





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a 						=      {
    "configuration_upernet": ["UperNetConfig"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a 						=      [
			    "UperNetForSemanticSegmentation",
			    "UperNetPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_upernet import UperNetConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
			import sys

			_a 						=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










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:
			_a 						=      None


_a 						=      logging.get_logger(__name__)

_a 						=      {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

_a 						=      {
    "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",
    },
}

_a 						=      {
    "xlnet-base-cased": None,
    "xlnet-large-cased": None,
}

_a 						=      "▁"

# Segments (not really needed)
_a 						=      0
_a 						=      1
_a 						=      2
_a 						=      3
_a 						=      4






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						VOCAB_FILES_NAMES
			lowerCAmelCase_							     =						PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_							     =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_							     =						"""left"""
			lowerCAmelCase_							     =						XLNetTokenizer





			def __init__(    self       ,  __lowerCAmelCase=None       ,  __lowerCAmelCase=None       ,  __lowerCAmelCase=False       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=False       ,  __lowerCAmelCase="<s>"       ,  __lowerCAmelCase="</s>"       ,  __lowerCAmelCase="<unk>"       ,  __lowerCAmelCase="<sep>"       ,  __lowerCAmelCase="<pad>"       ,  __lowerCAmelCase="<cls>"       ,  __lowerCAmelCase="<mask>"       ,  __lowerCAmelCase=["<eop>", "<eod>"]       ,  **__lowerCAmelCase       ,  ):



				'''simple docstring'''







				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 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase = None							):



				'''simple docstring'''







				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 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase = None							):



				'''simple docstring'''







				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 		__lowerCamelCase				(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase = 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(__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,)



