
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


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

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


lowerCamelCase_  :	Tuple 				=					get_tests_dir("""fixtures""")

class     _UpperCamelCase			(   unittest.TestCase					):






   '''simple docstring'''

   def  lowerCAmelCase__		(    self	:    Optional[int] ):
       # A mock response for an HTTP head request to emulate server down
       UpperCamelCase_:							Union[str, Any]		=  mock.Mock()
       UpperCamelCase_:							Union[str, Any]		=  500
       UpperCamelCase_:							Any		=  {}
       UpperCamelCase_:							List[str]		=  HTTPError
       UpperCamelCase_:							Optional[int]		=  {}

       # Download this model to make sure it's in the cache.
       UpperCamelCase_:							str		=  ViTImageProcessor.from_pretrained("""hf-internal-testing/tiny-random-vit""" )
       # Under the mock environment we get a 500 error when trying to reach the model.
       with mock.patch("""requests.Session.request"""  ,		return_value=snake_case_ ) as mock_head:
           UpperCamelCase_:							List[Any]		=  ViTImageProcessor.from_pretrained("""hf-internal-testing/tiny-random-vit""" )
           # This check we did call the fake head request
           mock_head.assert_called()

   def  lowerCAmelCase__		(    self	:    Dict ):
       # This test is for deprecated behavior and can be removed in v5
       UpperCamelCase_:							List[Any]		=  ViTImageProcessor.from_pretrained(
           """https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json""" )




   def  lowerCAmelCase__		(    self	:    Optional[Any] ):
       with self.assertRaises(snake_case_ ):
           # config is in subfolder, the following should not work without specifying the subfolder
           UpperCamelCase_:							str		=  AutoImageProcessor.from_pretrained("""hf-internal-testing/stable-diffusion-all-variants""" )

       UpperCamelCase_:							str		=  AutoImageProcessor.from_pretrained(
           """hf-internal-testing/stable-diffusion-all-variants"""  ,		subfolder="""feature_extractor""" )

       self.assertIsNotNone(snake_case_ )




@is_staging_test
class     _UpperCamelCase			(   unittest.TestCase					):






   '''simple docstring'''

   @classmethod
   def  lowerCAmelCase__		(    cls	:    Any ):
       UpperCamelCase_:							List[str]		=  TOKEN
       HfFolder.save_token(snake_case_ )

   @classmethod
   def  lowerCAmelCase__		(    cls	:    Dict ):
       try:
           delete_repo(token=cls._token  ,		repo_id="""test-image-processor""" )
       except HTTPError:
           pass

       try:
           delete_repo(token=cls._token  ,		repo_id="""valid_org/test-image-processor-org""" )
       except HTTPError:
           pass

       try:
           delete_repo(token=cls._token  ,		repo_id="""test-dynamic-image-processor""" )
       except HTTPError:
           pass

   def  lowerCAmelCase__		(    self	:    List[str] ):
       UpperCamelCase_:							Union[str, Any]		=  ViTImageProcessor.from_pretrained(snake_case_ )
       image_processor.push_to_hub("""test-image-processor"""  ,		use_auth_token=self._token )

       UpperCamelCase_:							List[str]		=  ViTImageProcessor.from_pretrained(f'''{USER}/test-image-processor''' )
       for k, v in image_processor.__dict__.items():
           self.assertEqual(snake_case_  ,		getattr(snake_case_  ,		snake_case_ ) )

       # Reset repo
       delete_repo(token=self._token  ,		repo_id="""test-image-processor""" )

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
           image_processor.save_pretrained(
               snake_case_  ,		repo_id="""test-image-processor"""  ,		push_to_hub=snake_case_  ,		use_auth_token=self._token )

       UpperCamelCase_:							int		=  ViTImageProcessor.from_pretrained(f'''{USER}/test-image-processor''' )
       for k, v in image_processor.__dict__.items():
           self.assertEqual(snake_case_  ,		getattr(snake_case_  ,		snake_case_ ) )

   def  lowerCAmelCase__		(    self	:    str ):
       UpperCamelCase_:							Union[str, Any]		=  ViTImageProcessor.from_pretrained(snake_case_ )
       image_processor.push_to_hub("""valid_org/test-image-processor"""  ,		use_auth_token=self._token )

       UpperCamelCase_:							Dict		=  ViTImageProcessor.from_pretrained("""valid_org/test-image-processor""" )
       for k, v in image_processor.__dict__.items():
           self.assertEqual(snake_case_  ,		getattr(snake_case_  ,		snake_case_ ) )

       # Reset repo
       delete_repo(token=self._token  ,		repo_id="""valid_org/test-image-processor""" )

       # Push to hub via save_pretrained
       with tempfile.TemporaryDirectory() as tmp_dir:
           image_processor.save_pretrained(
               snake_case_  ,		repo_id="""valid_org/test-image-processor-org"""  ,		push_to_hub=snake_case_  ,		use_auth_token=self._token )

       UpperCamelCase_:							Optional[int]		=  ViTImageProcessor.from_pretrained("""valid_org/test-image-processor-org""" )
       for k, v in image_processor.__dict__.items():
           self.assertEqual(snake_case_  ,		getattr(snake_case_  ,		snake_case_ ) )




   def  lowerCAmelCase__		(    self	:    Optional[int] ):
       CustomImageProcessor.register_for_auto_class()
       UpperCamelCase_:							int		=  CustomImageProcessor.from_pretrained(snake_case_ )

       image_processor.push_to_hub("""test-dynamic-image-processor"""  ,		use_auth_token=self._token )

       # This has added the proper auto_map field to the config
       self.assertDictEqual(
           image_processor.auto_map  ,		{"""AutoImageProcessor""": """custom_image_processing.CustomImageProcessor"""}  ,		)

       UpperCamelCase_:							str		=  AutoImageProcessor.from_pretrained(
           f'''{USER}/test-dynamic-image-processor'''  ,		trust_remote_code=snake_case_ )
       # Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
       self.assertEqual(new_image_processor.__class__.__name__  ,		"""CustomImageProcessor""" )








import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


lowerCamelCase_  :	Any 				=					logging.get_logger(__name__)


lowerCamelCase_  :	Optional[int] 				=					{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowerCamelCase_  :	str 				=					{
    """vocab_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json""",
    },
    """added_tokens.json""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json""",
    },
    """merges_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase_  :	Union[str, Any] 				=					{
    """RUCAIBox/mvp""": 10_24,
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  List[Any]    =	VOCAB_FILES_NAMES
			__UpperCamelCase :  int    =	PRETRAINED_VOCAB_FILES_MAP
			__UpperCamelCase :  Any    =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__UpperCamelCase :  Any    =	["""input_ids""", """attention_mask"""]
			__UpperCamelCase :  int    =	MvpTokenizer

			def __init__(    self	:    Union[str, Any]  ,		snake_case_	:    Any=None  ,		snake_case_	:    Any=None  ,		snake_case_	:    Union[str, Any]=None  ,		snake_case_	:    Tuple="replace"  ,		snake_case_	:    Dict="<s>"  ,		snake_case_	:    Dict="</s>"  ,		snake_case_	:    Tuple="</s>"  ,		snake_case_	:    int="<s>"  ,		snake_case_	:    Tuple="<unk>"  ,		snake_case_	:    Optional[int]="<pad>"  ,		snake_case_	:    Any="<mask>"  ,		snake_case_	:    Union[str, Any]=False  ,		snake_case_	:    Optional[int]=True  ,		**snake_case_	:    Union[str, Any]  ,		):
							super().__init__(
							    snake_case_  ,		snake_case_  ,		tokenizer_file=snake_case_  ,		errors=snake_case_  ,		bos_token=snake_case_  ,		eos_token=snake_case_  ,		sep_token=snake_case_  ,		cls_token=snake_case_  ,		unk_token=snake_case_  ,		pad_token=snake_case_  ,		mask_token=snake_case_  ,		add_prefix_space=snake_case_  ,		trim_offsets=snake_case_  ,		**snake_case_  ,		)

							UpperCamelCase_:							Any		=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
							if pre_tok_state.get("""add_prefix_space"""  ,		snake_case_ ) != add_prefix_space:
											UpperCamelCase_:							str		=  getattr(snake_case_  ,		pre_tok_state.pop("""type""" ) )
											UpperCamelCase_:							int		=  add_prefix_space
											UpperCamelCase_:							int		=  pre_tok_class(**snake_case_ )

							UpperCamelCase_:							int		=  add_prefix_space

							# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
							UpperCamelCase_:							Tuple		=  """post_processor"""
							UpperCamelCase_:							Optional[int]		=  getattr(self.backend_tokenizer  ,		snake_case_  ,		snake_case_ )
							if tokenizer_component_instance:
											UpperCamelCase_:							Optional[int]		=  json.loads(tokenizer_component_instance.__getstate__() )

											# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
											if "sep" in state:
															UpperCamelCase_:							Union[str, Any]		=  tuple(state["""sep"""] )
											if "cls" in state:
															UpperCamelCase_:							List[Any]		=  tuple(state["""cls"""] )

											UpperCamelCase_:							List[str]		=  False

											if state.get("""add_prefix_space"""  ,		snake_case_ ) != add_prefix_space:
															UpperCamelCase_:							str		=  add_prefix_space
															UpperCamelCase_:							Union[str, Any]		=  True

											if state.get("""trim_offsets"""  ,		snake_case_ ) != trim_offsets:
															UpperCamelCase_:							Optional[int]		=  trim_offsets
															UpperCamelCase_:							Any		=  True

											if changes_to_apply:
															UpperCamelCase_:							Optional[int]		=  getattr(snake_case_  ,		state.pop("""type""" ) )
															UpperCamelCase_:							Union[str, Any]		=  component_class(**snake_case_ )
															setattr(self.backend_tokenizer  ,		snake_case_  ,		snake_case_ )

			@property
			def  lowerCAmelCase__		(    self	:    Union[str, Any] ):
							if self._mask_token is None:
											if self.verbose:
															logger.error("""Using mask_token, but it is not set yet.""" )
											return None
							return str(self._mask_token )

			@mask_token.setter
			def  lowerCAmelCase__		(    self	:    Union[str, Any]  ,		snake_case_	:    Dict ):
							UpperCamelCase_:							List[str]		=  AddedToken(snake_case_  ,		lstrip=snake_case_  ,		rstrip=snake_case_ ) if isinstance(snake_case_  ,		snake_case_ ) else value
							UpperCamelCase_:							Optional[int]		=  value

			def  lowerCAmelCase__		(    self	:    Optional[int]  ,		*snake_case_	:    Dict  ,		**snake_case_	:    Optional[int] ):
							UpperCamelCase_:							Optional[int]		=  kwargs.get("""is_split_into_words"""  ,		snake_case_ )

							if is_split_into_words and not self.add_prefix_space:
											raise ValueError(
											    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
											    """to use it with pretokenized inputs.""" )

							return super()._batch_encode_plus(*snake_case_  ,		**snake_case_ )

			def  lowerCAmelCase__		(    self	:    Union[str, Any]  ,		*snake_case_	:    Dict  ,		**snake_case_	:    Tuple ):
							UpperCamelCase_:							Any		=  kwargs.get("""is_split_into_words"""  ,		snake_case_ )

							if is_split_into_words and not self.add_prefix_space:
											raise ValueError(
											    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
											    """to use it with pretokenized inputs.""" )

							return super()._encode_plus(*snake_case_  ,		**snake_case_ )

			def  lowerCAmelCase__		(    self	:    Tuple  ,		snake_case_	:    str  ,		snake_case_	:    Optional[str] = None ):
							UpperCamelCase_:							Optional[int]		=  self._tokenizer.model.save(snake_case_  ,		name=snake_case_ )
							return tuple(snake_case_ )

			def  lowerCAmelCase__		(    self	:    Tuple  ,		snake_case_	:    Union[str, Any]  ,		snake_case_	:    Any=None ):
							UpperCamelCase_:							str		=  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
											return output

							return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




			def  lowerCAmelCase__		(    self	:    Any  ,		snake_case_	:    List[int]  ,		snake_case_	:    Optional[List[int]] = None ):
							UpperCamelCase_:							Tuple		=  [self.sep_token_id]
							UpperCamelCase_:							List[str]		=  [self.cls_token_id]

							if token_ids_a is None:
											return len(cls + token_ids_a + sep ) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]






