





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

         A_     :				Dict			      =	os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES["""vocab_file"""]       )
         A_     :				Dict			      =	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 		_lowerCamelCase      (		self      ,       **a__       ):
         kwargs.update(self.special_tokens_map       )
         return self.tokenizer_class.from_pretrained(self.tmpdirname      ,       **UpperCAmelCase__       )
      def 		_lowerCamelCase      (		self      ,       **a__       ):
         kwargs.update(self.special_tokens_map       )
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,       **UpperCAmelCase__       )
      def 		_lowerCamelCase      (		self      ,       a__       ):
         return "lower newer", "lower newer"
      @cached_property
      def 		_lowerCamelCase      (		self       ):
         return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""       )
      @cached_property
      def 		_lowerCamelCase      (		self       ):
         return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""       )
      @require_torch
      def 		_lowerCamelCase      (		self       ):
         A_     :				Union[str, Any]			      =	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         A_     :				Optional[int]			      =	[0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				Dict			      =	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       )
            A_     :				List[str]			      =	batch.input_ids.tolist()[0]
            self.assertListEqual(UpperCAmelCase__      ,       UpperCAmelCase__       )
      @require_torch
      def 		_lowerCamelCase      (		self       ):
         A_     :				str			      =	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				Any			      =	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 		_lowerCamelCase      (		self       ):
         A_     :				Optional[int]			      =	[
             '''Summary of the text.''',
             '''Another summary.''',
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				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 		_lowerCamelCase      (		self       ):
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				Tuple			      =	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 		_lowerCamelCase      (		self       ):
         A_     :				Optional[int]			      =	['''A long paragraph for summarization.''']
         A_     :				Any			      =	[
             '''Summary of the text.''',
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				List[Any]			      =	tokenizer(UpperCAmelCase__      ,       return_tensors="""pt"""       )
            A_     :				Optional[Any]			      =	tokenizer(text_target=UpperCAmelCase__      ,       return_tensors="""pt"""       )
            A_     :				Any			      =	inputs['''input_ids''']
            A_     :				List[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 		_lowerCamelCase      (		self       ):
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            A_     :				Any			      =	['''Summary of the text.''', '''Another summary.''']
            A_     :				Optional[int]			      =	[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

            A_     :				List[Any]			      =	tokenizer(UpperCAmelCase__      ,       padding=UpperCAmelCase__       )
            A_     :				Any			      =	[[0] * len(UpperCAmelCase__       ) for x in encoded_output['''input_ids''']]
            A_     :				Tuple			      =	tokenizer.pad(UpperCAmelCase__       )
            self.assertSequenceEqual(outputs["""global_attention_mask"""]      ,       UpperCAmelCase__       )
      def 		_lowerCamelCase      (		self       ):
         pass






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

               A_     :				Optional[int]			      =	tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]       )
               A_     :				str			      =	tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]       )
               self.assertSequenceEqual(tokens_p["""input_ids"""]      ,       [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]       )
               self.assertSequenceEqual(tokens_r["""input_ids"""]      ,       [0, 250, 6, 50264, 3823, 487, 21992, 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>"""]       )













_lowerCAmelCase 				=     """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""



def     _lowerCAmelCase		(  ):
   '''simple docstring'''


   A_     :				Any			      =	input("""Enter message: """     )
   A_     :				Dict			      =	input("""Enter key [alphanumeric]: """     )
   A_     :				Dict			      =	input("""Encrypt/Decrypt [e/d]: """     )

   if mode.lower().startswith("""e"""     ):
      A_     :				Union[str, Any]			      =	"""encrypt"""
      A_     :				Optional[int]			      =	encrypt_message(_lowerCAmelCase  ,_lowerCAmelCase     )
   elif mode.lower().startswith("""d"""     ):
      A_     :				str			      =	"""decrypt"""
      A_     :				Dict			      =	decrypt_message(_lowerCAmelCase  ,_lowerCAmelCase     )

   print(f"""\n{mode.title()}ed message:"""     )
   print(_lowerCAmelCase     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   return translate_message(_lowerCAmelCase  ,_lowerCAmelCase  ,"""encrypt"""     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   return translate_message(_lowerCAmelCase  ,_lowerCAmelCase  ,"""decrypt"""     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				Dict			      =	[]
   A_     :				List[Any]			      =	0
   A_     :				int			      =	key.upper()

   for symbol in message:
      A_     :				Optional[int]			      =	LETTERS.find(symbol.upper()     )
      if num != -1:
         if mode == "encrypt":
            num += LETTERS.find(key[key_index]     )
         elif mode == "decrypt":
            num -= LETTERS.find(key[key_index]     )

         num %= len(_lowerCAmelCase     )

         if symbol.isupper():
            translated.append(LETTERS[num]     )
         elif symbol.islower():
            translated.append(LETTERS[num].lower()     )

         key_index += 1
         if key_index == len(_lowerCAmelCase     ):
            A_     :				Dict			      =	0
      else:
         translated.append(_lowerCAmelCase     )
   return "".join(_lowerCAmelCase     )


if __name__ == "__main__":
      main()






