


'''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 							__magic_name__	(       lowerCAmelCase    ,		unittest.TestCase ):

     """simple docstring"""






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


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          super().setUp()

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

          __A	:       Optional[int]      =							os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["vocab_file"]		)
          __A	:       Optional[int]      =							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			,     **lowerCamelCase		):


          '''simple docstring'''





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


     def lowerCAmelCase__  (   self			,     **lowerCamelCase		):


          '''simple docstring'''





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


     def lowerCAmelCase__  (   self			,     lowerCamelCase		):


          '''simple docstring'''





          __A	:       Any      =							"lower newer"
          __A	:       List[Any]      =							"lower newer"
          return input_text, output_text


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





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

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


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          if not self.test_rust_tokenizer:
               return

          __A	:       Tuple      =							self.get_tokenizer()
          __A	:       str      =							self.get_rust_tokenizer(add_prefix_space=lowerCamelCase		)

          __A	:       Optional[int]      =							"lower newer"

          # Testing tokenization
          __A	:       Any      =							tokenizer.tokenize(lowerCamelCase			,     add_prefix_space=lowerCamelCase		)
          __A	:       Tuple      =							rust_tokenizer.tokenize(lowerCamelCase		)
          self.assertListEqual(lowerCamelCase			,     lowerCamelCase		)

          # Testing conversion to ids without special tokens
          __A	:       List[str]      =							tokenizer.encode(lowerCamelCase			,     add_special_tokens=lowerCamelCase			,     add_prefix_space=lowerCamelCase		)
          __A	:       str      =							rust_tokenizer.encode(lowerCamelCase			,     add_special_tokens=lowerCamelCase		)
          self.assertListEqual(lowerCamelCase			,     lowerCamelCase		)

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

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


     def lowerCAmelCase__  (   self			,     *lowerCamelCase			,     **lowerCamelCase		):


          '''simple docstring'''





          pass


     def lowerCAmelCase__  (   self			,     lowerCamelCase=15		):


          '''simple docstring'''





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

                    # Simple input
                    __A	:       Dict      =							"This is a simple input"
                    __A	:       Optional[Any]      =							["This is a simple input 1", "This is a simple input 2"]
                    __A	:       List[Any]      =							("This is a simple input", "This is a pair")
                    __A	:       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(lowerCamelCase			,     tokenizer_r.encode			,     lowerCamelCase			,     max_length=lowerCamelCase			,     padding="max_length"		)

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

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

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

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

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


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Dict      =							GPTaTokenizer.from_pretrained(self.tmpdirname			,     pad_token="<pad>"		)

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

          __A	:       List[str]      =							tokenizer.pad_token_id

          __A	:       Any      =							tokenizer(lowerCamelCase			,     padding="max_length"			,     max_length=30			,     return_tensors="np"		)
          __A	:       Tuple      =							tokenizer(lowerCamelCase			,     padding=lowerCamelCase			,     truncate=lowerCamelCase			,     return_tensors="np"		)
          __A	:       Union[str, Any]      =							tokenizer(*lowerCamelCase			,     padding="max_length"			,     max_length=60			,     return_tensors="np"		)
          __A	:       List[Any]      =							tokenizer(lowerCamelCase			,     padding=lowerCamelCase			,     truncate=lowerCamelCase			,     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 lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Dict      =							"$$$"
          __A	:       int      =							GPTaTokenizer.from_pretrained(self.tmpdirname			,     bos_token=lowerCamelCase			,     add_bos_token=lowerCamelCase		)

          __A	:       Dict      =							"This is a simple input"
          __A	:       Dict      =							["This is a simple input 1", "This is a simple input 2"]

          __A	:       str      =							tokenizer.bos_token_id

          __A	:       List[str]      =							tokenizer(lowerCamelCase		)
          __A	:       Any      =							tokenizer(lowerCamelCase		)

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

          __A	:       Union[str, Any]      =							tokenizer.decode(out_s.input_ids		)
          __A	:       Union[str, Any]      =							tokenizer.batch_decode(out_sa.input_ids		)

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


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          pass


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





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

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







@require_tokenizers
class 							__magic_name__	(       unittest.TestCase ):

     """simple docstring"""






     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       List[str]      =							AutoTokenizer.from_pretrained("facebook/opt-350m"			,     from_slow=lowerCamelCase		)
          __A	:       List[str]      =							"A photo of a cat"

          __A	:       Any      =							tokenizer.encode(
              lowerCamelCase			,     )
          self.assertEqual(lowerCamelCase			,     [2, 250, 1345, 9, 10, 4758]		)
          tokenizer.save_pretrained("test_opt"		)

          __A	:       List[str]      =							AutoTokenizer.from_pretrained("./test_opt"		)
          __A	:       Dict      =							tokenizer.encode(
              lowerCamelCase			,     )
          self.assertEqual(lowerCamelCase			,     [2, 250, 1345, 9, 10, 4758]		)


     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          __A	:       Any      =							AutoTokenizer.from_pretrained("facebook/opt-350m"			,     use_slow=lowerCamelCase		)
          __A	:       Optional[Any]      =							"A photo of a cat"

          __A	:       int      =							tokenizer.encode(
              lowerCamelCase			,     )
          # Same as above
          self.assertEqual(lowerCamelCase			,     [2, 250, 1345, 9, 10, 4758]		)


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


          '''simple docstring'''





          __A	:       List[Any]      =							AutoTokenizer.from_pretrained("facebook/opt-350m"			,     from_slow=lowerCamelCase		)

          __A	:       List[str]      =							"bos"
          __A	:       Tuple      =							tokenizer.get_vocab()["bos"]

          __A	:       Tuple      =							"A photo of a cat"
          __A	:       Optional[int]      =							tokenizer.encode(
              lowerCamelCase			,     )
          # We changed the bos token
          self.assertEqual(lowerCamelCase			,     [3_1957, 250, 1345, 9, 10, 4758]		)
          tokenizer.save_pretrained("./tok"		)
          __A	:       str      =							AutoTokenizer.from_pretrained("./tok"		)
          self.assertTrue(tokenizer.is_fast		)
          __A	:       Optional[int]      =							tokenizer.encode(
              lowerCamelCase			,     )
          self.assertEqual(lowerCamelCase			,     [3_1957, 250, 1345, 9, 10, 4758]		)





'''simple docstring'''


def 		_lowercase (SCREAMING_SNAKE_CASE							):




     '''simple docstring'''





     __A	:       List[str]      =							1
     __A	:       Union[str, Any]      =							2
     while i * i <= n:
          __A	:       List[Any]      =							0
          while n % i == 0:
               n //= i
               multiplicity += 1
          n_divisors *= multiplicity + 1
          i += 1
     if n > 1:
          n_divisors *= 2
     return n_divisors


def 		_lowercase ():




     '''simple docstring'''





     __A	:       Optional[Any]      =							1
     __A	:       Dict      =							1

     while True:
          i += 1
          t_num += i

          if count_divisors(SCREAMING_SNAKE_CASE							) > 500:
               break

     return t_num


if __name__ == "__main__":
      print(solution())

