



"""simple docstring"""







import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A		=						get_tests_dir('fixtures/test_sentencepiece.model')

@require_sentencepiece
class       _a  ( SCREAMING_SNAKE_CASE__     ,	unittest.TestCase):
			__magic_name__     					=     XLMProphetNetTokenizer
			__magic_name__     					=     False
			__magic_name__     					=     True



			def 				__lowercase					(			self							:				Optional[Any]		)							->					List[Any]:
									super().setUp()

									# We have a SentencePiece fixture for testing
									snake_case   :			Tuple						    = XLMProphetNetTokenizer(lowerCamelCase_   ,	keep_accents=lowerCamelCase_		)
									tokenizer.save_pretrained(self.tmpdirname		)



			def 				__lowercase					(			self							:				Any		)							->					int:
									snake_case   :			Union[str, Any]						    = "[PAD]"
									snake_case   :			int						    = 0

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase_		)   ,	lowerCamelCase_		)
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase_		)   ,	lowerCamelCase_		)



			def 				__lowercase					(			self							:				str		)							->					List[Any]:
									snake_case   :			Tuple						    = list(self.get_tokenizer().get_vocab().keys()		)

									self.assertEqual(vocab_keys[0]   ,	"[PAD]"		)
									self.assertEqual(vocab_keys[1]   ,	"[CLS]"		)
									self.assertEqual(vocab_keys[-1]   ,	"j"		)
									self.assertEqual(len(lowerCamelCase_		)   ,	1012		)



			def 				__lowercase					(			self							:				Optional[int]		)							->					List[str]:
									self.assertEqual(self.get_tokenizer().vocab_size   ,	1012		)



			def 				__lowercase					(			self							:				str		)							->					Dict:
									snake_case   :			List[str]						    = XLMProphetNetTokenizer(lowerCamelCase_   ,	keep_accents=lowerCamelCase_		)

									snake_case   :			Optional[Any]						    = tokenizer.tokenize("This is a test"		)
									self.assertListEqual(lowerCamelCase_   ,	["▁This", "▁is", "▁a", "▁t", "est"]		)

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(lowerCamelCase_		)   ,	[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,	)

									snake_case   :			List[Any]						    = tokenizer.tokenize("I was born in 92000, and this is falsé."		)
									self.assertListEqual(
									    lowerCamelCase_   ,	[
									        SPIECE_UNDERLINE + "I",
									        SPIECE_UNDERLINE + "was",
									        SPIECE_UNDERLINE + "b",
									        "or",
									        "n",
									        SPIECE_UNDERLINE + "in",
									        SPIECE_UNDERLINE + "",
									        "9",
									        "2",
									        "0",
									        "0",
									        "0",
									        ",",
									        SPIECE_UNDERLINE + "and",
									        SPIECE_UNDERLINE + "this",
									        SPIECE_UNDERLINE + "is",
									        SPIECE_UNDERLINE + "f",
									        "al",
									        "s",
									        "é",
									        ".",
									    ]   ,	)
									snake_case   :			Dict						    = tokenizer.convert_tokens_to_ids(lowerCamelCase_		)
									self.assertListEqual(
									    lowerCamelCase_   ,	[
									        value + tokenizer.fairseq_offset
									        for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
									    ]   ,	)

									snake_case   :			int						    = tokenizer.convert_ids_to_tokens(lowerCamelCase_		)
									self.assertListEqual(
									    lowerCamelCase_   ,	[
									        SPIECE_UNDERLINE + "I",
									        SPIECE_UNDERLINE + "was",
									        SPIECE_UNDERLINE + "b",
									        "or",
									        "n",
									        SPIECE_UNDERLINE + "in",
									        SPIECE_UNDERLINE + "",
									        "[UNK]",
									        "2",
									        "0",
									        "0",
									        "0",
									        ",",
									        SPIECE_UNDERLINE + "and",
									        SPIECE_UNDERLINE + "this",
									        SPIECE_UNDERLINE + "is",
									        SPIECE_UNDERLINE + "f",
									        "al",
									        "s",
									        "[UNK]",
									        ".",
									    ]   ,	)



			@cached_property
			def 				__lowercase					(			self							:				Optional[Any]		)							->					List[str]:
									return XLMProphetNetTokenizer.from_pretrained("microsoft/xprophetnet-large-wiki100-cased"		)



			@slow
			def 				__lowercase					(			self							:				Any		)							->					Optional[Any]:
									snake_case   :			List[str]						    = "Hello World!"
									snake_case   :			Optional[Any]						    = [35389, 6672, 49, 2]
									self.assertListEqual(lowerCamelCase_   ,	self.big_tokenizer.encode(lowerCamelCase_		)		)



			@slow
			def 				__lowercase					(			self							:				str		)							->					Union[str, Any]:
									# fmt: off
									snake_case   :			Dict						    = {"input_ids": [[11073, 82783, 18, 26, 82783, 549, 51540, 248, 17209, 1301, 217, 20, 215186, 1325, 147, 17209, 1301, 217, 20, 56370, 53, 122020, 20, 16477, 27, 87355, 4548, 20, 4728, 78392, 17, 159969, 18, 26, 24491, 629, 15, 538, 22704, 5439, 15, 2788, 24491, 9885, 15, 43534, 605, 15, 814, 18403, 33200, 29, 15, 43534, 24458, 12410, 111, 24966, 83669, 9637, 144068, 26, 850, 22346, 27, 147, 24966, 83669, 83490, 26, 39113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 122020, 115785, 34, 816, 1339, 46887, 18, 147, 53905, 1951, 42238, 41170, 17732, 834, 436, 15, 27523, 98733, 217, 147, 5542, 4981, 930, 17347, 16, 2], [20091, 629, 94, 82786, 58, 490, 20, 1528, 84, 53905, 344, 80592, 110128, 18822, 5267, 1306, 62, 152537, 308, 7997, 401, 124427, 549, 35442, 225, 109, 15055, 25748, 147, 7119, 43712, 34, 767, 135366, 18, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [592, 63784, 119466, 17, 147808, 88214, 18, 656, 81, 32, 3296, 10280, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=lowerCamelCase_   ,	model_name="microsoft/xprophetnet-large-wiki100-cased"   ,	revision="1acad1643ddd54a44df6a1b797ada8373685d90e"   ,	)






"""simple docstring"""


from __future__ import annotations

from collections.abc import Sequence
from typing import Literal



def   _A					(	_a	:						str     ,   _a	:						str				):



      """simple docstring"""






      A				  =		list(_a				)
      A				  =		list(_a				)
      A				  =		0
      for i in range(len(_a				)				):
            if lista[i] != lista[i]:
                  count += 1
                  A				  =		"""_"""
      if count > 1:
            return False
      else:
            return "".join(_a				)



def   _A					(	_a	:						list[str]				):



      """simple docstring"""






      A				  =		[]
      while True:
            A				  =		["""$"""] * len(_a				)
            A				  =		[]
            for i in range(len(_a				)				):
                  for j in range(i + 1     ,   len(_a				)				):
                        A				  =		compare_string(binary[i]     ,   binary[j]				)
                        if k is False:
                              A				  =		"""*"""
                              A				  =		"""*"""
                              temp.append("""X"""				)
            for i in range(len(_a				)				):
                  if checka[i] == "$":
                        pi.append(binary[i]				)
            if len(_a				) == 0:
                  return pi
            A				  =		list(set(_a				)				)



def   _A					(	_a	:						int     ,   _a	:						Sequence[float]				):



      """simple docstring"""






      A				  =		[]
      for minterm in minterms:
            A				  =		""""""
            for _ in range(_a				):
                  A				  =		str(minterm % 2				) + string
                  minterm //= 2
            temp.append(_a				)
      return temp



def   _A					(	_a	:						str     ,   _a	:						str     ,   _a	:						int				):



      """simple docstring"""






      A				  =		list(_a				)
      A				  =		list(_a				)
      A				  =		0
      for i in range(len(_a				)				):
            if lista[i] != lista[i]:
                  count_n += 1
      return count_n == count



def   _A					(	_a	:						list[list[int]]     ,   _a	:						list[str]				):



      """simple docstring"""






      A				  =		[]
      A				  =		[0] * len(_a				)
      for i in range(len(chart[0]				)				):
            A				  =		0
            A				  =		-1
            for j in range(len(_a				)				):
                  if chart[j][i] == 1:
                        count += 1
                        A				  =		j
            if count == 1:
                  A				  =		1
      for i in range(len(_a				)				):
            if select[i] == 1:
                  for j in range(len(chart[0]				)				):
                        if chart[i][j] == 1:
                              for k in range(len(_a				)				):
                                    A				  =		0
                  temp.append(prime_implicants[i]				)
      while True:
            A				  =		0
            A				  =		-1
            A				  =		0
            for i in range(len(_a				)				):
                  A				  =		chart[i].count(1				)
                  if count_n > max_n:
                        A				  =		count_n
                        A				  =		i

            if max_n == 0:
                  return temp

            temp.append(prime_implicants[rem]				)

            for i in range(len(chart[0]				)				):
                  if chart[rem][i] == 1:
                        for j in range(len(_a				)				):
                              A				  =		0



def   _A					(	_a	:						list[str]     ,   _a	:						list[str]				):



      """simple docstring"""






      A				  =		[[0 for x in range(len(_a				)				)] for x in range(len(_a				)				)]
      for i in range(len(_a				)				):
            A				  =		prime_implicants[i].count("""_"""				)
            for j in range(len(_a				)				):
                  if is_for_table(prime_implicants[i]     ,   binary[j]     ,   _a				):
                        A				  =		1

      return chart



def   _A					(	):



      """simple docstring"""






      A				  =		int(input("""Enter the no. of variables\n"""				)				)
      A				  =		[
          float(_a				)
          for x in input(
              """Enter the decimal representation of Minterms 'Spaces Separated'\n"""				).split()
      ]
      A				  =		decimal_to_binary(_a     ,   _a				)

      A				  =		check(_a				)
      print("""Prime Implicants are:"""				)
      print(_a				)
      A				  =		prime_implicant_chart(_a     ,   _a				)

      A				  =		selection(_a     ,   _a				)
      print("""Essential Prime Implicants are:"""				)
      print(_a				)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




