





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     SCREAMING_SNAKE_CASE__ (						__A				,					unittest.TestCase      ):
 __SCREAMING_SNAKE_CASE							       =	LEDTokenizer
 __SCREAMING_SNAKE_CASE							       =	LEDTokenizerFast
 __SCREAMING_SNAKE_CASE							       =	True



 def 				UpperCamelCase			(							self ):
        super().setUp()
        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,**__lowerCamelCase ):
        kwargs.update(self.special_tokens_map )
        return self.tokenizer_class.from_pretrained(self.tmpdirname,**lowercase_ )



 def 				UpperCamelCase			(							self,**__lowerCamelCase ):
        kwargs.update(self.special_tokens_map )
        return self.rust_tokenizer_class.from_pretrained(self.tmpdirname,**lowercase_ )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        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 ):
        A__											=						["A long paragraph for summarization.", "Another paragraph for summarization."]
        A__											=						[0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               A__											=						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 )
               A__											=						batch.input_ids.tolist()[0]
               self.assertListEqual(lowercase_,lowercase_ )



 @require_torch
 def 				UpperCamelCase			(							self ):
        A__											=						["A long paragraph for summarization.", "Another paragraph for summarization."]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               A__											=						tokenizer(lowercase_,padding=lowercase_,return_tensors='''pt''' )
               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 ):
        A__											=						[
            "Summary of the text.",
            "Another summary.",
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               A__											=						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 ):
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               A__											=						tokenizer(
                   ['''I am a small frog''' * 1024, '''I am a small frog'''],padding=lowercase_,truncation=lowercase_,return_tensors='''pt''' )
               self.assertIsInstance(lowercase_,lowercase_ )
               self.assertEqual(batch.input_ids.shape,(2, 5122) )



 @require_torch
 def 				UpperCamelCase			(							self ):
        A__											=						["A long paragraph for summarization."]
        A__											=						[
            "Summary of the text.",
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               A__											=						tokenizer(lowercase_,return_tensors='''pt''' )
               A__											=						tokenizer(text_target=lowercase_,return_tensors='''pt''' )
               A__											=						inputs["input_ids"]
               A__											=						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]:
               A__											=						["Summary of the text.", "Another summary."]
               A__											=						[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

               A__											=						tokenizer(lowercase_,padding=lowercase_ )
               A__											=						[[0] * len(lowercase_ ) for x in encoded_output["input_ids"]]
               A__											=						tokenizer.pad(lowercase_ )
               self.assertSequenceEqual(outputs['''global_attention_mask'''],lowercase_ )



 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})" ):
                      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_ )
                      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'''] ),)

                      A__											=						tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''] )
                      A__											=						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(
                          lowercase_,['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''] )
                      self.assertSequenceEqual(
                          lowercase_,['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''] )






def 			lowercase_				(			_lowerCamelCase							:       int):
    lowercase__ :   Dict    					=				n ** (1 / 3)
    return (val * val * val) == n


if __name__ == "__main__":
      print(perfect_cube(27))
      print(perfect_cube(4))



