






import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase					,      unittest.TestCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  LongformerTokenizer
  _lowerCamelCase    =  True
  _lowerCamelCase    =  LongformerTokenizerFast
  _lowerCamelCase    =  True


  def  lowerCamelCase       (      self		:			int							)						->	Optional[int]:


         """simple docstring"""
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         _UpperCAmelCase							=    [
             """l""",
             """o""",
             """w""",
             """e""",
             """r""",
             """s""",
             """t""",
             """i""",
             """d""",
             """n""",
             """\u0120""",
             """\u0120l""",
             """\u0120n""",
             """\u0120lo""",
             """\u0120low""",
             """er""",
             """\u0120lowest""",
             """\u0120newer""",
             """\u0120wider""",
             """<unk>""",
         ]
         _UpperCAmelCase							=    dict(zip(lowerCamelCase       ,				range(len(lowerCamelCase							)							)							)							)
         _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(lowerCamelCase							) + """\n"""							)
         with open(self.merges_file       ,				"""w"""       ,				encoding="""utf-8"""							) as fp:
                fp.write("""\n""".join(lowerCamelCase							)							)


  def  lowerCamelCase       (      self		:			List[Any]       ,				**lowerCamelCase		:			str							)						->	Tuple:


         """simple docstring"""
         kwargs.update(self.special_tokens_map							)
         return self.tokenizer_class.from_pretrained(self.tmpdirname       ,				**lowerCamelCase							)


  def  lowerCamelCase       (      self		:			int       ,				**lowerCamelCase		:			str							)						->	int:


         """simple docstring"""
         kwargs.update(self.special_tokens_map							)
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname       ,				**lowerCamelCase							)


  def  lowerCamelCase       (      self		:			Union[str, Any]       ,				lowerCamelCase		:			Tuple							)						->	Optional[Any]:


         """simple docstring"""
         _UpperCAmelCase							=    """lower newer"""
         _UpperCAmelCase							=    """lower newer"""
         return input_text, output_text


  def  lowerCamelCase       (      self		:			Optional[Any]							)						->	str:


         """simple docstring"""
         _UpperCAmelCase							=    self.tokenizer_class(self.vocab_file       ,				self.merges_file       ,				**self.special_tokens_map							)
         _UpperCAmelCase							=    """lower newer"""
         _UpperCAmelCase							=    ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
         _UpperCAmelCase							=    tokenizer.tokenize(lowerCamelCase							)  # , add_prefix_space=True)
         self.assertListEqual(lowerCamelCase       ,				lowerCamelCase							)

         _UpperCAmelCase							=    tokens + [tokenizer.unk_token]
         _UpperCAmelCase							=    [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase							)       ,				lowerCamelCase							)


  def  lowerCamelCase       (      self		:			Dict							)						->	Tuple:


         """simple docstring"""
         _UpperCAmelCase							=    self.get_tokenizer()

         self.assertListEqual(tokenizer.encode("""Hello world!"""       ,				add_special_tokens=lowerCamelCase							)       ,				[0, 3_1414, 232, 328, 2]							)
         self.assertListEqual(
             tokenizer.encode("""Hello world! cécé herlolip 418"""       ,				add_special_tokens=lowerCamelCase							)       ,				[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]       ,				)


  @slow
  def  lowerCamelCase       (      self		:			Dict							)						->	Union[str, Any]:


         """simple docstring"""
         _UpperCAmelCase							=    self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""							)

         _UpperCAmelCase							=    tokenizer.encode("""sequence builders"""       ,				add_special_tokens=lowerCamelCase							)
         _UpperCAmelCase							=    tokenizer.encode("""multi-sequence build"""       ,				add_special_tokens=lowerCamelCase							)

         _UpperCAmelCase							=    tokenizer.encode(
             """sequence builders"""       ,				add_special_tokens=lowerCamelCase       ,				add_prefix_space=lowerCamelCase							)
         _UpperCAmelCase							=    tokenizer.encode(
             """sequence builders"""       ,				"""multi-sequence build"""       ,				add_special_tokens=lowerCamelCase       ,				add_prefix_space=lowerCamelCase							)

         _UpperCAmelCase							=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase							)
         _UpperCAmelCase							=    tokenizer.build_inputs_with_special_tokens(lowerCamelCase       ,				lowerCamelCase							)

         assert encoded_sentence == encoded_text_from_decode
         assert encoded_pair == encoded_pair_from_decode


  def  lowerCamelCase       (      self		:			Optional[int]							)						->	str:


         """simple docstring"""
         _UpperCAmelCase							=    self.get_tokenizer()

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

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

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

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

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

         _UpperCAmelCase							=    """Encode <mask> sequence"""
         _UpperCAmelCase							=    """Encode <mask>sequence"""

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

         _UpperCAmelCase							=    tokenizer.encode(lowerCamelCase							)
         _UpperCAmelCase							=    encoded.index(lowerCamelCase							)
         _UpperCAmelCase							=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]							)[0]
         self.assertNotEqual(lowerCamelCase       ,				lowerCamelCase							)


  def  lowerCamelCase       (      self		:			Optional[Any]							)						->	Union[str, Any]:


         """simple docstring"""
         pass


  def  lowerCamelCase       (      self		:			Any							)						->	Union[str, Any]:


         """simple docstring"""
         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(lowerCamelCase       ,				**lowerCamelCase							)
                       _UpperCAmelCase							=    self.tokenizer_class.from_pretrained(lowerCamelCase       ,				**lowerCamelCase							)
                       _UpperCAmelCase							=    """A, <mask> AllenNLP sentence."""
                       _UpperCAmelCase							=    tokenizer_r.encode_plus(lowerCamelCase       ,				add_special_tokens=lowerCamelCase       ,				return_token_type_ids=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_p.encode_plus(lowerCamelCase       ,				add_special_tokens=lowerCamelCase       ,				return_token_type_ids=lowerCamelCase							)

                       # 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, 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(
                           lowerCamelCase       ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)
                       self.assertSequenceEqual(
                           lowerCamelCase       ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)


  def  lowerCamelCase       (      self		:			int							)						->	str:


         """simple docstring"""
         for trim_offsets, add_prefix_space in itertools.product([True, False]       ,				repeat=2							):
                _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                    self.tmpdirname       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)

                _UpperCAmelCase							=    json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()							)
                _UpperCAmelCase							=    json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()							)

                self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]       ,				lowerCamelCase							)

                self.assertEqual(post_processor_state["""add_prefix_space"""]       ,				lowerCamelCase							)
                self.assertEqual(post_processor_state["""trim_offsets"""]       ,				lowerCamelCase							)





  def  lowerCamelCase       (      self		:			Dict							)						->	Tuple:


         """simple docstring"""
         # 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})"""							):
                       _UpperCAmelCase							=    """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                       _UpperCAmelCase							=    f"""{text_of_1_token} {text_of_1_token}"""

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(len(lowerCamelCase							) + 1, len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(len(lowerCamelCase							) + 1, len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(len(lowerCamelCase							), len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(len(lowerCamelCase							), len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    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)),
                       # )

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(1, 1 + len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(1 + len(lowerCamelCase							) + 1, 1 + len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, 1 + len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(1 + len(lowerCamelCase							), 1 + len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)

                       _UpperCAmelCase							=    self.rust_tokenizer_class.from_pretrained(
                           lowerCamelCase       ,				use_fast=lowerCamelCase       ,				add_prefix_space=lowerCamelCase       ,				trim_offsets=lowerCamelCase							)
                       _UpperCAmelCase							=    tokenizer_r(lowerCamelCase       ,				return_offsets_mapping=lowerCamelCase       ,				add_special_tokens=lowerCamelCase							)
                       self.assertEqual(encoding.offset_mapping[0]       ,				(0, 1 + len(lowerCamelCase							))							)
                       self.assertEqual(
                           encoding.offset_mapping[1]       ,				(1 + len(lowerCamelCase							), 1 + len(lowerCamelCase							) + 1 + len(lowerCamelCase							))       ,				)



import random
from typing import Any






def 	__lowerCamelCase						(							lowerCamelCase__		:						list      ):





			'''simple docstring'''




			for _ in range(len(lowerCamelCase__      )      ):
						lowerCamelCase    		=  random.randint(0  ,							len(lowerCamelCase__      ) - 1      )
						lowerCamelCase    		=  random.randint(0  ,							len(lowerCamelCase__      ) - 1      )
						lowerCamelCase		,		lowerCamelCase    		=  data[b], data[a]
			return data


if __name__ == "__main__":
		UpperCAmelCase   :    str     =		[0, 1, 2, 3, 4, 5, 6, 7]
		UpperCAmelCase   :    Union[str, Any]     =		["python", "says", "hello", "!"]
		print("Fisher-Yates Shuffle:")
		print("List", integers, strings)
		print("FY Shuffle", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))

