



"""simple docstring"""






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				):




	'''simple docstring'''





	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str])							->			Any:

				"""simple docstring"""

				__lowerCAmelCase :    Tuple				=			0

	def 				_SCREAMING_SNAKE_CASE  (	self:						Any)							->			int:

				"""simple docstring"""

				__lowerCAmelCase :    Tuple				=			AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32")
				self.assertIsInstance(A__			,     A__)

	def 				_SCREAMING_SNAKE_CASE  (	self:						int)							->			Dict:

				"""simple docstring"""

				with tempfile.TemporaryDirectory() as tmpdirname:
							__lowerCAmelCase :    Optional[int]				=			Path(A__) / '''preprocessor_config.json'''
							__lowerCAmelCase :    List[str]				=			Path(A__) / '''config.json'''
							json.dump(
							    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}			,     open(A__			,     "w")			,     )
							json.dump({"model_type": "clip"}			,     open(A__			,     "w"))

							__lowerCAmelCase :    str				=			AutoImageProcessor.from_pretrained(A__)
							self.assertIsInstance(A__			,     A__)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Any)							->			Tuple:

				"""simple docstring"""

				with tempfile.TemporaryDirectory() as tmpdirname:
							__lowerCAmelCase :    Optional[Any]				=			Path(A__) / '''preprocessor_config.json'''
							__lowerCAmelCase :    List[Any]				=			Path(A__) / '''config.json'''
							json.dump(
							    {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}			,     open(A__			,     "w")			,     )
							json.dump({"model_type": "clip"}			,     open(A__			,     "w"))

							__lowerCAmelCase :    List[str]				=			AutoImageProcessor.from_pretrained(A__)
							self.assertIsInstance(A__			,     A__)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Any)							->			int:

				"""simple docstring"""

				with tempfile.TemporaryDirectory() as tmpdirname:
							__lowerCAmelCase :    Any				=			CLIPConfig()

							# Create a dummy config file with image_proceesor_type
							__lowerCAmelCase :    int				=			Path(A__) / '''preprocessor_config.json'''
							__lowerCAmelCase :    List[str]				=			Path(A__) / '''config.json'''
							json.dump(
							    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}			,     open(A__			,     "w")			,     )
							json.dump({"model_type": "clip"}			,     open(A__			,     "w"))

							# remove image_processor_type to make sure config.json alone is enough to load image processor locally
							__lowerCAmelCase :    Tuple				=			AutoImageProcessor.from_pretrained(A__).to_dict()

							config_dict.pop("image_processor_type")
							__lowerCAmelCase :    Optional[Any]				=			CLIPImageProcessor(**A__)

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

							__lowerCAmelCase :    str				=			AutoImageProcessor.from_pretrained(A__)

							# make sure private variable is not incorrectly saved
							__lowerCAmelCase :    Any				=			json.loads(config.to_json_string())
							self.assertTrue("_processor_class" not in dict_as_saved)

				self.assertIsInstance(A__			,     A__)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			Union[str, Any]:

				"""simple docstring"""

				with tempfile.TemporaryDirectory() as tmpdirname:
							__lowerCAmelCase :    Any				=			Path(A__) / '''preprocessor_config.json'''
							json.dump(
							    {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}			,     open(A__			,     "w")			,     )

							__lowerCAmelCase :    Any				=			AutoImageProcessor.from_pretrained(A__)
							self.assertIsInstance(A__			,     A__)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict)							->			Optional[int]:

				"""simple docstring"""

				with self.assertRaisesRegex(
				    A__			,     "clip-base is not a local folder and is not a valid model identifier"):
							__lowerCAmelCase :    Union[str, Any]				=			AutoImageProcessor.from_pretrained("clip-base")

	def 				_SCREAMING_SNAKE_CASE  (	self:						Tuple)							->			Dict:

				"""simple docstring"""

				with self.assertRaisesRegex(
				    A__			,     r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"):
							__lowerCAmelCase :    Optional[int]				=			AutoImageProcessor.from_pretrained(A__			,     revision="aaaaaa")

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[Any])							->			Any:

				"""simple docstring"""

				with self.assertRaisesRegex(
				    A__			,     "hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."			,     ):
							__lowerCAmelCase :    str				=			AutoImageProcessor.from_pretrained("hf-internal-testing/config-no-model")

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			Dict:

				"""simple docstring"""

				with self.assertRaises(A__):
							__lowerCAmelCase :    List[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(A__):
							__lowerCAmelCase :    Tuple				=			AutoImageProcessor.from_pretrained(
							    "hf-internal-testing/test_dynamic_image_processor"			,     trust_remote_code=A__)

				__lowerCAmelCase :    Dict				=			AutoImageProcessor.from_pretrained(
				    "hf-internal-testing/test_dynamic_image_processor"			,     trust_remote_code=A__)
				self.assertEqual(image_processor.__class__.__name__			,     "NewImageProcessor")

				# Test image processor can be reloaded.
				with tempfile.TemporaryDirectory() as tmp_dir:
							image_processor.save_pretrained(A__)
							__lowerCAmelCase :    Optional[Any]				=			AutoImageProcessor.from_pretrained(A__			,     trust_remote_code=A__)
				self.assertEqual(reloaded_image_processor.__class__.__name__			,     "NewImageProcessor")

	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict)							->			int:

				"""simple docstring"""

				try:
							AutoConfig.register("custom"			,     A__)
							AutoImageProcessor.register(A__			,     A__)
							# Trying to register something existing in the Transformers library will raise an error
							with self.assertRaises(A__):
										AutoImageProcessor.register(A__			,     A__)

							with tempfile.TemporaryDirectory() as tmpdirname:
										__lowerCAmelCase :    int				=			Path(A__) / '''preprocessor_config.json'''
										__lowerCAmelCase :    Optional[Any]				=			Path(A__) / '''config.json'''
										json.dump(
										    {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}			,     open(A__			,     "w")			,     )
										json.dump({"model_type": "clip"}			,     open(A__			,     "w"))

										__lowerCAmelCase :    Optional[Any]				=			CustomImageProcessor.from_pretrained(A__)

							# 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(A__)
										__lowerCAmelCase :    Tuple				=			AutoImageProcessor.from_pretrained(A__)
										self.assertIsInstance(A__			,     A__)

				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 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			List[Any]:

				"""simple docstring"""

				class      A__  (    __snake_case				):




					'''simple docstring'''





					SCREAMING_SNAKE_CASE        =      True

				try:
							AutoConfig.register("custom"			,     A__)
							AutoImageProcessor.register(A__			,     A__)
							# If remote code is not set, the default is to use local
							__lowerCAmelCase :    int				=			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.
							__lowerCAmelCase :    Optional[Any]				=			AutoImageProcessor.from_pretrained(
							    "hf-internal-testing/test_dynamic_image_processor"			,     trust_remote_code=A__)
							self.assertEqual(image_processor.__class__.__name__			,     "NewImageProcessor")
							self.assertTrue(image_processor.is_local)

							# If remote is enabled, we load from the Hub
							__lowerCAmelCase :    List[str]				=			AutoImageProcessor.from_pretrained(
							    "hf-internal-testing/test_dynamic_image_processor"			,     trust_remote_code=A__)
							self.assertEqual(image_processor.__class__.__name__			,     "NewImageProcessor")
							self.assertTrue(not hasattr(A__			,     "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]







from __future__ import annotations



def  a__ (__lowercase							:list					,  __lowercase							:int | None = None					,  __lowercase							:int | None = None   )		-> None:
				if start is None:
								_A	:				Optional[int]   =      0

				if end is None:
								_A	:				Union[str, Any]   =      len(__lowercase   ) - 1

				if start >= end:
								return

				_A	:				Union[str, Any]   =      (start + end) // 2

				slowsort(__lowercase					,  __lowercase					,  __lowercase   )
				slowsort(__lowercase					,  mid + 1					,  __lowercase   )

				if sequence[end] < sequence[mid]:
								_A  ,				_A	:				Optional[int]   =      sequence[mid], sequence[end]

				slowsort(__lowercase					,  __lowercase					,  end - 1   )


if __name__ == "__main__":
	from doctest import testmod

	testmod()



