
import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer


class        lowercase      (	tf.keras.layers.Layer     ):



		def __init__(				self       ,   A_       ,   A_       ,   A_ = None       ,   A_ = None )						->      Tuple:
				"""simple docstring"""
				super().__init__()
				UpperCamelCase						=  pad_token_id
				UpperCamelCase						=  max_length
				UpperCamelCase						=  vocab
				UpperCamelCase						=  merges
				UpperCamelCase						=  BytePairTokenizer(_lowercase       ,   _lowercase       ,   sequence_length=_lowercase )



		@classmethod
		def __UpperCamelCase				(				cls       ,   A_       ,   *A_       ,   **A_ )						->      Any:
				"""simple docstring"""
				UpperCamelCase						=  [""" """.join(_lowercase ) for m in tokenizer.bpe_ranks.keys()]
				UpperCamelCase						=  tokenizer.get_vocab()
				return cls(_lowercase       ,   _lowercase       ,   *_lowercase       ,   **_lowercase )



		@classmethod
		def __UpperCamelCase				(				cls       ,   A_       ,   *A_       ,   **A_ )						->      str:
				"""simple docstring"""
				UpperCamelCase						=  GPTaTokenizer.from_pretrained(_lowercase       ,   *_lowercase       ,   **_lowercase )
				return cls.from_tokenizer(_lowercase       ,   *_lowercase       ,   **_lowercase )



		@classmethod
		def __UpperCamelCase				(				cls       ,   A_ )						->      Dict:
				"""simple docstring"""
				return cls(**_lowercase )



		def __UpperCamelCase				(				self )						->      Optional[int]:
				"""simple docstring"""
				return {
				    "vocab": self.vocab,
				    "merges": self.merges,
				    "max_length": self.max_length,
				    "pad_token_id": self.pad_token_id,
				}






		def __UpperCamelCase				(				self       ,   A_       ,   A_ = None )						->      int:
				"""simple docstring"""
				UpperCamelCase						=  self.tf_tokenizer(_lowercase )
				UpperCamelCase						=  tf.ones_like(_lowercase )

				if self.pad_token_id is not None:
						# pad the tokens up to max length
						UpperCamelCase						=  max_length if max_length is not None else self.max_length

						if max_length is not None:
								UpperCamelCase						=  pad_model_inputs(
								    _lowercase       ,   max_seq_length=_lowercase       ,   pad_value=self.pad_token_id )

				return {"attention_mask": attention_mask, "input_ids": input_ids}


import os

_UpperCAmelCase      :				int          = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1_000}


def    A (      lowercase				)     ->						int:
		'''simple docstring'''

		UpperCamelCase						=  0

		UpperCamelCase						=  0
		while index < len(lowercase				) - 1:
				UpperCamelCase						=  SYMBOLS[numerals[index]]
				UpperCamelCase						=  SYMBOLS[numerals[index + 1]]
				if current_value < next_value:
						total_value -= current_value
				else:
						total_value += current_value
				index += 1
		total_value += SYMBOLS[numerals[index]]

		return total_value


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  ''

		UpperCamelCase						=  num // 1_000
		numerals += m_count * "M"
		num %= 1_000

		UpperCamelCase						=  num // 100
		if c_count == 9:
				numerals += "CM"
				c_count -= 9
		elif c_count == 4:
				numerals += "CD"
				c_count -= 4
		if c_count >= 5:
				numerals += "D"
				c_count -= 5
		numerals += c_count * "C"
		num %= 100

		UpperCamelCase						=  num // 10
		if x_count == 9:
				numerals += "XC"
				x_count -= 9
		elif x_count == 4:
				numerals += "XL"
				x_count -= 4
		if x_count >= 5:
				numerals += "L"
				x_count -= 5
		numerals += x_count * "X"
		num %= 10

		if num == 9:
				numerals += "IX"
				num -= 9
		elif num == 4:
				numerals += "IV"
				num -= 4
		if num >= 5:
				numerals += "V"
				num -= 5
		numerals += num * "I"

		return numerals


def    A (      lowercase = "/p089_roman.txt"				)     ->						int:
		'''simple docstring'''

		UpperCamelCase						=  0

		with open(os.path.dirname(lowercase				) + roman_numerals_filename				) as filea:
				UpperCamelCase						=  filea.readlines()

		for line in lines:
				UpperCamelCase						=  line.strip()
				UpperCamelCase						=  parse_roman_numerals(lowercase				)
				UpperCamelCase						=  generate_roman_numerals(lowercase				)
				savings += len(lowercase				) - len(lowercase				)

		return savings


if __name__ == "__main__":
					print(F'''{solution() = }''')
