
'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


UpperCAmelCase__   : List[Any]					=		{"configuration_bert_generation": ["BertGenerationConfig"]}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase__   : List[Any]					=		["BertGenerationTokenizer"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase__   : int					=		[
		    "BertGenerationDecoder",
		    "BertGenerationEncoder",
		    "BertGenerationPreTrainedModel",
		    "load_tf_weights_in_bert_generation",
		]


if TYPE_CHECKING:
		from .configuration_bert_generation import BertGenerationConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_bert_generation import BertGenerationTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bert_generation import (
				    BertGenerationDecoder,
				    BertGenerationEncoder,
				    BertGenerationPreTrainedModel,
				    load_tf_weights_in_bert_generation,
				)

else:
		import sys

		UpperCAmelCase__   : Optional[int]					=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_layoutlm import LayoutLMTokenizer


UpperCAmelCase__   : Optional[Any]					=		logging.get_logger(__name__)

UpperCAmelCase__   : str					=		{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

UpperCAmelCase__   : Union[str, Any]					=		{
    "vocab_file": {
        "microsoft/layoutlm-base-uncased": (
            "https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/vocab.txt"
        ),
        "microsoft/layoutlm-large-uncased": (
            "https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "microsoft/layoutlm-base-uncased": (
            "https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/tokenizer.json"
        ),
        "microsoft/layoutlm-large-uncased": (
            "https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/tokenizer.json"
        ),
    },
}

UpperCAmelCase__   : List[Any]					=		{
    "microsoft/layoutlm-base-uncased": 5_12,
    "microsoft/layoutlm-large-uncased": 5_12,
}

UpperCAmelCase__   : List[str]					=		{
    "microsoft/layoutlm-base-uncased": {"do_lower_case": True},
    "microsoft/layoutlm-large-uncased": {"do_lower_case": True},
}






class    A     (	SCREAMING_SNAKE_CASE__    ):
	snake_case__      :Union[str, Any]        =     VOCAB_FILES_NAMES
	snake_case__      :List[str]        =     PRETRAINED_VOCAB_FILES_MAP
	snake_case__      :Union[str, Any]        =     PRETRAINED_INIT_CONFIGURATION
	snake_case__      :int        =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case__      :int        =     LayoutLMTokenizer





	def __init__(					self			:       Any      ,							__magic_name__			:       List[Any]=None      ,							__magic_name__			:       Optional[int]=None      ,							__magic_name__			:       Dict=True      ,							__magic_name__			:       Dict="[UNK]"      ,							__magic_name__			:       List[str]="[SEP]"      ,							__magic_name__			:       int="[PAD]"      ,							__magic_name__			:       Tuple="[CLS]"      ,							__magic_name__			:       int="[MASK]"      ,							__magic_name__			:       Dict=True      ,							__magic_name__			:       Tuple=None      ,							**__magic_name__			:       Optional[int]      ,							):


				"""simple docstring"""

				super().__init__(
				    __magic_name__      ,							tokenizer_file=__magic_name__      ,							do_lower_case=__magic_name__      ,							unk_token=__magic_name__      ,							sep_token=__magic_name__      ,							pad_token=__magic_name__      ,							cls_token=__magic_name__      ,							mask_token=__magic_name__      ,							tokenize_chinese_chars=__magic_name__      ,							strip_accents=__magic_name__      ,							**__magic_name__      ,							)

				lowerCAmelCase__								=							json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
				if (
				    normalizer_state.get("lowercase"      ,							__magic_name__							) != do_lower_case
				    or normalizer_state.get("strip_accents"      ,							__magic_name__							) != strip_accents
				    or normalizer_state.get("handle_chinese_chars"      ,							__magic_name__							) != tokenize_chinese_chars
				):
							lowerCAmelCase__								=							getattr(__magic_name__      ,							normalizer_state.pop("type"							)							)
							lowerCAmelCase__								=							do_lower_case
							lowerCAmelCase__								=							strip_accents
							lowerCAmelCase__								=							tokenize_chinese_chars
							lowerCAmelCase__								=							normalizer_class(**__magic_name__							)

				lowerCAmelCase__								=							do_lower_case





	def 							__SCREAMING_SNAKE_CASE  (					self			:       List[str]      ,							__magic_name__			:       Optional[int]      ,							__magic_name__			:       List[str]=None							):


				"""simple docstring"""

				lowerCAmelCase__								=							[self.cls_token_id] + token_ids_a + [self.sep_token_id]

				if token_ids_a:
							output += token_ids_a + [self.sep_token_id]

				return output





	def 							__SCREAMING_SNAKE_CASE  (					self			:       Tuple      ,							__magic_name__			:       List[int]      ,							__magic_name__			:       Optional[List[int]] = None							):


				"""simple docstring"""

				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							) * [0] + len(token_ids_a + sep							) * [1]







	def 							__SCREAMING_SNAKE_CASE  (					self			:       Optional[Any]      ,							__magic_name__			:       str      ,							__magic_name__			:       Optional[str] = None							):


				"""simple docstring"""

				lowerCAmelCase__								=							self._tokenizer.model.save(__magic_name__      ,							name=__magic_name__							)
				return tuple(__magic_name__							)





