





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_xlnet import XLNetTokenizer
else:
							UpperCAmelCase__  :     Tuple   			=None


UpperCAmelCase__  :     Any   			=logging.get_logger(__name__)

UpperCAmelCase__  :     Any   			={'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase__  :     Dict   			={
    '''vocab_file''': {
        '''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model''',
        '''xlnet-large-cased''': '''https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/tokenizer.json''',
        '''xlnet-large-cased''': '''https://huggingface.co/xlnet-large-cased/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase__  :     Tuple   			={
    '''xlnet-base-cased''': None,
    '''xlnet-large-cased''': None,
}

UpperCAmelCase__  :     Any   			='''▁'''

# Segments (not really needed)
UpperCAmelCase__  :     str   			=0
UpperCAmelCase__  :     Any   			=1
UpperCAmelCase__  :     Optional[int]   			=2
UpperCAmelCase__  :     Optional[Any]   			=3
UpperCAmelCase__  :     int   			=4

class  __A       (  A__      ):
				__A								=			VOCAB_FILES_NAMES
				__A								=			PRETRAINED_VOCAB_FILES_MAP
				__A								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__A								=			'left'
				__A								=			XLNetTokenizer


				def __init__(						self				,	UpperCAmelCase_=None				,	UpperCAmelCase_=None				,	UpperCAmelCase_=False				,	UpperCAmelCase_=True				,	UpperCAmelCase_=False				,	UpperCAmelCase_="<s>"				,	UpperCAmelCase_="</s>"				,	UpperCAmelCase_="<unk>"				,	UpperCAmelCase_="<sep>"				,	UpperCAmelCase_="<pad>"				,	UpperCAmelCase_="<cls>"				,	UpperCAmelCase_="<mask>"				,	UpperCAmelCase_=["<eop>", "<eod>"]				,	**UpperCAmelCase_				,	):
								# 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__(
								    vocab_file=lowerCamelCase__				,	tokenizer_file=lowerCamelCase__				,	do_lower_case=lowerCamelCase__				,	remove_space=lowerCamelCase__				,	keep_accents=lowerCamelCase__				,	bos_token=lowerCamelCase__				,	eos_token=lowerCamelCase__				,	unk_token=lowerCamelCase__				,	sep_token=lowerCamelCase__				,	pad_token=lowerCamelCase__				,	cls_token=lowerCamelCase__				,	mask_token=lowerCamelCase__				,	additional_special_tokens=lowerCamelCase__				,	**lowerCamelCase__				,	)

								lowerCamelCase			=3
								lowerCamelCase			=do_lower_case
								lowerCamelCase			=remove_space
								lowerCamelCase			=keep_accents
								lowerCamelCase			=vocab_file
								lowerCamelCase			=False if not self.vocab_file else True


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = None							):
								lowerCamelCase			=[self.sep_token_id]
								lowerCamelCase			=[self.cls_token_id]
								if token_ids_a is None:
												return token_ids_a + sep + cls
								return token_ids_a + sep + token_ids_a + sep + cls


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = None							):
								lowerCamelCase			=[self.sep_token_id]
								lowerCamelCase			=[2]

								if token_ids_a is None:
												return len(token_ids_a + sep							) * [0] + cls_segment_id
								return len(token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1] + cls_segment_id


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = 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,)









from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

UpperCAmelCase__  :     Any   			={
    '''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}

class  __A       (  a      ):
				__A								=			"""vit_msn"""


				def __init__(						self				,	UpperCAmelCase_=768				,	UpperCAmelCase_=12				,	UpperCAmelCase_=12				,	UpperCAmelCase_=3072				,	UpperCAmelCase_="gelu"				,	UpperCAmelCase_=0.0				,	UpperCAmelCase_=0.0				,	UpperCAmelCase_=0.0_2				,	UpperCAmelCase_=1E-06				,	UpperCAmelCase_=224				,	UpperCAmelCase_=16				,	UpperCAmelCase_=3				,	UpperCAmelCase_=True				,	**UpperCAmelCase_				,	):
								super().__init__(**UpperCAmelCase_							)

								lowerCamelCase			=hidden_size
								lowerCamelCase			=num_hidden_layers
								lowerCamelCase			=num_attention_heads
								lowerCamelCase			=intermediate_size
								lowerCamelCase			=hidden_act
								lowerCamelCase			=hidden_dropout_prob
								lowerCamelCase			=attention_probs_dropout_prob
								lowerCamelCase			=initializer_range
								lowerCamelCase			=layer_norm_eps
								lowerCamelCase			=image_size
								lowerCamelCase			=patch_size
								lowerCamelCase			=num_channels
								lowerCamelCase			=qkv_bias





