


from typing import TYPE_CHECKING

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


lowerCAmelCase       =							{'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfig']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase       =							[
			    'VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'ViTMAEForPreTraining',
			    'ViTMAELayer',
			    'ViTMAEModel',
			    'ViTMAEPreTrainedModel',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase       =							[
			    'TFViTMAEForPreTraining',
			    'TFViTMAEModel',
			    'TFViTMAEPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_vit_mae import (
						    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ViTMAEForPreTraining,
						    ViTMAELayer,
						    ViTMAEModel,
						    ViTMAEPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
			import sys

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








import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402





class        lowerCamelCase_							(      unittest.TestCase					):


 '''simple docstring'''







 def       lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_							=			0



 def       lowerCAmelCase_  (							self  :		int						):
       SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('openai/clip-vit-base-patch32'						)
       self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		Optional[int]						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		str						):
       # Ensure we can load the image processor from the feature extractor config
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		Union[str, Any]						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			CLIPConfig()

             # Create a dummy config file with image_proceesor_type
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             # remove image_processor_type to make sure config.json alone is enough to load image processor locally
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						).to_dict()

             config_dict.pop('image_processor_type'						)
             SCREAMING_SNAKE_CASE_							=			CLIPImageProcessor(**_lowerCAmelCase						)

             # save in new folder
             model_config.save_pretrained(_lowerCAmelCase						)
             config.save_pretrained(_lowerCAmelCase						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)

             # make sure private variable is not incorrectly saved
             SCREAMING_SNAKE_CASE_							=			json.loads(config.to_json_string()						)
             self.assertTrue('_processor_class' not in dict_as_saved						)

       self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		str						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		List[Any]						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				'clip-base is not a local folder and is not a valid model identifier'						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('clip-base'						)



 def       lowerCAmelCase_  (							self  :		List[Any]						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase				,				revision='aaaaaa'						)



 def       lowerCAmelCase_  (							self  :		str						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'				,				):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/config-no-model'						)



 def       lowerCAmelCase_  (							self  :		Tuple						):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor'						)
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
           'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)

       # Test image processor can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
             image_processor.save_pretrained(_lowerCAmelCase						)
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase				,				trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(reloaded_image_processor.__class__.__name__				,				'NewImageProcessor'						)



 def       lowerCAmelCase_  (							self  :		Optional[Any]						):
       try:
             AutoConfig.register('custom'				,				_lowerCAmelCase						)
             AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)
             # Trying to register something existing in the Transformers library will raise an error
             with self.assertRaises(_lowerCAmelCase						):
                   AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)

             with tempfile.TemporaryDirectory() as tmpdirname:
                   SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
                   SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
                   json.dump(
                       {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
                   json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

                   SCREAMING_SNAKE_CASE_							=			CustomImageProcessor.from_pretrained(_lowerCAmelCase						)

             # Now that the config is registered, it can be used as any other config with the auto-API
             with tempfile.TemporaryDirectory() as tmp_dir:
                   image_processor.save_pretrained(_lowerCAmelCase						)
                   SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
                   self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)

       finally:
             if "custom" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["custom"]
             if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                   del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]




 def       lowerCAmelCase_  (							self  :		Union[str, Any]						):





       class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


        '''simple docstring'''







        lowercase_				    =    True

       try:
             AutoConfig.register('custom'				,				_lowerCAmelCase						)
             AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)
             # If remote code is not set, the default is to use local
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor'						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(image_processor.is_local						)

             # If remote code is disabled, we load the local one.
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(image_processor.is_local						)

             # If remote is enabled, we load from the Hub
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(not hasattr(_lowerCAmelCase				,				'is_local'						)						)

       finally:
             if "custom" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["custom"]
             if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                   del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]