

import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors






@require_tokenizers
class 						__magic_name__					(							snake_case			,      unittest.TestCase				):
     UpperCamelCase_	:Any										=      MvpTokenizer
     UpperCamelCase_	:int										=      MvpTokenizerFast
     UpperCamelCase_	:Optional[int]										=      True
     UpperCamelCase_	:int										=      filter_roberta_detectors






     def 	UpperCAmelCase_				(				self	)->     int:
         super().setUp()
         UpperCamelCase_			  =						[
             "l",
             "o",
             "w",
             "e",
             "r",
             "s",
             "t",
             "i",
             "d",
             "n",
             "\u0120",
             "\u0120l",
             "\u0120n",
             "\u0120lo",
             "\u0120low",
             "er",
             "\u0120lowest",
             "\u0120newer",
             "\u0120wider",
             "<unk>",
         ]
         UpperCamelCase_			  =						dict(zip(_lowercase		,						range(len(_lowercase	)	)	)	)
         UpperCamelCase_			  =						["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
         UpperCamelCase_			  =						{"unk_token": "<unk>"}

         UpperCamelCase_			  =						os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["vocab_file"]	)
         UpperCamelCase_			  =						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		,						**_lowercase	)->     Dict:
         kwargs.update(self.special_tokens_map	)
         return self.tokenizer_class.from_pretrained(self.tmpdirname		,						**_lowercase	)






     def 	UpperCAmelCase_				(				self		,						**_lowercase	)->     Optional[Any]:
         kwargs.update(self.special_tokens_map	)
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname		,						**_lowercase	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Optional[int]:
         return "lower newer", "lower newer"






     @cached_property
     def 	UpperCAmelCase_				(				self	)->     List[str]:
         return MvpTokenizer.from_pretrained("RUCAIBox/mvp"	)






     @cached_property
     def 	UpperCAmelCase_				(				self	)->     int:
         return MvpTokenizerFast.from_pretrained("RUCAIBox/mvp"	)






     @require_torch
     def 	UpperCAmelCase_				(				self	)->     List[str]:
         UpperCamelCase_			  =						["A long paragraph for summarization.", "Another paragraph for summarization."]
         UpperCamelCase_			  =						[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             UpperCamelCase_			  =						tokenizer(_lowercase		,						max_length=len(_lowercase	)		,						padding=_lowercase		,						return_tensors="pt"	)
             self.assertIsInstance(_lowercase		,						_lowercase	)

             self.assertEqual((2, 9)		,						batch.input_ids.shape	)
             self.assertEqual((2, 9)		,						batch.attention_mask.shape	)
             UpperCamelCase_			  =						batch.input_ids.tolist()[0]
             self.assertListEqual(_lowercase		,						_lowercase	)
             # Test that special tokens are reset






     @require_torch
     def 	UpperCAmelCase_				(				self	)->     Dict:
         UpperCamelCase_			  =						["A long paragraph for summarization.", "Another paragraph for summarization."]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             UpperCamelCase_			  =						tokenizer(_lowercase		,						padding=_lowercase		,						return_tensors="pt"	)
             # check if input_ids are returned and no labels
             self.assertIn("input_ids"		,						_lowercase	)
             self.assertIn("attention_mask"		,						_lowercase	)
             self.assertNotIn("labels"		,						_lowercase	)
             self.assertNotIn("decoder_attention_mask"		,						_lowercase	)






     @require_torch
     def 	UpperCAmelCase_				(				self	)->     List[Any]:
         UpperCamelCase_			  =						[
             "Summary of the text.",
             "Another summary.",
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             UpperCamelCase_			  =						tokenizer(text_target=_lowercase		,						max_length=32		,						padding="max_length"		,						return_tensors="pt"	)
             self.assertEqual(32		,						targets["input_ids"].shape[1]	)






     @require_torch
     def 	UpperCAmelCase_				(				self	)->     Optional[int]:
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             UpperCamelCase_			  =						tokenizer(
                 ["I am a small frog" * 1_024, "I am a small frog"]		,						padding=_lowercase		,						truncation=_lowercase		,						return_tensors="pt"	)
             self.assertIsInstance(_lowercase		,						_lowercase	)
             self.assertEqual(batch.input_ids.shape		,						(2, 1_024)	)






     @require_torch
     def 	UpperCAmelCase_				(				self	)->     Union[str, Any]:
         UpperCamelCase_			  =						["A long paragraph for summarization."]
         UpperCamelCase_			  =						[
             "Summary of the text.",
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             UpperCamelCase_			  =						tokenizer(_lowercase		,						text_target=_lowercase		,						return_tensors="pt"	)
             UpperCamelCase_			  =						inputs["input_ids"]
             UpperCamelCase_			  =						inputs["labels"]
             self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()	)
             self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()	)
             self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()	)
             self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()	)






     def 	UpperCAmelCase_				(				self	)->     Dict:
         pass






     def 	UpperCAmelCase_				(				self	)->     List[Any]:
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"	):
                 UpperCamelCase_			  =						self.rust_tokenizer_class.from_pretrained(_lowercase		,						**_lowercase	)
                 UpperCamelCase_			  =						self.tokenizer_class.from_pretrained(_lowercase		,						**_lowercase	)
                 UpperCamelCase_			  =						"A, <mask> AllenNLP sentence."
                 UpperCamelCase_			  =						tokenizer_r.encode_plus(_lowercase		,						add_special_tokens=_lowercase		,						return_token_type_ids=_lowercase	)
                 UpperCamelCase_			  =						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"]	)		,						)

                 UpperCamelCase_			  =						tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]	)
                 UpperCamelCase_			  =						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, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]	)
                 self.assertSequenceEqual(tokens_r["input_ids"]		,						[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 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 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_ = 4_0_0_0_0_0_0			)->						int:



    """simple docstring"""






    UpperCamelCase_			  =						[0, 1]
    UpperCamelCase_			  =						0
    while fib[i] <= n:
        fib.append(fib[i] + fib[i + 1]			)
        if fib[i + 2] > n:
            break
        i += 1
    UpperCamelCase_			  =						0
    for j in range(len(SCREAMING_SNAKE_CASE_			) - 1			):
        if fib[j] % 2 == 0:
            total += fib[j]

    return total


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