


import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led 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






@require_tokenizers
class      UpperCamelCase					(		lowercase__						,      unittest.TestCase     ):


   '''simple docstring'''







   lowercase					:	Optional[int]									=LEDTokenizer
   lowercase					:	Any									=LEDTokenizerFast
   lowercase					:	Any									=True
   def 		UpperCamelCase  (     self		):
        super().setUp()
        lowercase_       :List[Any]     =       [
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''\u0120''',
            '''\u0120l''',
            '''\u0120n''',
            '''\u0120lo''',
            '''\u0120low''',
            '''er''',
            '''\u0120lowest''',
            '''\u0120newer''',
            '''\u0120wider''',
            '''<unk>''',
        ]
        lowercase_       :str     =       dict(zip(UpperCamelCase_   ,							range(len(UpperCamelCase_		)		)		)		)
        lowercase_       :List[Any]     =       ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
        lowercase_       :Optional[Any]     =       {'''unk_token''': '''<unk>'''}

        lowercase_       :Tuple     =       os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES['''vocab_file''']		)
        lowercase_       :List[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(UpperCamelCase_		) + '''\n'''		)
        with open(self.merges_file   ,							'''w'''   ,							encoding='''utf-8'''		) as fp:
             fp.write('''\n'''.join(UpperCamelCase_		)		)
   def 		UpperCamelCase  (     self   ,							**UpperCamelCase_		):
        kwargs.update(self.special_tokens_map		)
        return self.tokenizer_class.from_pretrained(self.tmpdirname   ,							**UpperCamelCase_		)
   def 		UpperCamelCase  (     self   ,							**UpperCamelCase_		):
        kwargs.update(self.special_tokens_map		)
        return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,							**UpperCamelCase_		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_		):
        return "lower newer", "lower newer"
   @cached_property
   def 		UpperCamelCase  (     self		):
        return LEDTokenizer.from_pretrained('''allenai/led-base-16384'''		)
   @cached_property
   def 		UpperCamelCase  (     self		):
        return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384'''		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :List[str]     =       ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        lowercase_       :str     =       [0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :List[Any]     =       tokenizer(UpperCamelCase_   ,							max_length=len(UpperCamelCase_		)   ,							padding=UpperCamelCase_   ,							return_tensors='''pt'''		)
             self.assertIsInstance(UpperCamelCase_   ,							UpperCamelCase_		)

             self.assertEqual((2, 9)   ,							batch.input_ids.shape		)
             self.assertEqual((2, 9)   ,							batch.attention_mask.shape		)
             lowercase_       :Union[str, Any]     =       batch.input_ids.tolist()[0]
             self.assertListEqual(UpperCamelCase_   ,							UpperCamelCase_		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Tuple     =       ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :str     =       tokenizer(UpperCamelCase_   ,							padding=UpperCamelCase_   ,							return_tensors='''pt'''		)
             self.assertIn('''input_ids'''   ,							UpperCamelCase_		)
             self.assertIn('''attention_mask'''   ,							UpperCamelCase_		)
             self.assertNotIn('''labels'''   ,							UpperCamelCase_		)
             self.assertNotIn('''decoder_attention_mask'''   ,							UpperCamelCase_		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Optional[Any]     =       [
            '''Summary of the text.''',
            '''Another summary.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :List[str]     =       tokenizer(text_target=UpperCamelCase_   ,							max_length=32   ,							padding='''max_length'''   ,							return_tensors='''pt'''		)
             self.assertEqual(32   ,							targets['''input_ids'''].shape[1]		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :Union[str, Any]     =       tokenizer(
                 ['''I am a small frog''' * 1024, '''I am a small frog''']   ,							padding=UpperCamelCase_   ,							truncation=UpperCamelCase_   ,							return_tensors='''pt'''		)
             self.assertIsInstance(UpperCamelCase_   ,							UpperCamelCase_		)
             self.assertEqual(batch.input_ids.shape   ,							(2, 5122)		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Union[str, Any]     =       ['''A long paragraph for summarization.''']
        lowercase_       :Any     =       [
            '''Summary of the text.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :Tuple     =       tokenizer(UpperCamelCase_   ,							return_tensors='''pt'''		)
             lowercase_       :int     =       tokenizer(text_target=UpperCamelCase_   ,							return_tensors='''pt'''		)
             lowercase_       :Union[str, Any]     =       inputs['''input_ids''']
             lowercase_       :Any     =       targets['''input_ids''']
             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()		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
             lowercase_       :Union[str, Any]     =       ['''Summary of the text.''', '''Another summary.''']
             lowercase_       :int     =       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

             lowercase_       :Any     =       tokenizer(UpperCamelCase_   ,							padding=UpperCamelCase_		)
             lowercase_       :Union[str, Any]     =       [[0] * len(UpperCamelCase_		) for x in encoded_output['''input_ids''']]
             lowercase_       :List[Any]     =       tokenizer.pad(UpperCamelCase_		)
             self.assertSequenceEqual(outputs['''global_attention_mask''']   ,							UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        pass




   def 		UpperCamelCase  (     self		):
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                  lowercase_       :Optional[int]     =       self.rust_tokenizer_class.from_pretrained(UpperCamelCase_   ,							**UpperCamelCase_		)
                  lowercase_       :Union[str, Any]     =       self.tokenizer_class.from_pretrained(UpperCamelCase_   ,							**UpperCamelCase_		)
                  lowercase_       :int     =       '''A, <mask> AllenNLP sentence.'''
                  lowercase_       :Any     =       tokenizer_r.encode_plus(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_   ,							return_token_type_ids=UpperCamelCase_		)
                  lowercase_       :Dict     =       tokenizer_p.encode_plus(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_   ,							return_token_type_ids=UpperCamelCase_		)
                  self.assertEqual(sum(tokens_r['''token_type_ids''']		)   ,							sum(tokens_p['''token_type_ids''']		)		)
                  self.assertEqual(
                      sum(tokens_r['''attention_mask''']		) / len(tokens_r['''attention_mask''']		)   ,							sum(tokens_p['''attention_mask''']		) / len(tokens_p['''attention_mask''']		)   ,							)

                  lowercase_       :List[str]     =       tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']		)
                  lowercase_       :str     =       tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']		)
                  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>''']		)





import math

SCREAMING_SNAKE_CASE       :		List[str]         =				10
SCREAMING_SNAKE_CASE       :		Dict         =				7
SCREAMING_SNAKE_CASE       :		int         =				BALLS_PER_COLOUR * NUM_COLOURS




def     UpperCamelCase    (      _a = 2_0		)					->							str:
     '''simple docstring'''





     lowercase_       :List[str]     =       math.comb(_a       ,		_a		)
     lowercase_       :Tuple     =       math.comb(NUM_BALLS - BALLS_PER_COLOUR       ,		_a		)

     lowercase_       :Dict     =       NUM_COLOURS * (1 - missing_colour / total)

     return f"{result:.9f}"


if __name__ == "__main__":
   print(solution(20))

