


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 		_snake_case  (				unittest.TestCase							):




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:Tuple										=	0




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:List[Any]										=	AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''   )
       self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       with tempfile.TemporaryDirectory() as tmpdirname:
             a						:Optional[Any]										=	Path(_lowerCamelCase   ) / '''preprocessor_config.json'''
             a						:Union[str, 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'''   )   )

             a						:Optional[int]										=	AutoImageProcessor.from_pretrained(_lowerCamelCase   )
             self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       # Ensure we can load the image processor from the feature extractor config
       with tempfile.TemporaryDirectory() as tmpdirname:
             a						:List[Any]										=	Path(_lowerCamelCase   ) / '''preprocessor_config.json'''
             a						: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'''   )   )

             a						:str										=	AutoImageProcessor.from_pretrained(_lowerCamelCase   )
             self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       with tempfile.TemporaryDirectory() as tmpdirname:
             a						:str										=	CLIPConfig()

             # Create a dummy config file with image_proceesor_type
             a						:Optional[int]										=	Path(_lowerCamelCase   ) / '''preprocessor_config.json'''
             a						: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'''   )   )

             # remove image_processor_type to make sure config.json alone is enough to load image processor locally
             a						:Union[str, Any]										=	AutoImageProcessor.from_pretrained(_lowerCamelCase   ).to_dict()

             config_dict.pop('''image_processor_type'''   )
             a						:Dict										=	CLIPImageProcessor(**_lowerCamelCase   )

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

             a						:List[str]										=	AutoImageProcessor.from_pretrained(_lowerCamelCase   )

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

       self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )




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

             a						:Dict										=	AutoImageProcessor.from_pretrained(_lowerCamelCase   )
             self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       with self.assertRaisesRegex(
           _lowerCamelCase ,  '''clip-base is not a local folder and is not a valid model identifier'''   ):
             a						:Optional[int]										=	AutoImageProcessor.from_pretrained('''clip-base'''   )




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




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       with self.assertRaisesRegex(
           _lowerCamelCase ,  '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.''' ,  ):
             a						:Optional[Any]										=	AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(_lowerCamelCase   ):
             a						: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(_lowerCamelCase   ):
             a						:Any										=	AutoImageProcessor.from_pretrained(
                 '''hf-internal-testing/test_dynamic_image_processor''' ,  trust_remote_code=_lowerCamelCase   )

       a						:Dict										=	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   )
             a						:List[Any]										=	AutoImageProcessor.from_pretrained(_lowerCamelCase ,  trust_remote_code=_lowerCamelCase   )
       self.assertEqual(reloaded_image_processor.__class__.__name__ ,  '''NewImageProcessor'''   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       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:
                   a						:Tuple										=	Path(_lowerCamelCase   ) / '''preprocessor_config.json'''
                   a						: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'''   )   )

                   a						:Optional[int]										=	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   )
                   a						:Union[str, Any]										=	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 	SCREAMING_SNAKE_CASE__    (		self   ):







       class 		_snake_case  (				_snake_case							):
        SCREAMING_SNAKE_CASE__				=	True

       try:
             AutoConfig.register('''custom''' ,  _lowerCamelCase   )
             AutoImageProcessor.register(_lowerCamelCase ,  _lowerCamelCase   )
             # If remote code is not set, the default is to use local
             a						: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.
             a						:Union[str, Any]										=	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
             a						:Tuple										=	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]









import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


snake_case    :   List[Any]	    =					get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')







class 		_snake_case  (				_snake_case						,   unittest.TestCase							):
 SCREAMING_SNAKE_CASE__				=	BartphoTokenizer
 SCREAMING_SNAKE_CASE__				=	False
 SCREAMING_SNAKE_CASE__				=	True




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       super().setUp()

       a						:Dict										=	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
       a						:Optional[Any]										=	dict(zip(_lowerCamelCase ,  range(len(_lowerCamelCase   )   )   )   )
       a						:Tuple										=	{'''unk_token''': '''<unk>'''}

       a						:Union[str, Any]										=	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES['''monolingual_vocab_file''']   )
       with open(self.monolingual_vocab_file ,  '''w''' ,  encoding='''utf-8'''   ) as fp:
             for token in vocab_tokens:
                   fp.write(F'''{token} {vocab_tokens[token]}\n'''   )

       a						:Any										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       tokenizer.save_pretrained(self.tmpdirname   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  **_lowerCamelCase   ):
       kwargs.update(self.special_tokens_map   )
       return BartphoTokenizer.from_pretrained(self.tmpdirname ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:int										=	'''This is a là test'''
       a						:str										=	'''This is a<unk><unk> test'''
       return input_text, output_text




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:List[str]										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       a						:Optional[Any]										=	'''This is a là test'''
       a						:Tuple										=	'''▁This ▁is ▁a ▁l à ▁t est'''.split()
       a						:int										=	tokenizer.tokenize(_lowerCamelCase   )
       self.assertListEqual(_lowerCamelCase ,  _lowerCamelCase   )

       a						:Union[str, Any]										=	tokens + [tokenizer.unk_token]
       a						:str										=	[4, 5, 6, 3, 3, 7, 8, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase   ) ,  _lowerCamelCase   )





