"""simple docstring"""


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase__			=    logging.get_logger(__name__)

UpperCAmelCase__			=    '▁'

UpperCAmelCase__			=    {'vocab_file': 'sentencepiece.bpe.model', 'monolingual_vocab_file': 'dict.txt'}

UpperCAmelCase__			=    {
    'vocab_file': {
        'vinai/bartpho-syllable': 'https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model',
    },
    'monolingual_vocab_file': {
        'vinai/bartpho-syllable': 'https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt',
    },
}

UpperCAmelCase__			=    {'vinai/bartpho-syllable': 1_0_2_4}


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	Tuple  				=				VOCAB_FILES_NAMES
    _snake_case  :	List[str]  				=				PRETRAINED_VOCAB_FILES_MAP
    _snake_case  :	Any  				=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _snake_case  :	List[Any]  				=				['''input_ids''', '''attention_mask''']


    def __init__(       self						:	str ,					__lowerCAmelCase						:	str ,					__lowerCAmelCase						:	List[Any] ,					__lowerCAmelCase						:	Any="<s>" ,					__lowerCAmelCase						:	Optional[int]="</s>" ,					__lowerCAmelCase						:	List[str]="</s>" ,					__lowerCAmelCase						:	str="<s>" ,					__lowerCAmelCase						:	Any="<unk>" ,					__lowerCAmelCase						:	Optional[int]="<pad>" ,					__lowerCAmelCase						:	str="<mask>" ,					__lowerCAmelCase						:	str = None ,					**__lowerCAmelCase						:	Dict ,					):
      _UpperCAmelCase    			=   AddedToken(lowerCamelCase_ ,					lstrip=lowerCamelCase_ ,					rstrip=lowerCamelCase_       ) if isinstance(lowerCamelCase_ ,					lowerCamelCase_       ) else mask_token

      _UpperCAmelCase    			=   {} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=lowerCamelCase_ ,					eos_token=lowerCamelCase_ ,					unk_token=lowerCamelCase_ ,					sep_token=lowerCamelCase_ ,					cls_token=lowerCamelCase_ ,					pad_token=lowerCamelCase_ ,					mask_token=lowerCamelCase_ ,					sp_model_kwargs=self.sp_model_kwargs ,					**lowerCamelCase_ ,					)

      _UpperCAmelCase    			=   vocab_file
      _UpperCAmelCase    			=   monolingual_vocab_file
      _UpperCAmelCase    			=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
      self.sp_model.Load(str(lowerCamelCase_       )       )

      # Load the reduced vocab

      # Keep order of special tokens for backward compatibility
      _UpperCAmelCase    			=   {}
      _UpperCAmelCase    			=   0
      for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
        if str(lowerCamelCase_       ) not in self.fairseq_tokens_to_ids:
          _UpperCAmelCase    			=   cnt
          cnt += 1
      with open(lowerCamelCase_ ,					"""r""" ,					encoding="""utf-8"""       ) as f:
        for line in f.readlines():
          _UpperCAmelCase    			=   line.strip().split()[0]
          _UpperCAmelCase    			=   len(self.fairseq_tokens_to_ids       )
      if str(lowerCamelCase_       ) not in self.fairseq_tokens_to_ids:
        _UpperCAmelCase    			=   len(self.fairseq_tokens_to_ids       )

      _UpperCAmelCase    			=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}


    def __getstate__(       self						:	Optional[int]       ):
      _UpperCAmelCase    			=   self.__dict__.copy()
      _UpperCAmelCase    			=   None
      _UpperCAmelCase    			=   self.sp_model.serialized_model_proto()
      return state


    def __setstate__(       self						:	Union[str, Any] ,					__lowerCAmelCase						:	List[str]       ):
      _UpperCAmelCase    			=   d

      # for backward compatibility
      if not hasattr(self ,					"""sp_model_kwargs"""       ):
        _UpperCAmelCase    			=   {}

      _UpperCAmelCase    			=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
      self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )


    def   lowerCAmelCase_	(       self						:	List[Any] ,					__lowerCAmelCase						:	str ,					__lowerCAmelCase						:	Union[str, Any] = None       ):



      if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _UpperCAmelCase    			=   [self.cls_token_id]
      _UpperCAmelCase    			=   [self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep


    def   lowerCAmelCase_	(       self						:	Optional[Any] ,					__lowerCAmelCase						:	Dict ,					__lowerCAmelCase						:	Union[str, Any] = None ,					__lowerCAmelCase						:	List[Any] = False       ):



      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=lowerCamelCase_ ,					token_ids_a=lowerCamelCase_ ,					already_has_special_tokens=lowerCamelCase_       )

      if token_ids_a is None:
        return [1] + ([0] * len(lowerCamelCase_       )) + [1]
      return [1] + ([0] * len(lowerCamelCase_       )) + [1, 1] + ([0] * len(lowerCamelCase_       )) + [1]


    def   lowerCAmelCase_	(       self						:	Any ,					__lowerCAmelCase						:	List[str] ,					__lowerCAmelCase						:	int = None       ):
      _UpperCAmelCase    			=   [self.sep_token_id]
      _UpperCAmelCase    			=   [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]


    @property
    def   lowerCAmelCase_	(       self						:	List[Any]       ):
      return len(self.fairseq_ids_to_tokens       )


    def   lowerCAmelCase_	(       self						:	Tuple       ):
      _UpperCAmelCase    			=   {self.convert_ids_to_tokens(lowerCamelCase_       ): i for i in range(self.vocab_size       )}
      vocab.update(self.added_tokens_encoder       )
      return vocab


    def   lowerCAmelCase_	(       self						:	Dict ,					__lowerCAmelCase						:	str       ):
      return self.sp_model.encode(lowerCamelCase_ ,					out_type=lowerCamelCase_       )


    def   lowerCAmelCase_	(       self						:	Dict ,					__lowerCAmelCase						:	int       ):



      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      else:
        return self.unk_token_id


    def   lowerCAmelCase_	(       self						:	List[str] ,					__lowerCAmelCase						:	Tuple       ):
      return self.fairseq_ids_to_tokens[index]


    def   lowerCAmelCase_	(       self						:	Dict ,					__lowerCAmelCase						:	List[Any]       ):
      _UpperCAmelCase    			=   ''''''.join(lowerCamelCase_       ).replace(lowerCamelCase_ ,					""" """       ).strip()
      return out_string


    def   lowerCAmelCase_	(       self						:	Any ,					__lowerCAmelCase						:	Dict ,					__lowerCAmelCase						:	List[Any] = None       ):



      if not os.path.isdir(lowerCamelCase_       ):
        logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''       )
        return
      _UpperCAmelCase    			=   os.path.join(
          lowerCamelCase_ ,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )
      _UpperCAmelCase    			=   os.path.join(
          lowerCamelCase_ ,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""monolingual_vocab_file"""] ,					)

      if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowerCamelCase_       ) and os.path.isfile(self.vocab_file       ):
        copyfile(self.vocab_file ,					lowerCamelCase_       )
      elif not os.path.isfile(self.vocab_file       ):
        with open(lowerCamelCase_ ,					"""wb"""       ) as fi:
          _UpperCAmelCase    			=   self.sp_model.serialized_model_proto()
          fi.write(lowerCamelCase_       )

      if os.path.abspath(self.monolingual_vocab_file       ) != os.path.abspath(
          lowerCamelCase_       ) and os.path.isfile(self.monolingual_vocab_file       ):
        copyfile(self.monolingual_vocab_file ,					lowerCamelCase_       )
      elif not os.path.isfile(self.monolingual_vocab_file       ):
        with open(lowerCamelCase_ ,					"""w""" ,					encoding="""utf-8"""       ) as fp:
          for token in self.fairseq_tokens_to_ids:
            if token not in self.all_special_tokens:
              fp.write(f'''{str(lowerCamelCase_       )} \n'''       )

      return out_vocab_file, out_monolingual_vocab_file

'''simple docstring'''

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


UpperCamelCase__  :						str					=      get_tests_dir('fixtures')


class 					_lowercase						(   unittest.TestCase ):
      '''simple docstring'''


      def 		lowerCAmelCase__       (					self				)      ->      int:



         '''simple docstring'''



         UpperCAmelCase__				:					Optional[int] 					=	mock.Mock()
         UpperCAmelCase__				:					Dict 					=	500
         UpperCAmelCase__				:					Optional[int] 					=	{}
         UpperCAmelCase__				:					List[str] 					=	HTTPError
         UpperCAmelCase__				:					Tuple 					=	{}

         # Download this model to make sure it's in the cache.
         UpperCAmelCase__				:					Any 					=	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=lowerCamelCase_				) as mock_head:
            UpperCAmelCase__				:					Tuple 					=	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				)      ->      Tuple:



         '''simple docstring'''



         UpperCAmelCase__				:					Dict 					=	ViTImageProcessor.from_pretrained(
             '''https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json'''				)




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



         '''simple docstring'''



         with self.assertRaises(lowerCamelCase_				):
            # config is in subfolder, the following should not work without specifying the subfolder
            UpperCAmelCase__				:					int 					=	AutoImageProcessor.from_pretrained('''hf-internal-testing/stable-diffusion-all-variants'''				)

         UpperCAmelCase__				:					Optional[Any] 					=	AutoImageProcessor.from_pretrained(
             '''hf-internal-testing/stable-diffusion-all-variants'''       ,subfolder='''feature_extractor'''				)

         self.assertIsNotNone(lowerCamelCase_				)




@is_staging_test
class 					_lowercase						(   unittest.TestCase ):
      '''simple docstring'''


      @classmethod
      def 		lowerCAmelCase__       (					cls				)      ->      Optional[Any]:



         '''simple docstring'''



         UpperCAmelCase__				:					Optional[int] 					=	TOKEN
         HfFolder.save_token(lowerCamelCase_				)




      @classmethod
      def 		lowerCAmelCase__       (					cls				)      ->      List[str]:



         '''simple docstring'''



         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				)      ->      Union[str, Any]:



         '''simple docstring'''



         UpperCAmelCase__				:					Optional[Any] 					=	ViTImageProcessor.from_pretrained(lowerCamelCase_				)
         image_processor.push_to_hub('''test-image-processor'''       ,use_auth_token=self._token				)

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

         # 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(
                lowerCamelCase_       ,repo_id='''test-image-processor'''       ,push_to_hub=lowerCamelCase_       ,use_auth_token=self._token				)

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




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



         '''simple docstring'''



         UpperCAmelCase__				:					Union[str, Any] 					=	ViTImageProcessor.from_pretrained(lowerCamelCase_				)
         image_processor.push_to_hub('''valid_org/test-image-processor'''       ,use_auth_token=self._token				)

         UpperCAmelCase__				:					Any 					=	ViTImageProcessor.from_pretrained('''valid_org/test-image-processor'''				)
         for k, v in image_processor.__dict__.items():
            self.assertEqual(lowerCamelCase_       ,getattr(lowerCamelCase_       ,lowerCamelCase_				)				)

         # 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(
                lowerCamelCase_       ,repo_id='''valid_org/test-image-processor-org'''       ,push_to_hub=lowerCamelCase_       ,use_auth_token=self._token				)

         UpperCAmelCase__				:					Any 					=	ViTImageProcessor.from_pretrained('''valid_org/test-image-processor-org'''				)
         for k, v in image_processor.__dict__.items():
            self.assertEqual(lowerCamelCase_       ,getattr(lowerCamelCase_       ,lowerCamelCase_				)				)




      def 		lowerCAmelCase__       (					self				)      ->      str:



         '''simple docstring'''



         CustomImageProcessor.register_for_auto_class()
         UpperCAmelCase__				:					List[str] 					=	CustomImageProcessor.from_pretrained(lowerCamelCase_				)

         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__				:					Any 					=	AutoImageProcessor.from_pretrained(
             f'''{USER}/test-dynamic-image-processor'''       ,trust_remote_code=lowerCamelCase_				)
         # 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'''				)




