


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class        snake_case__	(			__A   ,     unittest.TestCase							):
	UpperCAmelCase :				Optional[Any]       =			RobertaTokenizer
	UpperCAmelCase :				List[Any]       =			RobertaTokenizerFast
	UpperCAmelCase :				Tuple       =			True
	UpperCAmelCase :				Tuple       =			{"""cls_token""": """<s>"""}





	def      A					(	self				)		->      List[str]:
								"""simple docstring"""






								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								a_							: str								=						[
								    """l""",
								    """o""",
								    """w""",
								    """e""",
								    """r""",
								    """s""",
								    """t""",
								    """i""",
								    """d""",
								    """n""",
								    """\u0120""",
								    """\u0120l""",
								    """\u0120n""",
								    """\u0120lo""",
								    """\u0120low""",
								    """er""",
								    """\u0120lowest""",
								    """\u0120newer""",
								    """\u0120wider""",
								    """<unk>""",
								]
								a_							: List[Any]								=						dict(zip(lowercase__					,     range(len(lowercase__				)				)				)				)
								a_							: List[Any]								=						["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
								a_							: Union[str, Any]								=						{"""unk_token""": """<unk>"""}

								a_							: str								=						os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["""vocab_file"""]				)
								a_							: Any								=						os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["""merges_file"""]				)
								with open(self.vocab_file					,     """w"""					,     encoding="""utf-8"""				) as fp:
															fp.write(json.dumps(lowercase__				) + """\n"""				)
								with open(self.merges_file					,     """w"""					,     encoding="""utf-8"""				) as fp:
															fp.write("""\n""".join(lowercase__				)				)





	def      A					(	self					,     **UpperCamelCase_				)		->      int:
								"""simple docstring"""






								kwargs.update(self.special_tokens_map				)
								return self.tokenizer_class.from_pretrained(self.tmpdirname					,     **lowercase__				)





	def      A					(	self					,     **UpperCamelCase_				)		->      Optional[Any]:
								"""simple docstring"""






								kwargs.update(self.special_tokens_map				)
								return RobertaTokenizerFast.from_pretrained(self.tmpdirname					,     **lowercase__				)





	def      A					(	self					,     UpperCamelCase_				)		->      int:
								"""simple docstring"""






								a_							: Dict								=						"""lower newer"""
								a_							: int								=						"""lower newer"""
								return input_text, output_text





	def      A					(	self				)		->      str:
								"""simple docstring"""






								a_							: Dict								=						self.tokenizer_class(self.vocab_file					,     self.merges_file					,     **self.special_tokens_map				)
								a_							: int								=						"""lower newer"""
								a_							: List[str]								=						["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
								a_							: Tuple								=						tokenizer.tokenize(lowercase__				)  # , add_prefix_space=True)
								self.assertListEqual(lowercase__					,     lowercase__				)

								a_							: int								=						tokens + [tokenizer.unk_token]
								a_							: str								=						[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__				)					,     lowercase__				)





	def      A					(	self				)		->      str:
								"""simple docstring"""






								a_							: str								=						self.get_tokenizer()

								self.assertListEqual(tokenizer.encode("""Hello world!"""					,     add_special_tokens=lowercase__				)					,     [0, 31414, 232, 328, 2]				)
								self.assertListEqual(
								    tokenizer.encode("""Hello world! cécé herlolip 418"""					,     add_special_tokens=lowercase__				)					,     [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]					,     )





	@slow
	def      A					(	self				)		->      Optional[Any]:
								"""simple docstring"""






								a_							: Optional[Any]								=						self.tokenizer_class.from_pretrained("""roberta-base"""				)

								a_							: Any								=						tokenizer.encode("""sequence builders"""					,     add_special_tokens=lowercase__				)
								a_							: int								=						tokenizer.encode("""multi-sequence build"""					,     add_special_tokens=lowercase__				)

								a_							: Dict								=						tokenizer.encode(
								    """sequence builders"""					,     add_special_tokens=lowercase__					,     add_prefix_space=lowercase__				)
								a_							: int								=						tokenizer.encode(
								    """sequence builders"""					,     """multi-sequence build"""					,     add_special_tokens=lowercase__					,     add_prefix_space=lowercase__				)

								a_							: str								=						tokenizer.build_inputs_with_special_tokens(lowercase__				)
								a_							: List[Any]								=						tokenizer.build_inputs_with_special_tokens(lowercase__					,     lowercase__				)

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode





	def      A					(	self				)		->      Dict:
								"""simple docstring"""






								a_							: str								=						self.get_tokenizer()

								a_							: List[Any]								=						"""Encode this sequence."""
								a_							: Any								=						tokenizer.byte_encoder[""" """.encode("""utf-8"""				)[0]]

								# Testing encoder arguments
								a_							: Optional[int]								=						tokenizer.encode(lowercase__					,     add_special_tokens=lowercase__					,     add_prefix_space=lowercase__				)
								a_							: Dict								=						tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
								self.assertNotEqual(lowercase__					,     lowercase__				)

								a_							: Dict								=						tokenizer.encode(lowercase__					,     add_special_tokens=lowercase__					,     add_prefix_space=lowercase__				)
								a_							: List[str]								=						tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
								self.assertEqual(lowercase__					,     lowercase__				)

								tokenizer.add_special_tokens({"""bos_token""": """<s>"""}				)
								a_							: str								=						tokenizer.encode(lowercase__					,     add_special_tokens=lowercase__				)
								a_							: int								=						tokenizer.convert_ids_to_tokens(encoded[1]				)[0]
								self.assertNotEqual(lowercase__					,     lowercase__				)

								# Testing spaces after special tokens
								a_							: Union[str, Any]								=						"""<mask>"""
								tokenizer.add_special_tokens(
								    {"""mask_token""": AddedToken(lowercase__					,     lstrip=lowercase__					,     rstrip=lowercase__				)}				)  # mask token has a left space
								a_							: Any								=						tokenizer.convert_tokens_to_ids(lowercase__				)

								a_							: Union[str, Any]								=						"""Encode <mask> sequence"""
								a_							: List[str]								=						"""Encode <mask>sequence"""

								a_							: Dict								=						tokenizer.encode(lowercase__				)
								a_							: List[Any]								=						encoded.index(lowercase__				)
								a_							: List[Any]								=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
								self.assertEqual(lowercase__					,     lowercase__				)

								a_							: List[Any]								=						tokenizer.encode(lowercase__				)
								a_							: Dict								=						encoded.index(lowercase__				)
								a_							: Optional[Any]								=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
								self.assertNotEqual(lowercase__					,     lowercase__				)





	def      A					(	self				)		->      List[str]:
								"""simple docstring"""






								pass





	def      A					(	self				)		->      Any:
								"""simple docstring"""






								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
																						a_							: Union[str, Any]								=						self.rust_tokenizer_class.from_pretrained(lowercase__					,     **lowercase__				)
																						a_							: Union[str, Any]								=						self.tokenizer_class.from_pretrained(lowercase__					,     **lowercase__				)
																						a_							: List[str]								=						"""A, <mask> AllenNLP sentence."""
																						a_							: Any								=						tokenizer_r.encode_plus(lowercase__					,     add_special_tokens=lowercase__					,     return_token_type_ids=lowercase__				)
																						a_							: Optional[int]								=						tokenizer_p.encode_plus(lowercase__					,     add_special_tokens=lowercase__					,     return_token_type_ids=lowercase__				)

																						# token_type_ids should put 0 everywhere
																						self.assertEqual(sum(tokens_r["""token_type_ids"""]				)					,     sum(tokens_p["""token_type_ids"""]				)				)

																						# attention_mask should put 1 everywhere, so sum over length should be 1
																						self.assertEqual(
																						    sum(tokens_r["""attention_mask"""]				) / len(tokens_r["""attention_mask"""]				)					,     sum(tokens_p["""attention_mask"""]				) / len(tokens_p["""attention_mask"""]				)					,     )

																						a_							: Tuple								=						tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]				)
																						a_							: Any								=						tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]				)

																						# Rust correctly handles the space before the mask while python doesnt
																						self.assertSequenceEqual(tokens_p["""input_ids"""]					,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]				)
																						self.assertSequenceEqual(tokens_r["""input_ids"""]					,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]				)

																						self.assertSequenceEqual(
																						    lowercase__					,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)
																						self.assertSequenceEqual(
																						    lowercase__					,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)





	def      A					(	self				)		->      Any:
								"""simple docstring"""






								for trim_offsets, add_prefix_space in itertools.product([True, False]					,     repeat=2				):
															a_							: Any								=						self.rust_tokenizer_class.from_pretrained(
															    self.tmpdirname					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)

															a_							: List[str]								=						json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()				)
															a_							: Union[str, Any]								=						json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()				)

															self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]					,     lowercase__				)

															self.assertEqual(post_processor_state["""add_prefix_space"""]					,     lowercase__				)
															self.assertEqual(post_processor_state["""trim_offsets"""]					,     lowercase__				)





	def      A					(	self				)		->      Dict:
								"""simple docstring"""






								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
																						a_							: Dict								=						"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																						a_							: List[Any]								=						f"""{text_of_1_token} {text_of_1_token}"""

																						a_							: int								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: Any								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (len(lowercase__				) + 1, len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: Union[str, Any]								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: List[str]								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (len(lowercase__				) + 1, len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: Tuple								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: Optional[Any]								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (len(lowercase__				), len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: Optional[Any]								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: str								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (len(lowercase__				), len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: int								=						f""" {text}"""

																						# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																						#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																						# )
																						# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																						# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																						# self.assertEqual(
																						#     encoding.offset_mapping[1],
																						#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																						# )

																						a_							: Tuple								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: str								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (1, 1 + len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (1 + len(lowercase__				) + 1, 1 + len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: List[Any]								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: Any								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, 1 + len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (1 + len(lowercase__				), 1 + len(lowercase__				) + 1 + len(lowercase__				))					,     )

																						a_							: Union[str, Any]								=						self.rust_tokenizer_class.from_pretrained(
																						    lowercase__					,     use_fast=lowercase__					,     add_prefix_space=lowercase__					,     trim_offsets=lowercase__				)
																						a_							: Any								=						tokenizer_r(lowercase__					,     return_offsets_mapping=lowercase__					,     add_special_tokens=lowercase__				)
																						self.assertEqual(encoding.offset_mapping[0]					,     (0, 1 + len(lowercase__				))				)
																						self.assertEqual(
																						    encoding.offset_mapping[1]					,     (1 + len(lowercase__				), 1 + len(lowercase__				) + 1 + len(lowercase__				))					,     )



import functools






def _lowerCamelCase  (		snake_case     , snake_case  ):

							# Validation
							if not isinstance(snake_case     , snake_case  ) or not all(isinstance(snake_case     , snake_case  ) for day in days  ):
														raise ValueError('The parameter days should be a list of integers'  )

							if len(snake_case  ) != 3 or not all(isinstance(snake_case     , snake_case  ) for cost in costs  ):
														raise ValueError('The parameter costs should be a list of three integers'  )

							if len(snake_case  ) == 0:
														return 0

							if min(snake_case  ) <= 0:
														raise ValueError('All days elements should be greater than 0'  )

							if max(snake_case  ) >= 366:
														raise ValueError('All days elements should be less than 366'  )

							_lowerCAmelCase							=							set(snake_case  )

							@functools.cache
							def dynamic_programming(snake_case  ) -> int:
														if index > 365:
																					return 0

														if index not in days_set:
																					return dynamic_programming(index + 1  )

														return min(
														    costs[0] + dynamic_programming(index + 1  )     , costs[1] + dynamic_programming(index + 7  )     , costs[2] + dynamic_programming(index + 30  )     , )

							return dynamic_programming(1  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()






