





# Lint as: python3
import itertools
import os
import re


lowerCAmelCase							:       List[Any]					 =	re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowerCAmelCase							:       Tuple					 =	re.compile(r"""([a-z\d])([A-Z])""")

lowerCAmelCase							:       Optional[int]					 =	re.compile(r"""(?<!_)_(?!_)""")
lowerCAmelCase							:       Tuple					 =	re.compile(r"""(_{2,})""")

lowerCAmelCase							:       str					 =	r"""^\w+(\.\w+)*$"""

lowerCAmelCase							:       List[Any]					 =	r"""<>:/\|?*"""






def 		lowerCAmelCase  (	UpperCamelCase__   :   Optional[Any]					)      ->    Union[str, Any]:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				str           =   _uppercase_uppercase_re.sub(R'''\1_\2'''       ,			UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				Any           =   _lowercase_uppercase_re.sub(R'''\1_\2'''       ,			UpperCamelCase__					)
						return name.lower()






def 		lowerCAmelCase  (	UpperCamelCase__   :   Tuple					)      ->    Union[str, Any]:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				List[str]           =   _single_underscore_re.split(UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				str           =   [_multiple_underscores_re.split(UpperCamelCase__					) for n in name]
						return "".join(n.capitalize() for n in itertools.chain.from_iterable(UpperCamelCase__					) if n != ''''''					)






def 		lowerCAmelCase  (	UpperCamelCase__   :   Optional[Any]					)      ->    Union[str, Any]:

						"""simple docstring"""





						if os.path.basename(UpperCamelCase__					) != name:
												raise ValueError(F"""Should be a dataset name, not a path: {name}"""					)
						return camelcase_to_snakecase(UpperCamelCase__					)






def 		lowerCAmelCase  (	UpperCamelCase__   :   Union[str, Any]       ,			UpperCamelCase__   :   Optional[int]					)      ->    List[Any]:

						"""simple docstring"""





						if os.path.basename(UpperCamelCase__					) != name:
												raise ValueError(F"""Should be a dataset name, not a path: {name}"""					)
						if not re.match(_split_re       ,			UpperCamelCase__					):
												raise ValueError(F"""Split name should match '{_split_re}'' but got '{split}'."""					)
						return F"""{filename_prefix_for_name(UpperCamelCase__					)}-{split}"""






def 		lowerCAmelCase  (	UpperCamelCase__   :   Any       ,			UpperCamelCase__   :   List[Any]       ,			UpperCamelCase__   :   Any       ,			UpperCamelCase__   :   int=None					)      ->    Optional[Any]:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				List[Any]           =   filename_prefix_for_split(UpperCamelCase__       ,			UpperCamelCase__					)
						if filetype_suffix:
												prefix += F""".{filetype_suffix}"""
						__SCREAMING_SNAKE_CASE:				Tuple           =   os.path.join(UpperCamelCase__       ,			UpperCamelCase__					)
						return F"""{filepath}*"""






def 		lowerCAmelCase  (	UpperCamelCase__   :   Dict       ,			UpperCamelCase__   :   int       ,			UpperCamelCase__   :   List[str]       ,			UpperCamelCase__   :   Union[str, Any]=None       ,			UpperCamelCase__   :   Union[str, Any]=None					)      ->    int:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   filename_prefix_for_split(UpperCamelCase__       ,			UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				int           =   os.path.join(UpperCamelCase__       ,			UpperCamelCase__					)

						if shard_lengths:
												__SCREAMING_SNAKE_CASE:				str           =   len(UpperCamelCase__					)
												__SCREAMING_SNAKE_CASE:				Tuple           =   [F"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(UpperCamelCase__					)]
												if filetype_suffix:
																		__SCREAMING_SNAKE_CASE:				str           =   [filename + F""".{filetype_suffix}""" for filename in filenames]
												return filenames
						else:
												__SCREAMING_SNAKE_CASE:				List[str]           =   prefix
												if filetype_suffix:
																		filename += F""".{filetype_suffix}"""
												return [filename]










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 				a			(      unittest.TestCase			):






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[int]           =   0






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				List[str]           =   AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''					)
										self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																__SCREAMING_SNAKE_CASE:				List[str]           =   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:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				int           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																__SCREAMING_SNAKE_CASE:				Tuple           =   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:				str           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				int           =   CLIPConfig()

																# Create a dummy config file with image_proceesor_type
																__SCREAMING_SNAKE_CASE:				Any           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   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:				Any           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					).to_dict()

																config_dict.pop('''image_processor_type'''					)
																__SCREAMING_SNAKE_CASE:				List[str]           =   CLIPImageProcessor(**_lowerCAmelCase					)

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

																__SCREAMING_SNAKE_CASE:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)

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

										self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with tempfile.TemporaryDirectory() as tmpdirname:
																__SCREAMING_SNAKE_CASE:				Optional[int]           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																json.dump(
																    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}			, open(_lowerCAmelCase			, '''w'''					)			, )

																__SCREAMING_SNAKE_CASE:				int           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase					)
																self.assertIsInstance(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaisesRegex(
										    _lowerCAmelCase			, '''clip-base is not a local folder and is not a valid model identifier'''					):
																__SCREAMING_SNAKE_CASE:				Tuple           =   AutoImageProcessor.from_pretrained('''clip-base'''					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaisesRegex(
										    _lowerCAmelCase			, R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''					):
																__SCREAMING_SNAKE_CASE:				Dict           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase			, revision='''aaaaaa'''					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




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






				def 			snake_case_    (  self					):

										"""simple docstring"""




										with self.assertRaises(_lowerCAmelCase					):
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   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:				Any           =   AutoImageProcessor.from_pretrained(
																    '''hf-internal-testing/test_dynamic_image_processor'''			, trust_remote_code=_lowerCAmelCase					)

										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   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:				List[str]           =   AutoImageProcessor.from_pretrained(_lowerCAmelCase			, trust_remote_code=_lowerCAmelCase					)
										self.assertEqual(reloaded_image_processor.__class__.__name__			, '''NewImageProcessor'''					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										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:				Optional[int]           =   Path(_lowerCAmelCase					) / '''preprocessor_config.json'''
																						__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   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:				List[str]           =   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:				int           =   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 			snake_case_    (  self					):

										"""simple docstring"""




										class 				a			(      __lowercase			):
														SCREAMING_SNAKE_CASE__     :   Tuple		      =     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:				str           =   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:				Tuple           =   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:				Any           =   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]



