


'''simple docstring'''

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					(					lowercase    ,		unittest.TestCase    ):





  """simple docstring"""




  _lowerCamelCase						=						RobertaTokenizer
  _lowerCamelCase						=						RobertaTokenizerFast
  _lowerCamelCase						=						True
  _lowerCamelCase						=						{"cls_token": "<s>"}






  def 						snake_case	(					self  ):







   """simple docstring"""
   super().setUp()

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

   lowerCamelCase_  				=						os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["vocab_file"]  )
   lowerCamelCase_  				=						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(UpperCamelCase  ) + "\n"  )
   with open(self.merges_file    ,						"w"    ,						encoding="utf-8"  ) as fp:
    fp.write("\n".join(UpperCamelCase  )  )






  def 						snake_case	(					self    ,						**UpperCamelCase  ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map  )
   return self.tokenizer_class.from_pretrained(self.tmpdirname    ,						**UpperCamelCase  )






  def 						snake_case	(					self    ,						**UpperCamelCase  ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map  )
   return RobertaTokenizerFast.from_pretrained(self.tmpdirname    ,						**UpperCamelCase  )






  def 						snake_case	(					self    ,						UpperCamelCase  ):







   """simple docstring"""
   lowerCamelCase_  				=						"lower newer"
   lowerCamelCase_  				=						"lower newer"
   return input_text, output_text






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.tokenizer_class(self.vocab_file    ,						self.merges_file    ,						**self.special_tokens_map  )
   lowerCamelCase_  				=						"lower newer"
   lowerCamelCase_  				=						["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
   lowerCamelCase_  				=						tokenizer.tokenize(UpperCamelCase  )  # , add_prefix_space=True)
   self.assertListEqual(UpperCamelCase    ,						UpperCamelCase  )

   lowerCamelCase_  				=						tokens + [tokenizer.unk_token]
   lowerCamelCase_  				=						[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase  )    ,						UpperCamelCase  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_tokenizer()

   self.assertListEqual(tokenizer.encode("Hello world!"    ,						add_special_tokens=UpperCamelCase  )    ,						[0, 3_1414, 232, 328, 2]  )
   self.assertListEqual(
       tokenizer.encode("Hello world! cécé herlolip 418"    ,						add_special_tokens=UpperCamelCase  )    ,						[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]    ,						)






  @slow
  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.tokenizer_class.from_pretrained("roberta-base"  )

   lowerCamelCase_  				=						tokenizer.encode("sequence builders"    ,						add_special_tokens=UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.encode("multi-sequence build"    ,						add_special_tokens=UpperCamelCase  )

   lowerCamelCase_  				=						tokenizer.encode(
       "sequence builders"    ,						add_special_tokens=UpperCamelCase    ,						add_prefix_space=UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.encode(
       "sequence builders"    ,						"multi-sequence build"    ,						add_special_tokens=UpperCamelCase    ,						add_prefix_space=UpperCamelCase  )

   lowerCamelCase_  				=						tokenizer.build_inputs_with_special_tokens(UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.build_inputs_with_special_tokens(UpperCamelCase    ,						UpperCamelCase  )

   assert encoded_sentence == encoded_text_from_decode
   assert encoded_pair == encoded_pair_from_decode






  def 						snake_case	(					self  ):







   """simple docstring"""
   lowerCamelCase_  				=						self.get_tokenizer()

   lowerCamelCase_  				=						"Encode this sequence."
   lowerCamelCase_  				=						tokenizer.byte_encoder[" ".encode("utf-8"  )[0]]

   # Testing encoder arguments
   lowerCamelCase_  				=						tokenizer.encode(UpperCamelCase    ,						add_special_tokens=UpperCamelCase    ,						add_prefix_space=UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
   self.assertNotEqual(UpperCamelCase    ,						UpperCamelCase  )

   lowerCamelCase_  				=						tokenizer.encode(UpperCamelCase    ,						add_special_tokens=UpperCamelCase    ,						add_prefix_space=UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
   self.assertEqual(UpperCamelCase    ,						UpperCamelCase  )

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

   # Testing spaces after special tokens
   lowerCamelCase_  				=						"<mask>"
   tokenizer.add_special_tokens(
       {"mask_token": AddedToken(UpperCamelCase    ,						lstrip=UpperCamelCase    ,						rstrip=UpperCamelCase  )}  )  # mask token has a left space
   lowerCamelCase_  				=						tokenizer.convert_tokens_to_ids(UpperCamelCase  )

   lowerCamelCase_  				=						"Encode <mask> sequence"
   lowerCamelCase_  				=						"Encode <mask>sequence"

   lowerCamelCase_  				=						tokenizer.encode(UpperCamelCase  )
   lowerCamelCase_  				=						encoded.index(UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
   self.assertEqual(UpperCamelCase    ,						UpperCamelCase  )

   lowerCamelCase_  				=						tokenizer.encode(UpperCamelCase  )
   lowerCamelCase_  				=						encoded.index(UpperCamelCase  )
   lowerCamelCase_  				=						tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
   self.assertNotEqual(UpperCamelCase    ,						UpperCamelCase  )






  def 						snake_case	(					self  ):







   """simple docstring"""
   pass






  def 						snake_case	(					self  ):







   """simple docstring"""




   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
    with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(UpperCamelCase    ,						**UpperCamelCase  )
     lowerCamelCase_  				=						self.tokenizer_class.from_pretrained(UpperCamelCase    ,						**UpperCamelCase  )
     lowerCamelCase_  				=						"A, <mask> AllenNLP sentence."
     lowerCamelCase_  				=						tokenizer_r.encode_plus(UpperCamelCase    ,						add_special_tokens=UpperCamelCase    ,						return_token_type_ids=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_p.encode_plus(UpperCamelCase    ,						add_special_tokens=UpperCamelCase    ,						return_token_type_ids=UpperCamelCase  )

     # 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"]  )    ,						)

     lowerCamelCase_  				=						tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]  )
     lowerCamelCase_  				=						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, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )
     self.assertSequenceEqual(tokens_r["input_ids"]    ,						[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )

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






  def 						snake_case	(					self  ):







   """simple docstring"""




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

    lowerCamelCase_  				=						json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()  )
    lowerCamelCase_  				=						json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()  )

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

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







  def 						snake_case	(					self  ):







   """simple docstring"""




   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
    with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
     lowerCamelCase_  				=						"hello"  # `hello` is a token in the vocabulary of `pretrained_name`
     lowerCamelCase_  				=						f'''{text_of_1_token} {text_of_1_token}'''

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(len(UpperCamelCase  ) + 1, len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(len(UpperCamelCase  ) + 1, len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(len(UpperCamelCase  ), len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(len(UpperCamelCase  ), len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						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)),
     # )

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(1, 1 + len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(1 + len(UpperCamelCase  ) + 1, 1 + len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, 1 + len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(1 + len(UpperCamelCase  ), 1 + len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)

     lowerCamelCase_  				=						self.rust_tokenizer_class.from_pretrained(
         UpperCamelCase    ,						use_fast=UpperCamelCase    ,						add_prefix_space=UpperCamelCase    ,						trim_offsets=UpperCamelCase  )
     lowerCamelCase_  				=						tokenizer_r(UpperCamelCase    ,						return_offsets_mapping=UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
     self.assertEqual(encoding.offset_mapping[0]    ,						(0, 1 + len(UpperCamelCase  ))  )
     self.assertEqual(
         encoding.offset_mapping[1]    ,						(1 + len(UpperCamelCase  ), 1 + len(UpperCamelCase  ) + 1 + len(UpperCamelCase  ))    ,						)







'''simple docstring'''

from collections.abc import Sequence





def __snake_case      (   UpperCAmelCase_		:		Sequence[int] | None = None	):
 if nums is None or not nums:
  raise ValueError("Input sequence should not be empty"	)

 lowerCamelCase_  				=						nums[0]
 for i in range(1      ,       len(UpperCAmelCase_	)	):
  lowerCamelCase_  				=						nums[i]
  lowerCamelCase_  				=						max(UpperCAmelCase_      ,       ans + num      ,       UpperCAmelCase_	)

 return ans


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     # Try on a sample input from the user
     a_						:       Any      			=				int(input("""Enter number of elements : """).strip())
     a_						:       Union[str, Any]      			=				list(map(int, input("""\nEnter the numbers : """).strip().split()))[:n]
     print(max_subsequence_sum(array))



