



"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_camembert import CamembertTokenizer
else:
			__SCREAMING_SNAKE_CASE  :						List[str]    							=      None


__SCREAMING_SNAKE_CASE  :						Tuple    							=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE  :						Tuple    							=      {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__SCREAMING_SNAKE_CASE  :						Any    							=      {
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

__SCREAMING_SNAKE_CASE  :						Optional[int]    							=      {
    '''camembert-base''': 5_1_2,
}

__SCREAMING_SNAKE_CASE  :						List[Any]    							=      '''▁'''


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					lowercase__   :       Union[str, Any]										= VOCAB_FILES_NAMES
					lowercase__   :       Dict										= PRETRAINED_VOCAB_FILES_MAP
					lowercase__   :       str										= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__   :       Dict										= ['input_ids', 'attention_mask']
					lowercase__   :       Tuple										= CamembertTokenizer

					def __init__(    self				,       lowerCamelCase__=None				,       lowerCamelCase__=None				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="<unk>"				,       lowerCamelCase__="<pad>"				,       lowerCamelCase__="<mask>"				,       lowerCamelCase__=["<s>NOTUSED", "</s>NOTUSED"]				,       **lowerCamelCase__				,       ):
									# Mask token behave like a normal word, i.e. include the space before it
									_lowerCamelCase        =				AddedToken(lowerCamelCase__				,       lstrip=lowerCamelCase__				,       rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__				,       lowerCamelCase__   ) else mask_token

									super().__init__(
									    lowerCamelCase__				,       tokenizer_file=lowerCamelCase__				,       bos_token=lowerCamelCase__				,       eos_token=lowerCamelCase__				,       sep_token=lowerCamelCase__				,       cls_token=lowerCamelCase__				,       unk_token=lowerCamelCase__				,       pad_token=lowerCamelCase__				,       mask_token=lowerCamelCase__				,       additional_special_tokens=lowerCamelCase__				,       **lowerCamelCase__				,       )

									_lowerCamelCase        =				vocab_file
									_lowerCamelCase        =				False if not self.vocab_file else True

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):

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

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				[self.sep_token_id]
									_lowerCamelCase        =				[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]





					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									if not self.can_save_slow_tokenizer:
													raise ValueError(
													    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
													    '''tokenizer.'''   )

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

									if os.path.abspath(self.vocab_file   ) != os.path.abspath(lowerCamelCase__   ):
													copyfile(self.vocab_file				,       lowerCamelCase__   )

									return (out_vocab_file,)





"""simple docstring"""
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
			if not (is_transformers_available() and is_torch_available()):
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
			from .pipeline_kandinsky import KandinskyPipeline
			from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
			from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
			from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
			from .text_encoder import MultilingualCLIP
