



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  lowerCamelCase__	(    UpperCAmelCase_							,     unittest.TestCase):
     """simple docstring"""



     _A      =      GPTaTokenizer
     _A      =      GPTaTokenizerFast
     _A      =      True
     _A      =      {'add_prefix_space': True}
     _A      =      False







     def     _a   (self     ):






           '''simple docstring'''



           super().setUp()

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

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







     def     _a   (self					,      **__a     ):






           '''simple docstring'''



           kwargs.update(self.special_tokens_map     )
           return GPTaTokenizer.from_pretrained(self.tmpdirname					,      **__a     )







     def     _a   (self					,      **__a     ):






           '''simple docstring'''



           kwargs.update(self.special_tokens_map     )
           return GPTaTokenizerFast.from_pretrained(self.tmpdirname					,      **__a     )







     def     _a   (self					,      __a     ):






           '''simple docstring'''



           lowerCamelCase             =		"lower newer"
           lowerCamelCase             =		"lower newer"
           return input_text, output_text







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		GPTaTokenizer(self.vocab_file					,      self.merges_file					,      **self.special_tokens_map     )
           lowerCamelCase             =		"lower newer"
           lowerCamelCase             =		["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
           lowerCamelCase             =		tokenizer.tokenize(__a					,      add_prefix_space=__a     )
           self.assertListEqual(__a					,      __a     )

           lowerCamelCase             =		tokens + [tokenizer.unk_token]
           lowerCamelCase             =		[14, 15, 10, 9, 3, 2, 15, 19]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__a     )					,      __a     )







     def     _a   (self     ):






           '''simple docstring'''



           if not self.test_rust_tokenizer:
                 return

           lowerCamelCase             =		self.get_tokenizer()
           lowerCamelCase             =		self.get_rust_tokenizer(add_prefix_space=__a     )

           lowerCamelCase             =		"lower newer"

           # Testing tokenization
           lowerCamelCase             =		tokenizer.tokenize(__a					,      add_prefix_space=__a     )
           lowerCamelCase             =		rust_tokenizer.tokenize(__a     )
           self.assertListEqual(__a					,      __a     )

           # Testing conversion to ids without special tokens
           lowerCamelCase             =		tokenizer.encode(__a					,      add_special_tokens=__a					,      add_prefix_space=__a     )
           lowerCamelCase             =		rust_tokenizer.encode(__a					,      add_special_tokens=__a     )
           self.assertListEqual(__a					,      __a     )

           # Testing conversion to ids with special tokens
           lowerCamelCase             =		self.get_rust_tokenizer(add_prefix_space=__a     )
           lowerCamelCase             =		tokenizer.encode(__a					,      add_prefix_space=__a     )
           lowerCamelCase             =		rust_tokenizer.encode(__a     )
           self.assertListEqual(__a					,      __a     )

           # Testing the unknown token
           lowerCamelCase             =		tokens + [rust_tokenizer.unk_token]
           lowerCamelCase             =		[14, 15, 10, 9, 3, 2, 15, 19]
           self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(__a     )					,      __a     )







     def     _a   (self					,      *__a					,      **__a     ):






           '''simple docstring'''



           pass







     def     _a   (self					,      __a=15     ):






           '''simple docstring'''



           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
                       lowerCamelCase             =		self.rust_tokenizer_class.from_pretrained(__a					,      **__a     )

                       # Simple input
                       lowerCamelCase             =		"This is a simple input"
                       lowerCamelCase             =		["This is a simple input 1", "This is a simple input 2"]
                       lowerCamelCase             =		("This is a simple input", "This is a pair")
                       lowerCamelCase             =		[
                           ("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(__a					,      tokenizer_r.encode					,      __a					,      max_length=__a					,      padding="max_length"     )

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

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

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

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

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







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		GPTaTokenizer.from_pretrained(self.tmpdirname					,      pad_token="<pad>"     )

           # Simple input
           lowerCamelCase             =		"This is a simple input"
           lowerCamelCase             =		["This is a simple input looooooooong", "This is a simple input"]
           lowerCamelCase             =		("This is a simple input", "This is a pair")
           lowerCamelCase             =		[
               ("This is a simple input loooooong", "This is a simple input"),
               ("This is a simple pair loooooong", "This is a simple pair"),
           ]

           lowerCamelCase             =		tokenizer.pad_token_id

           lowerCamelCase             =		tokenizer(__a					,      padding="max_length"					,      max_length=30					,      return_tensors="np"     )
           lowerCamelCase             =		tokenizer(__a					,      padding=__a					,      truncate=__a					,      return_tensors="np"     )
           lowerCamelCase             =		tokenizer(*__a					,      padding="max_length"					,      max_length=60					,      return_tensors="np"     )
           lowerCamelCase             =		tokenizer(__a					,      padding=__a					,      truncate=__a					,      return_tensors="np"     )

           # s
           # test single string max_length padding
           self.assertEqual(out_s["input_ids"].shape[-1]					,      30     )
           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]					,      33     )
           # 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]					,      60     )
           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]					,      52     )
           # 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     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		"$$$"
           lowerCamelCase             =		GPTaTokenizer.from_pretrained(self.tmpdirname					,      bos_token=__a					,      add_bos_token=__a     )

           lowerCamelCase             =		"This is a simple input"
           lowerCamelCase             =		["This is a simple input 1", "This is a simple input 2"]

           lowerCamelCase             =		tokenizer.bos_token_id

           lowerCamelCase             =		tokenizer(__a     )
           lowerCamelCase             =		tokenizer(__a     )

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

           lowerCamelCase             =		tokenizer.decode(out_s.input_ids     )
           lowerCamelCase             =		tokenizer.batch_decode(out_sa.input_ids     )

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







     def     _a   (self     ):






           '''simple docstring'''



           pass







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		[self.get_tokenizer(do_lower_case=__a					,      add_bos_token=__a     )]
           for tokenizer in tokenizers:
                 with self.subTest(F"""{tokenizer.__class__.__name__}"""     ):
                       lowerCamelCase             =		"Encode this."
                       lowerCamelCase             =		"This one too please."
                       lowerCamelCase             =		tokenizer.encode(__a					,      add_special_tokens=__a     )
                       encoded_sequence += tokenizer.encode(__a					,      add_special_tokens=__a     )
                       lowerCamelCase             =		tokenizer.encode_plus(
                           __a					,      __a					,      add_special_tokens=__a					,      return_special_tokens_mask=__a					,      )
                       lowerCamelCase             =		encoded_sequence_dict["input_ids"]
                       lowerCamelCase             =		encoded_sequence_dict["special_tokens_mask"]
                       self.assertEqual(len(__a     )					,      len(__a     )     )

                       lowerCamelCase             =		[
                           (x if not special_tokens_mask[i] else None) for i, x in enumerate(__a     )
                       ]
                       lowerCamelCase             =		[x for x in filtered_sequence if x is not None]
                       self.assertEqual(__a					,      __a     )





@require_tokenizers
class  lowerCamelCase__	(    unittest.TestCase):
     """simple docstring"""



     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		AutoTokenizer.from_pretrained("facebook/opt-350m"					,      from_slow=__a     )
           lowerCamelCase             =		"A photo of a cat"

           lowerCamelCase             =		tokenizer.encode(
               __a					,      )
           self.assertEqual(__a					,      [2, 2_50, 13_45, 9, 10, 47_58]     )
           tokenizer.save_pretrained("test_opt"     )

           lowerCamelCase             =		AutoTokenizer.from_pretrained("./test_opt"     )
           lowerCamelCase             =		tokenizer.encode(
               __a					,      )
           self.assertEqual(__a					,      [2, 2_50, 13_45, 9, 10, 47_58]     )







     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		AutoTokenizer.from_pretrained("facebook/opt-350m"					,      use_slow=__a     )
           lowerCamelCase             =		"A photo of a cat"

           lowerCamelCase             =		tokenizer.encode(
               __a					,      )
           # Same as above
           self.assertEqual(__a					,      [2, 2_50, 13_45, 9, 10, 47_58]     )







     @unittest.skip("This test is failing because of a bug in the fast tokenizer"     )
     def     _a   (self     ):






           '''simple docstring'''



           lowerCamelCase             =		AutoTokenizer.from_pretrained("facebook/opt-350m"					,      from_slow=__a     )

           lowerCamelCase             =		"bos"
           lowerCamelCase             =		tokenizer.get_vocab()["bos"]

           lowerCamelCase             =		"A photo of a cat"
           lowerCamelCase             =		tokenizer.encode(
               __a					,      )
           # We changed the bos token
           self.assertEqual(__a					,      [3_19_57, 2_50, 13_45, 9, 10, 47_58]     )
           tokenizer.save_pretrained("./tok"     )
           lowerCamelCase             =		AutoTokenizer.from_pretrained("./tok"     )
           self.assertTrue(tokenizer.is_fast     )
           lowerCamelCase             =		tokenizer.encode(
               __a					,      )
           self.assertEqual(__a					,      [3_19_57, 2_50, 13_45, 9, 10, 47_58]     )




from __future__ import annotations

def      __lowercase(						UpperCAmelCase__			):


      """simple docstring"""



      lowerCamelCase             =		2
      lowerCamelCase             =		[]
      while i * i <= n:
            if n % i:
                  i += 1
            else:
                  n //= i
                  factors.append(UpperCAmelCase__			)
      if n > 1:
            factors.append(UpperCAmelCase__			)
      return factors


if __name__ == "__main__":
     import doctest

     doctest.testmod()