImageProcessor.from_pretrained("hf-internal-testing/stable-diffusion-all-variants"     )

						__lowerCAmelCase												=  AutoImageProcessor.from_pretrained(
						    "hf-internal-testing/stable-diffusion-all-variants"			,				subfolder="feature_extractor"     )

						self.assertIsNotNone(UpperCamelCase     )






@is_staging_test
class 					UpperCAmelCase__	(		unittest.TestCase ):



					@classmethod
					def        UpperCAmelCase_ (    cls     )     ->			int:
						__lowerCAmelCase												=  TOKEN
						HfFolder.save_token(UpperCamelCase     )



					@classmethod
					def        UpperCAmelCase_ (    cls     )     ->			Tuple:
						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        UpperCAmelCase_ (    self     )     ->			List[str]:
						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained(UpperCamelCase     )
						image_processor.push_to_hub("test-image-processor"			,				use_auth_token=self._token     )

						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained(F'''{USER}/test-image-processor'''     )
						for k, v in image_processor.__dict__.items():
							self.assertEqual(UpperCamelCase			,				getattr(UpperCamelCase			,				UpperCamelCase     )     )

						# 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(
							    UpperCamelCase			,				repo_id="test-image-processor"			,				push_to_hub=UpperCamelCase			,				use_auth_token=self._token     )

						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained(F'''{USER}/test-image-processor'''     )
						for k, v in image_processor.__dict__.items():
							self.assertEqual(UpperCamelCase			,				getattr(UpperCamelCase			,				UpperCamelCase     )     )



					def        UpperCAmelCase_ (    self     )     ->			Optional[int]:
						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained(UpperCamelCase     )
						image_processor.push_to_hub("valid_org/test-image-processor"			,				use_auth_token=self._token     )

						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained("valid_org/test-image-processor"     )
						for k, v in image_processor.__dict__.items():
							self.assertEqual(UpperCamelCase			,				getattr(UpperCamelCase			,				UpperCamelCase     )     )

						# 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(
							    UpperCamelCase			,				repo_id="valid_org/test-image-processor-org"			,				push_to_hub=UpperCamelCase			,				use_auth_token=self._token     )

						__lowerCAmelCase												=  ViTImageProcessor.from_pretrained("valid_org/test-image-processor-org"     )
						for k, v in image_processor.__dict__.items():
							self.assertEqual(UpperCamelCase			,				getattr(UpperCamelCase			,				UpperCamelCase     )     )



					def        UpperCAmelCase_ (    self     )     ->			int:
						CustomImageProcessor.register_for_auto_class()
						__lowerCAmelCase												=  CustomImageProcessor.from_pretrained(UpperCamelCase     )

						image_processor.push_to_hub("test-dynamic-image-processor"			,				use_auth_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"}			,				)

						__lowerCAmelCase												=  AutoImageProcessor.from_pretrained(
						    F'''{USER}/test-dynamic-image-processor'''			,				trust_remote_code=UpperCamelCase     )
						# 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"     )




'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase	:		Union[str, Any]				=   {
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   ['''DistilBertTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   [
	    '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DistilBertForMaskedLM''',
	    '''DistilBertForMultipleChoice''',
	    '''DistilBertForQuestionAnswering''',
	    '''DistilBertForSequenceClassification''',
	    '''DistilBertForTokenClassification''',
	    '''DistilBertModel''',
	    '''DistilBertPreTrainedModel''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		List[str]				=   [
	    '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFDistilBertForMaskedLM''',
	    '''TFDistilBertForMultipleChoice''',
	    '''TFDistilBertForQuestionAnswering''',
	    '''TFDistilBertForSequenceClassification''',
	    '''TFDistilBertForTokenClassification''',
	    '''TFDistilBertMainLayer''',
	    '''TFDistilBertModel''',
	    '''TFDistilBertPreTrainedModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Optional[int]				=   [
	    '''FlaxDistilBertForMaskedLM''',
	    '''FlaxDistilBertForMultipleChoice''',
	    '''FlaxDistilBertForQuestionAnswering''',
	    '''FlaxDistilBertForSequenceClassification''',
	    '''FlaxDistilBertForTokenClassification''',
	    '''FlaxDistilBertModel''',
	    '''FlaxDistilBertPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_distilbert import (
	    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DistilBertConfig,
	    DistilBertOnnxConfig,
	)
	from .tokenization_distilbert import DistilBertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_distilbert_fast import DistilBertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_distilbert import (
		    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DistilBertForMaskedLM,
		    DistilBertForMultipleChoice,
		    DistilBertForQuestionAnswering,
		    DistilBertForSequenceClassification,
		    DistilBertForTokenClassification,
		    DistilBertModel,
		    DistilBertPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_distilbert import (
		    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDistilBertForMaskedLM,
		    TFDistilBertForMultipleChoice,
		    TFDistilBertForQuestionAnswering,
		    TFDistilBertForSequenceClassification,
		    TFDistilBertForTokenClassification,
		    TFDistilBertMainLayer,
		    TFDistilBertModel,
		    TFDistilBertPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_distilbert import (
		    FlaxDistilBertForMaskedLM,
		    FlaxDistilBertForMultipleChoice,
		    FlaxDistilBertForQuestionAnswering,
		    FlaxDistilBertForSequenceClassification,
		    FlaxDistilBertForTokenClassification,
		    FlaxDistilBertModel,
		    FlaxDistilBertPreTrainedModel,
		)

else:
	import sys

	lowerCAmelCase	:		List[str]				=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)