
'''simple docstring'''






import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class  UpperCAmelCase__						(       snake_case__						,	unittest.TestCase ):
    lowerCAmelCase_				    =		GPTaTokenizer
    lowerCAmelCase_				    =		GPTaTokenizerFast
    lowerCAmelCase_				    =		True
    lowerCAmelCase_				    =		{'add_prefix_space': True}
    lowerCAmelCase_				    =		False



    def   lowerCamelCase_  (	self      :       Any     ):
          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          _lowerCamelCase				:   str								=   [
              "l",
              "o",
              "w",
              "e",
              "r",
              "s",
              "t",
              "i",
              "d",
              "n",
              "\u0120",
              "\u0120l",
              "\u0120n",
              "\u0120lo",
              "\u0120low",
              "er",
              "\u0120lowest",
              "\u0120newer",
              "\u0120wider",
              "<unk>",
              "<|endoftext|>",
          ]
          _lowerCamelCase				:   List[str]								=   dict(zip(lowercase_,range(len(lowercase_     )     )     )     )
          _lowerCamelCase				:   str								=   ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
          _lowerCamelCase				:   Any								=   {"unk_token": "<unk>"}

          _lowerCamelCase				:   Optional[Any]								=   os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["vocab_file"]     )
          _lowerCamelCase				:   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(lowercase_     ) + "\n"     )
          with open(self.merges_file,"w",encoding="utf-8"     ) as fp:
                fp.write("\n".join(lowercase_     )     )



    def   lowerCamelCase_  (	self      :       Dict,**__A      :       Optional[Any]     ):
          kwargs.update(self.special_tokens_map     )
          return GPTaTokenizer.from_pretrained(self.tmpdirname,**lowercase_     )



    def   lowerCamelCase_  (	self      :       Any,**__A      :       Any     ):
          kwargs.update(self.special_tokens_map     )
          return GPTaTokenizerFast.from_pretrained(self.tmpdirname,**lowercase_     )



    def   lowerCamelCase_  (	self      :       Dict,__A      :       List[Any]     ):
          _lowerCamelCase				:   int								=   "lower newer"
          _lowerCamelCase				:   Any								=   "lower newer"
          return input_text, output_text



    def   lowerCamelCase_  (	self      :       Union[str, Any]     ):
          _lowerCamelCase				:   Tuple								=   GPTaTokenizer(self.vocab_file,self.merges_file,**self.special_tokens_map     )
          _lowerCamelCase				:   List[Any]								=   "lower newer"
          _lowerCamelCase				:   str								=   ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
          _lowerCamelCase				:   str								=   tokenizer.tokenize(lowercase_,add_prefix_space=lowercase_     )
          self.assertListEqual(lowercase_,lowercase_     )

          _lowerCamelCase				:   int								=   tokens + [tokenizer.unk_token]
          _lowerCamelCase				:   Dict								=   [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_     ),lowercase_     )



    def   lowerCamelCase_  (	self      :       List[Any]     ):
          if not self.test_rust_tokenizer:
                return

          _lowerCamelCase				:   int								=   self.get_tokenizer()
          _lowerCamelCase				:   List[Any]								=   self.get_rust_tokenizer(add_prefix_space=lowercase_     )

          _lowerCamelCase				:   Union[str, Any]								=   "lower newer"

          # Testing tokenization
          _lowerCamelCase				:   List[str]								=   tokenizer.tokenize(lowercase_,add_prefix_space=lowercase_     )
          _lowerCamelCase				:   int								=   rust_tokenizer.tokenize(lowercase_     )
          self.assertListEqual(lowercase_,lowercase_     )

          # Testing conversion to ids without special tokens
          _lowerCamelCase				:   int								=   tokenizer.encode(lowercase_,add_special_tokens=lowercase_,add_prefix_space=lowercase_     )
          _lowerCamelCase				:   int								=   rust_tokenizer.encode(lowercase_,add_special_tokens=lowercase_     )
          self.assertListEqual(lowercase_,lowercase_     )

          # Testing conversion to ids with special tokens
          _lowerCamelCase				:   Optional[Any]								=   self.get_rust_tokenizer(add_prefix_space=lowercase_     )
          _lowerCamelCase				:   str								=   tokenizer.encode(lowercase_,add_prefix_space=lowercase_     )
          _lowerCamelCase				:   Optional[int]								=   rust_tokenizer.encode(lowercase_     )
          self.assertListEqual(lowercase_,lowercase_     )

          # Testing the unknown token
          _lowerCamelCase				:   int								=   tokens + [rust_tokenizer.unk_token]
          _lowerCamelCase				:   Optional[int]								=   [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
          self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowercase_     ),lowercase_     )



    def   lowerCamelCase_  (	self      :       List[str],*__A      :       Union[str, Any],**__A      :       Union[str, Any]     ):
          # It's very difficult to mix/test pretokenization with byte-level
          # And get both GPT2 and Roberta to work at the same time (mostly an issue of adding a space before the string)
          pass



    def   lowerCamelCase_  (	self      :       Tuple,__A      :       List[str]=1_5     ):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'     ):
                      _lowerCamelCase				:   int								=   self.rust_tokenizer_class.from_pretrained(lowercase_,**lowercase_     )

                      # Simple input
                      _lowerCamelCase				:   int								=   "This is a simple input"
                      _lowerCamelCase				:   List[str]								=   ["This is a simple input 1", "This is a simple input 2"]
                      _lowerCamelCase				:   str								=   ("This is a simple input", "This is a pair")
                      _lowerCamelCase				:   Union[str, Any]								=   [
                          ("This is a simple input 1", "This is a simple input 2"),
                          ("This is a simple pair 1", "This is a simple pair 2"),
                      ]

                      # Simple input tests
                      self.assertRaises(lowercase_,tokenizer_r.encode,lowercase_,max_length=lowercase_,padding="max_length"     )

                      # Simple input
                      self.assertRaises(lowercase_,tokenizer_r.encode_plus,lowercase_,max_length=lowercase_,padding="max_length"     )

                      # Simple input
                      self.assertRaises(
                          lowercase_,tokenizer_r.batch_encode_plus,lowercase_,max_length=lowercase_,padding="max_length",)

                      # Pair input
                      self.assertRaises(lowercase_,tokenizer_r.encode,lowercase_,max_length=lowercase_,padding="max_length"     )

                      # Pair input
                      self.assertRaises(lowercase_,tokenizer_r.encode_plus,lowercase_,max_length=lowercase_,padding="max_length"     )

                      # Pair input
                      self.assertRaises(
                          lowercase_,tokenizer_r.batch_encode_plus,lowercase_,max_length=lowercase_,padding="max_length",)



    def   lowerCamelCase_  (	self      :       int     ):
          _lowerCamelCase				:   int								=   GPTaTokenizer.from_pretrained(self.tmpdirname,pad_token="<pad>"     )

          # Simple input
          _lowerCamelCase				:   Dict								=   "This is a simple input"
          _lowerCamelCase				:   Optional[Any]								=   ["This is a simple input looooooooong", "This is a simple input"]
          _lowerCamelCase				:   Optional[Any]								=   ("This is a simple input", "This is a pair")
          _lowerCamelCase				:   int								=   [
              ("This is a simple input loooooong", "This is a simple input"),
              ("This is a simple pair loooooong", "This is a simple pair"),
          ]

          _lowerCamelCase				:   Optional[int]								=   tokenizer.pad_token_id

          _lowerCamelCase				:   Optional[int]								=   tokenizer(lowercase_,padding="max_length",max_length=3_0,return_tensors="np"     )
          _lowerCamelCase				:   Optional[int]								=   tokenizer(lowercase_,padding=lowercase_,truncate=lowercase_,return_tensors="np"     )
          _lowerCamelCase				:   List[str]								=   tokenizer(*lowercase_,padding="max_length",max_length=6_0,return_tensors="np"     )
          _lowerCamelCase				:   Tuple								=   tokenizer(lowercase_,padding=lowercase_,truncate=lowercase_,return_tensors="np"     )

          # s
          # test single string max_length padding
          self.assertEqual(out_s["input_ids"].shape[-1],3_0     )
          self.assertTrue(pad_token_id in out_s["input_ids"]     )
          self.assertTrue(0 in out_s["attention_mask"]     )

          # s2
          # test automatic padding
          self.assertEqual(out_sa["input_ids"].shape[-1],3_3     )
          # long slice doesn't have padding
          self.assertFalse(pad_token_id in out_sa["input_ids"][0]     )
          self.assertFalse(0 in out_sa["attention_mask"][0]     )
          # short slice does have padding
          self.assertTrue(pad_token_id in out_sa["input_ids"][1]     )
          self.assertTrue(0 in out_sa["attention_mask"][1]     )

          # p
          # test single pair max_length padding
          self.assertEqual(out_p["input_ids"].shape[-1],6_0     )
          self.assertTrue(pad_token_id in out_p["input_ids"]     )
          self.assertTrue(0 in out_p["attention_mask"]     )

          # p2
          # test automatic padding pair
          self.assertEqual(out_pa["input_ids"].shape[-1],5_2     )
          # long slice pair doesn't have padding
          self.assertFalse(pad_token_id in out_pa["input_ids"][0]     )
          self.assertFalse(0 in out_pa["attention_mask"][0]     )
          # short slice pair does have padding
          self.assertTrue(pad_token_id in out_pa["input_ids"][1]     )
          self.assertTrue(0 in out_pa["attention_mask"][1]     )



    def   lowerCamelCase_  (	self      :       Any     ):
          _lowerCamelCase				:   str								=   "$$$"
          _lowerCamelCase				:   Dict								=   GPTaTokenizer.from_pretrained(self.tmpdirname,bos_token=lowercase_,add_bos_token=lowercase_     )

          _lowerCamelCase				:   Tuple								=   "This is a simple input"
          _lowerCamelCase				:   Optional[int]								=   ["This is a simple input 1", "This is a simple input 2"]

          _lowerCamelCase				:   Tuple								=   tokenizer.bos_token_id

          _lowerCamelCase				:   Optional[int]								=   tokenizer(lowercase_     )
          _lowerCamelCase				:   Optional[int]								=   tokenizer(lowercase_     )

          self.assertEqual(out_s.input_ids[0],lowercase_     )
          self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids     )     )

          _lowerCamelCase				:   int								=   tokenizer.decode(out_s.input_ids     )
          _lowerCamelCase				:   Optional[int]								=   tokenizer.batch_decode(out_sa.input_ids     )

          self.assertEqual(decode_s.split()[0],lowercase_     )
          self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa     )     )



    def   lowerCamelCase_  (	self      :       Optional[int]     ):
          pass



    def   lowerCamelCase_  (	self      :       Optional[Any]     ):
          # TODO: change to self.get_tokenizers() when the fast version is implemented
          _lowerCamelCase				:   Dict								=   [self.get_tokenizer(do_lower_case=lowercase_,add_bos_token=lowercase_     )]
          for tokenizer in tokenizers:
                with self.subTest(f'{tokenizer.__class__.__name__}'     ):
                      _lowerCamelCase				:   Dict								=   "Encode this."
                      _lowerCamelCase				:   Dict								=   "This one too please."
                      _lowerCamelCase				:   str								=   tokenizer.encode(lowercase_,add_special_tokens=lowercase_     )
                      encoded_sequence += tokenizer.encode(lowercase_,add_special_tokens=lowercase_     )
                      _lowerCamelCase				:   Union[str, Any]								=   tokenizer.encode_plus(
                          lowercase_,lowercase_,add_special_tokens=lowercase_,return_special_tokens_mask=lowercase_,)
                      _lowerCamelCase				:   List[str]								=   encoded_sequence_dict["input_ids"]
                      _lowerCamelCase				:   Tuple								=   encoded_sequence_dict["special_tokens_mask"]
                      self.assertEqual(len(lowercase_     ),len(lowercase_     )     )

                      _lowerCamelCase				:   Any								=   [
                          (x if not special_tokens_mask[i] else None) for i, x in enumerate(lowercase_     )
                      ]
                      _lowerCamelCase				:   Tuple								=   [x for x in filtered_sequence if x is not None]
                      self.assertEqual(lowercase_,lowercase_     )


@require_tokenizers
class  UpperCAmelCase__						(       unittest.TestCase ):



    def   lowerCamelCase_  (	self      :       Optional[Any]     ):
          # More context:
          # https://huggingface.co/wjmcat/opt-350m-paddle/discussions/1
          # https://huggingface.slack.com/archives/C01N44FJDHT/p1653511495183519
          # https://github.com/huggingface/transformers/pull/17088#discussion_r871246439

          _lowerCamelCase				:   Union[str, Any]								=   AutoTokenizer.from_pretrained("facebook/opt-350m",from_slow=lowercase_     )
          _lowerCamelCase				:   str								=   "A photo of a cat"

          _lowerCamelCase				:   int								=   tokenizer.encode(
              lowercase_,)
          self.assertEqual(lowercase_,[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]     )
          tokenizer.save_pretrained("test_opt"     )

          _lowerCamelCase				:   List[str]								=   AutoTokenizer.from_pretrained("./test_opt"     )
          _lowerCamelCase				:   int								=   tokenizer.encode(
              lowercase_,)
          self.assertEqual(lowercase_,[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]     )



    def   lowerCamelCase_  (	self      :       str     ):
          _lowerCamelCase				:   List[str]								=   AutoTokenizer.from_pretrained("facebook/opt-350m",use_slow=lowercase_     )
          _lowerCamelCase				:   List[str]								=   "A photo of a cat"

          _lowerCamelCase				:   Dict								=   tokenizer.encode(
              lowercase_,)
          # Same as above
          self.assertEqual(lowercase_,[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]     )



    @unittest.skip("This test is failing because of a bug in the fast tokenizer"     )
    def   lowerCamelCase_  (	self      :       Any     ):
          _lowerCamelCase				:   List[str]								=   AutoTokenizer.from_pretrained("facebook/opt-350m",from_slow=lowercase_     )

          _lowerCamelCase				:   int								=   "bos"
          _lowerCamelCase				:   int								=   tokenizer.get_vocab()["bos"]

          _lowerCamelCase				:   List[Any]								=   "A photo of a cat"
          _lowerCamelCase				:   Optional[int]								=   tokenizer.encode(
              lowercase_,)
          # We changed the bos token
          self.assertEqual(lowercase_,[3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]     )
          tokenizer.save_pretrained("./tok"     )
          _lowerCamelCase				:   Optional[int]								=   AutoTokenizer.from_pretrained("./tok"     )
          self.assertTrue(tokenizer.is_fast     )
          _lowerCamelCase				:   Any								=   tokenizer.encode(
              lowercase_,)
          self.assertEqual(lowercase_,[3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]     )

'''simple docstring'''






import random
from typing import Any







def 		A_       (	_lowerCAmelCase   :    list							):



      """simple docstring"""




      for _ in range(len(_lowerCAmelCase							)							):
            _lowerCamelCase				:   Any								=   random.randint(0				,	len(_lowerCAmelCase							) - 1							)
            _lowerCamelCase				:   List[str]								=   random.randint(0				,	len(_lowerCAmelCase							) - 1							)
            _lowerCamelCase						,		_lowerCamelCase				:   Union[str, Any]								=   data[b], data[a]
      return data


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