





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        _SCREAMING_SNAKE_CASE						(     unittest.TestCase   ):







 '''simple docstring'''

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



   '''simple docstring'''



   lowerCamelCase__:				Union[str, Any]        =0

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->str:



   '''simple docstring'''



   lowerCamelCase__:				Any        =AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32")
   self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[str])	->Tuple:



   '''simple docstring'''



   with tempfile.TemporaryDirectory() as tmpdirname:
     lowerCamelCase__:				Dict        =Path(UpperCAmelCase_) / "preprocessor_config.json"
     lowerCamelCase__:				Union[str, Any]        =Path(UpperCAmelCase_) / "config.json"
     json.dump(
         {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}	,			open(UpperCAmelCase_	,			"w")	,			)
     json.dump({"model_type": "clip"}	,			open(UpperCAmelCase_	,			"w"))

     lowerCamelCase__:				List[str]        =AutoImageProcessor.from_pretrained(UpperCAmelCase_)
     self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

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



   '''simple docstring'''



   with tempfile.TemporaryDirectory() as tmpdirname:
     lowerCamelCase__:				Any        =Path(UpperCAmelCase_) / "preprocessor_config.json"
     lowerCamelCase__:				Any        =Path(UpperCAmelCase_) / "config.json"
     json.dump(
         {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}	,			open(UpperCAmelCase_	,			"w")	,			)
     json.dump({"model_type": "clip"}	,			open(UpperCAmelCase_	,			"w"))

     lowerCamelCase__:				Tuple        =AutoImageProcessor.from_pretrained(UpperCAmelCase_)
     self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->int:



   '''simple docstring'''



   with tempfile.TemporaryDirectory() as tmpdirname:
     lowerCamelCase__:				Union[str, Any]        =CLIPConfig()

     # Create a dummy config file with image_proceesor_type
     lowerCamelCase__:				Optional[Any]        =Path(UpperCAmelCase_) / "preprocessor_config.json"
     lowerCamelCase__:				List[Any]        =Path(UpperCAmelCase_) / "config.json"
     json.dump(
         {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}	,			open(UpperCAmelCase_	,			"w")	,			)
     json.dump({"model_type": "clip"}	,			open(UpperCAmelCase_	,			"w"))

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

     config_dict.pop("image_processor_type")
     lowerCamelCase__:				Union[str, Any]        =CLIPImageProcessor(**UpperCAmelCase_)

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

     lowerCamelCase__:				Dict        =AutoImageProcessor.from_pretrained(UpperCAmelCase_)

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

   self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple)	->Tuple:



   '''simple docstring'''



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

     lowerCamelCase__:				int        =AutoImageProcessor.from_pretrained(UpperCAmelCase_)
     self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->Any:



   '''simple docstring'''



   with self.assertRaisesRegex(
       UpperCAmelCase_	,			"clip-base is not a local folder and is not a valid model identifier"):
     lowerCamelCase__:				Dict        =AutoImageProcessor.from_pretrained("clip-base")

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->List[Any]:



   '''simple docstring'''



   with self.assertRaisesRegex(
       UpperCAmelCase_	,			R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"):
     lowerCamelCase__:				List[str]        =AutoImageProcessor.from_pretrained(UpperCAmelCase_	,			revision="aaaaaa")

 def 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any])	->List[Any]:



   '''simple docstring'''



   with self.assertRaisesRegex(
       UpperCAmelCase_	,			"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    :       Tuple)	->Optional[Any]:



   '''simple docstring'''



   with self.assertRaises(UpperCAmelCase_):
     lowerCamelCase__:				Optional[int]        =AutoImageProcessor.from_pretrained("hf-internal-testing/test_dynamic_image_processor")
   # If remote code is disabled, we can't load this config.
   with self.assertRaises(UpperCAmelCase_):
     lowerCamelCase__:				str        =AutoImageProcessor.from_pretrained(
         "hf-internal-testing/test_dynamic_image_processor"	,			trust_remote_code=UpperCAmelCase_)

   lowerCamelCase__:				int        =AutoImageProcessor.from_pretrained(
       "hf-internal-testing/test_dynamic_image_processor"	,			trust_remote_code=UpperCAmelCase_)
   self.assertEqual(image_processor.__class__.__name__	,			"NewImageProcessor")

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

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



   '''simple docstring'''



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

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

       lowerCamelCase__:				Dict        =CustomImageProcessor.from_pretrained(UpperCAmelCase_)

     # 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(UpperCAmelCase_)
       lowerCamelCase__:				List[str]        =AutoImageProcessor.from_pretrained(UpperCAmelCase_)
       self.assertIsInstance(UpperCAmelCase_	,			UpperCAmelCase_)

   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    :       int)	->int:



   '''simple docstring'''



   class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







    '''simple docstring'''
    lowercase_		=      True

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

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








def 					lowerCAmelCase_			(	__a     ,   __a		)					->		Tuple:







  """simple docstring"""





  assert x is not None
  assert y is not None

  lowerCamelCase__:				Any        =len(__a		)
  lowerCamelCase__:				int        =len(__a		)

  # declaring the array for storing the dp values
  lowerCamelCase__:				List[Any]        =[[0] * (n + 1) for _ in range(m + 1		)]  # noqa: E741

  for i in range(1     ,   m + 1		):
    for j in range(1     ,   n + 1		):
      lowerCamelCase__:				str        =1 if x[i - 1] == y[j - 1] else 0

      lowerCamelCase__:				str        =max(l[i - 1][j]     ,   l[i][j - 1]     ,   l[i - 1][j - 1] + match		)

  lowerCamelCase__:				Any        =""
  lowerCamelCase__  , lowerCamelCase__:				str        =m, n
  while i > 0 and j > 0:
    lowerCamelCase__:				Union[str, Any]        =1 if x[i - 1] == y[j - 1] else 0

    if l[i][j] == l[i - 1][j - 1] + match:
      if match == 1:
        lowerCamelCase__:				Any        =x[i - 1] + seq
      i -= 1
      j -= 1
    elif l[i][j] == l[i - 1][j]:
      i -= 1
    else:
      j -= 1

  return l[m][n], seq


if __name__ == "__main__":
     __A     =    "AGGTAB"
     __A     =    "GXTXAYB"
     __A     =    4
     __A     =    "GTAB"

     __A ,     __A     =    longest_common_subsequence(a, b)
     print("len =", ln, ", sub-sequence =", subseq)
     import doctest

     doctest.testmod()

