



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_albert import AlbertTokenizer
else:
						_snake_case		=  None

_snake_case		=  logging.get_logger(__name__)
_snake_case		=  {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

_snake_case		=  {
    "vocab_file": {
        "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/spiece.model",
        "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/spiece.model",
        "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model",
        "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model",
        "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/spiece.model",
        "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/spiece.model",
        "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model",
        "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json",
        "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json",
        "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json",
        "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json",
        "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json",
        "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json",
        "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json",
        "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json",
    },
}

_snake_case		=  {
    "albert-base-v1": 512,
    "albert-large-v1": 512,
    "albert-xlarge-v1": 512,
    "albert-xxlarge-v1": 512,
    "albert-base-v2": 512,
    "albert-large-v2": 512,
    "albert-xlarge-v2": 512,
    "albert-xxlarge-v2": 512,
}

_snake_case		=  "▁"



class   UpperCAmelCase_    (       a):
							lowerCamelCase__   			=		VOCAB_FILES_NAMES
							lowerCamelCase__   			=		PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase__   			=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase__   			=		AlbertTokenizer







							def __init__(   self,			__a=None,			__a=None,			__a=True,			__a=True,			__a=False,			__a="[CLS]",			__a="[SEP]",			__a="<unk>",			__a="[SEP]",			__a="<pad>",			__a="[CLS]",			__a="[MASK]",			**__a,			):

														'''simple docstring'''

														_lowerCAmelCase     :							List[str]    =    (
														    AddedToken(__a,			lstrip=__a,			rstrip=__a,			normalized=__a)
														    if isinstance(__a,			__a)
														    else mask_token
														)

														super().__init__(
														    __a,			tokenizer_file=__a,			do_lower_case=__a,			remove_space=__a,			keep_accents=__a,			bos_token=__a,			eos_token=__a,			unk_token=__a,			sep_token=__a,			pad_token=__a,			cls_token=__a,			mask_token=__a,			**__a,			)

														_lowerCAmelCase     :							List[str]    =    do_lower_case
														_lowerCAmelCase     :							Tuple    =    remove_space
														_lowerCAmelCase     :							Optional[Any]    =    keep_accents
														_lowerCAmelCase     :							Dict    =    vocab_file
														_lowerCAmelCase     :							Tuple    =    False if not self.vocab_file else True







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

														'''simple docstring'''

														_lowerCAmelCase     :							Tuple    =    [self.sep_token_id]
														_lowerCAmelCase     :							Union[str, Any]    =    [self.cls_token_id]
														if token_ids_a is None:
																					return cls + token_ids_a + sep
														return cls + token_ids_a + sep + token_ids_a + sep







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

														'''simple docstring'''

														_lowerCAmelCase     :							Dict    =    [self.sep_token_id]
														_lowerCAmelCase     :							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) * [0] + len(token_ids_a + sep) * [1]







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

														'''simple docstring'''

														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(__a):
																					logger.error(f"Vocabulary path ({save_directory}) should be a directory")
																					return
														_lowerCAmelCase     :							Tuple    =    os.path.join(
														    __a,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

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

														return (out_vocab_file,)

'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


SCREAMING_SNAKE_CASE_:     Union[str, Any]  =logging.get_logger(__name__)




class        __A      ( UpperCamelCase__	):



    def __init__(self    :    int   ,			*__a    :    Dict   ,			**__a    :    str ):
         warnings.warn(
             "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use CLIPImageProcessor instead."   ,			__a   ,			)
         super().__init__(*__a   ,			**__a )




