


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


SCREAMING_SNAKE_CASE__       			=				logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE__       			=				{
    """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"""
        ),
    },
}

SCREAMING_SNAKE_CASE__       			=				{
    """microsoft/layoutlm-base-uncased""": 5_1_2,
    """microsoft/layoutlm-large-uncased""": 5_1_2,
}

SCREAMING_SNAKE_CASE__       			=				{
    """microsoft/layoutlm-base-uncased""": {"""do_lower_case""": True},
    """microsoft/layoutlm-large-uncased""": {"""do_lower_case""": True},
}







class     __lowerCamelCase     (  snake_case_     ):


							"""simple docstring"""

							lowerCAmelCase__          =				VOCAB_FILES_NAMES
							lowerCAmelCase__          =				PRETRAINED_VOCAB_FILES_MAP
							lowerCAmelCase__          =				PRETRAINED_INIT_CONFIGURATION
							lowerCAmelCase__          =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCAmelCase__          =				LayoutLMTokenizer




							def __init__(  self						,       UpperCAmelCase=None						,       UpperCAmelCase=None						,       UpperCAmelCase=True						,       UpperCAmelCase="[UNK]"						,       UpperCAmelCase="[SEP]"						,       UpperCAmelCase="[PAD]"						,       UpperCAmelCase="[CLS]"						,       UpperCAmelCase="[MASK]"						,       UpperCAmelCase=True						,       UpperCAmelCase=None						,       **UpperCAmelCase						,       )     ->       Tuple:






								'''simple docstring'''






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

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

								lowercase_			 = do_lower_case




							def 				A__      (  self						,       UpperCAmelCase						,       UpperCAmelCase=None  )     ->       Tuple:






								'''simple docstring'''






								lowercase_			 = [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 				A__      (  self						,       UpperCAmelCase						,       UpperCAmelCase = None  )     ->       List[int]:






								'''simple docstring'''






								lowercase_			 = [self.sep_token_id]
								lowercase_			 = [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 				A__      (  self						,       UpperCAmelCase						,       UpperCAmelCase = None  )     ->       Tuple[str]:






								'''simple docstring'''






								lowercase_			 = self._tokenizer.model.save(UpperCAmelCase						,       name=UpperCAmelCase  )
								return tuple(UpperCAmelCase  )





from __future__ import annotations

from statistics import mean




def SCREAMING_SNAKE_CASE_  (				__lowerCamelCase:		list[int]  ):







	'''simple docstring'''



	lowercase_			 = 2
	lowercase_			 = list(__lowerCamelCase  )
	lowercase_			 = [0] * len(__lowerCamelCase  )
	lowercase_			 = 0
	while True:
		lowercase_			 = True
		for i, burst_time in enumerate(__lowerCamelCase  ):
			if rem_burst_times[i] > 0:
				lowercase_			 = False
				if rem_burst_times[i] > quantum:
					t += quantum
					rem_burst_times[i] -= quantum
				else:
					t += rem_burst_times[i]
					lowercase_			 = t - burst_time
					lowercase_			 = 0
		if done is True:
			return waiting_times




def SCREAMING_SNAKE_CASE_  (				__lowerCamelCase:		list[int]  ,			__lowerCamelCase:		list[int]  ):







	'''simple docstring'''



	return [burst + waiting for burst, waiting in zip(__lowerCamelCase  ,			__lowerCamelCase  )]


if __name__ == "__main__":
							SCREAMING_SNAKE_CASE__       			=				[3, 5, 7]
							SCREAMING_SNAKE_CASE__       			=				calculate_waiting_times(burst_times)
							SCREAMING_SNAKE_CASE__       			=				calculate_turn_around_times(burst_times, waiting_times)
							print("""Process ID \tBurst Time \tWaiting Time \tTurnaround Time""")
							for i, burst_time in enumerate(burst_times):
														print(
														    f"""  {i + 1}\t\t  {burst_time}\t\t  {waiting_times[i]}\t\t  """
														    f"""{turn_around_times[i]}"""
														)
							print(f"""\nAverage waiting time = {mean(waiting_times):.5f}""")
							print(f"""Average turn around time = {mean(turn_around_times):.5f}""")

