





'''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   UpperCAmelCase      (			UpperCamelCase__     ,			unittest.TestCase							):
 __lowercase  						=							RobertaTokenizer
 __lowercase  						=							RobertaTokenizerFast
 __lowercase  						=							True
 __lowercase  						=							{"""cls_token""": """<s>"""}
 def 	UpperCAmelCase_				(							self :Optional[Any]				)->				Optional[int]:
     super().setUp()

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

     A__							=     os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES["vocab_file"]				)
     A__							=     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 	UpperCAmelCase_				(							self :Optional[int]		,			**lowercase_ :Optional[int]				)->				str:
     kwargs.update(self.special_tokens_map				)
     return self.tokenizer_class.from_pretrained(self.tmpdirname		,			**lowercase_				)
 def 	UpperCAmelCase_				(							self :Any		,			**lowercase_ :Tuple				)->				str:
     kwargs.update(self.special_tokens_map				)
     return RobertaTokenizerFast.from_pretrained(self.tmpdirname		,			**lowercase_				)
 def 	UpperCAmelCase_				(							self :Any		,			lowercase_ :int				)->				str:
     A__							=     "lower newer"
     A__							=     "lower newer"
     return input_text, output_text
 def 	UpperCAmelCase_				(							self :Any				)->				Any:
     A__							=     self.tokenizer_class(self.vocab_file		,			self.merges_file		,			**self.special_tokens_map				)
     A__							=     "lower newer"
     A__							=     ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
     A__							=     tokenizer.tokenize(lowercase_				)  # , add_prefix_space=True)
     self.assertListEqual(lowercase_		,			lowercase_				)

     A__							=     tokens + [tokenizer.unk_token]
     A__							=     [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_				)		,			lowercase_				)
 def 	UpperCAmelCase_				(							self :int				)->				str:
     A__							=     self.get_tokenizer()

     self.assertListEqual(tokenizer.encode("Hello world!"		,			add_special_tokens=lowercase_				)		,			[0, 3_14_14, 2_32, 3_28, 2]				)
     self.assertListEqual(
         tokenizer.encode("Hello world! cécé herlolip 418"		,			add_special_tokens=lowercase_				)		,			[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]		,			)
 @slow
 def 	UpperCAmelCase_				(							self :str				)->				Dict:
     A__							=     self.tokenizer_class.from_pretrained("roberta-base"				)

     A__							=     tokenizer.encode("sequence builders"		,			add_special_tokens=lowercase_				)
     A__							=     tokenizer.encode("multi-sequence build"		,			add_special_tokens=lowercase_				)

     A__							=     tokenizer.encode(
         "sequence builders"		,			add_special_tokens=lowercase_		,			add_prefix_space=lowercase_				)
     A__							=     tokenizer.encode(
         "sequence builders"		,			"multi-sequence build"		,			add_special_tokens=lowercase_		,			add_prefix_space=lowercase_				)

     A__							=     tokenizer.build_inputs_with_special_tokens(lowercase_				)
     A__							=     tokenizer.build_inputs_with_special_tokens(lowercase_		,			lowercase_				)

     assert encoded_sentence == encoded_text_from_decode
     assert encoded_pair == encoded_pair_from_decode
 def 	UpperCAmelCase_				(							self :Optional[int]				)->				int:
     A__							=     self.get_tokenizer()

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

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

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

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

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

     A__							=     "Encode <mask> sequence"
     A__							=     "Encode <mask>sequence"

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

     A__							=     tokenizer.encode(lowercase_				)
     A__							=     encoded.index(lowercase_				)
     A__							=     tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
     self.assertNotEqual(lowercase_		,			lowercase_				)
 def 	UpperCAmelCase_				(							self :Tuple				)->				int:
     pass
 def 	UpperCAmelCase_				(							self :List[str]				)->				Tuple:
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
             A__							=     self.rust_tokenizer_class.from_pretrained(lowercase_		,			**lowercase_				)
             A__							=     self.tokenizer_class.from_pretrained(lowercase_		,			**lowercase_				)
             A__							=     "A, <mask> AllenNLP sentence."
             A__							=     tokenizer_r.encode_plus(lowercase_		,			add_special_tokens=lowercase_		,			return_token_type_ids=lowercase_				)
             A__							=     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__							=     tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]				)
             A__							=     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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)
             self.assertSequenceEqual(tokens_r["input_ids"]		,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 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 	UpperCAmelCase_				(							self :Union[str, Any]				)->				List[Any]:
     for trim_offsets, add_prefix_space in itertools.product([True, False]		,			repeat=2				):
         A__							=     self.rust_tokenizer_class.from_pretrained(
             self.tmpdirname		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)

         A__							=     json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()				)
         A__							=     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 	UpperCAmelCase_				(							self :List[str]				)->				Optional[int]:
     # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
     # `trim_offsets`
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
             A__							=     "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
             A__							=     F"{text_of_1_token} {text_of_1_token}"

             A__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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__							=     self.rust_tokenizer_class.from_pretrained(
                 lowercase_		,			use_fast=lowercase_		,			add_prefix_space=lowercase_		,			trim_offsets=lowercase_				)
             A__							=     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_				))		,			)










'''simple docstring'''

__lowerCAmelCase				:      List[str]						      ="Alexander Joslin"

import operator as op

from .stack import Stack





def 		UpperCamelCase							(				_lowerCamelCase   :   str			):
    A__							=     {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}

    A__							=     Stack()
    A__							=     Stack()

    for i in equation:
        if i.isdigit():
            # RULE 1
            operand_stack.push(int(_lowerCamelCase			)			)
        elif i in operators:
            # RULE 2
            operator_stack.push(_lowerCamelCase			)
        elif i == ")":
            # RULE 4
            A__							=     operator_stack.peek()
            operator_stack.pop()
            A__							=     operand_stack.peek()
            operand_stack.pop()
            A__							=     operand_stack.peek()
            operand_stack.pop()

            A__							=     operators[opr](_lowerCamelCase		,			_lowerCamelCase			)
            operand_stack.push(_lowerCamelCase			)

    # RULE 5
    return operand_stack.peek()


if __name__ == "__main__":
  __lowerCAmelCase				:      Dict						      ="(5 + ((4 * 2) * (2 + 3)))"
  # answer = 45
  print(f"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")



