






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			(a_							,		unittest.TestCase			):
      snake_case_  =							GPTaTokenizer
      snake_case_  =							GPTaTokenizerFast
      snake_case_  =							True
      snake_case_  =							{"""add_prefix_space""": True}
      snake_case_  =							False


      def  __UpperCAmelCase		(	self	)->	Optional[int]:
           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(__UpperCamelCase					,						range(len(__UpperCamelCase	)	)	)	)
           __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(__UpperCamelCase	) + "\n"	)
           with open(self.merges_file					,						"w"					,						encoding="utf-8"	) as fp:
                fp.write("\n".join(__UpperCamelCase	)	)


      def  __UpperCAmelCase		(	self					,						**__UpperCamelCase	)->	str:
           kwargs.update(self.special_tokens_map	)
           return GPTaTokenizer.from_pretrained(self.tmpdirname					,						**__UpperCamelCase	)


      def  __UpperCAmelCase		(	self					,						**__UpperCamelCase	)->	Tuple:
           kwargs.update(self.special_tokens_map	)
           return GPTaTokenizerFast.from_pretrained(self.tmpdirname					,						**__UpperCamelCase	)


      def  __UpperCAmelCase		(	self					,						__UpperCamelCase	)->	int:
           __lowerCAmelCase								=					"lower newer"
           __lowerCAmelCase								=					"lower newer"
           return input_text, output_text


      def  __UpperCAmelCase		(	self	)->	Union[str, Any]:
           __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(__UpperCamelCase					,						add_prefix_space=__UpperCamelCase	)
           self.assertListEqual(__UpperCamelCase					,						__UpperCamelCase	)

           __lowerCAmelCase								=					tokens + [tokenizer.unk_token]
           __lowerCAmelCase								=					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase	)					,						__UpperCamelCase	)


      def  __UpperCAmelCase		(	self	)->	Optional[Any]:
           if not self.test_rust_tokenizer:
                return

           __lowerCAmelCase								=					self.get_tokenizer()
           __lowerCAmelCase								=					self.get_rust_tokenizer(add_prefix_space=__UpperCamelCase	)

           __lowerCAmelCase								=					"lower newer"

           # Testing tokenization
           __lowerCAmelCase								=					tokenizer.tokenize(__UpperCamelCase					,						add_prefix_space=__UpperCamelCase	)
           __lowerCAmelCase								=					rust_tokenizer.tokenize(__UpperCamelCase	)
           self.assertListEqual(__UpperCamelCase					,						__UpperCamelCase	)

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

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

           # Testing the unknown token
           __lowerCAmelCase								=					tokens + [rust_tokenizer.unk_token]
           __lowerCAmelCase								=					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
           self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(__UpperCamelCase	)					,						__UpperCamelCase	)


      def  __UpperCAmelCase		(	self					,						*__UpperCamelCase					,						**__UpperCamelCase	)->	Optional[int]:
           # 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  __UpperCAmelCase		(	self					,						__UpperCamelCase=1_5	)->	List[Any]:
           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(__UpperCamelCase					,						**__UpperCamelCase	)

                     # 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(__UpperCamelCase					,						tokenizer_r.encode					,						__UpperCamelCase					,						max_length=__UpperCamelCase					,						padding="max_length"	)

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

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

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

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

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


      def  __UpperCAmelCase		(	self	)->	Optional[Any]:
           __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(__UpperCamelCase					,						padding="max_length"					,						max_length=3_0					,						return_tensors="np"	)
           __lowerCAmelCase								=					tokenizer(__UpperCamelCase					,						padding=__UpperCamelCase					,						truncate=__UpperCamelCase					,						return_tensors="np"	)
           __lowerCAmelCase								=					tokenizer(*__UpperCamelCase					,						padding="max_length"					,						max_length=6_0					,						return_tensors="np"	)
           __lowerCAmelCase								=					tokenizer(__UpperCamelCase					,						padding=__UpperCamelCase					,						truncate=__UpperCamelCase					,						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  __UpperCAmelCase		(	self	)->	Optional[Any]:
           __lowerCAmelCase								=					"$$$"
           __lowerCAmelCase								=					GPTaTokenizer.from_pretrained(self.tmpdirname					,						bos_token=__UpperCamelCase					,						add_bos_token=__UpperCamelCase	)

           __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(__UpperCamelCase	)
           __lowerCAmelCase								=					tokenizer(__UpperCamelCase	)

           self.assertEqual(out_s.input_ids[0]					,						__UpperCamelCase	)
           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]					,						__UpperCamelCase	)
           self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa	)	)


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


      def  __UpperCAmelCase		(	self	)->	List[Any]:
           # TODO: change to self.get_tokenizers() when the fast version is implemented
           __lowerCAmelCase								=					[self.get_tokenizer(do_lower_case=__UpperCamelCase					,						add_bos_token=__UpperCamelCase	)]
           for tokenizer in tokenizers:
                with self.subTest(F"""{tokenizer.__class__.__name__}"""	):
                     __lowerCAmelCase								=					"Encode this."
                     __lowerCAmelCase								=					"This one too please."
                     __lowerCAmelCase								=					tokenizer.encode(__UpperCamelCase					,						add_special_tokens=__UpperCamelCase	)
                     encoded_sequence += tokenizer.encode(__UpperCamelCase					,						add_special_tokens=__UpperCamelCase	)
                     __lowerCAmelCase								=					tokenizer.encode_plus(
                         __UpperCamelCase					,						__UpperCamelCase					,						add_special_tokens=__UpperCamelCase					,						return_special_tokens_mask=__UpperCamelCase					,						)
                     __lowerCAmelCase								=					encoded_sequence_dict["input_ids"]
                     __lowerCAmelCase								=					encoded_sequence_dict["special_tokens_mask"]
                     self.assertEqual(len(__UpperCamelCase	)					,						len(__UpperCamelCase	)	)

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



@require_tokenizers
class 							_UpperCamelCase			(unittest.TestCase			):


      def  __UpperCAmelCase		(	self	)->	List[str]:
           # 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								=					AutoTokenizer.from_pretrained("facebook/opt-350m"					,						from_slow=__UpperCamelCase	)
           __lowerCAmelCase								=					"A photo of a cat"

           __lowerCAmelCase								=					tokenizer.encode(
               __UpperCamelCase					,						)
           self.assertEqual(__UpperCamelCase					,						[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]	)
           tokenizer.save_pretrained("test_opt"	)

           __lowerCAmelCase								=					AutoTokenizer.from_pretrained("./test_opt"	)
           __lowerCAmelCase								=					tokenizer.encode(
               __UpperCamelCase					,						)
           self.assertEqual(__UpperCamelCase					,						[2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]	)


      def  __UpperCAmelCase		(	self	)->	Dict:
           __lowerCAmelCase								=					AutoTokenizer.from_pretrained("facebook/opt-350m"					,						use_slow=__UpperCamelCase	)
           __lowerCAmelCase								=					"A photo of a cat"

           __lowerCAmelCase								=					tokenizer.encode(
               __UpperCamelCase					,						)
           # Same as above
           self.assertEqual(__UpperCamelCase					,						[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  __UpperCAmelCase		(	self	)->	Tuple:
           __lowerCAmelCase								=					AutoTokenizer.from_pretrained("facebook/opt-350m"					,						from_slow=__UpperCamelCase	)

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

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














def       __lowerCAmelCase      (						__snake_case					, __snake_case       ):
     if not isinstance(__snake_case					, __snake_case       ):
          raise ValueError("iterations must be defined as integers"       )
     if not isinstance(__snake_case					, __snake_case       ) or not number >= 1:
          raise ValueError(
              "starting number must be\n                         and integer and be more than 0"       )
     if not iterations >= 1:
          raise ValueError("Iterations must be done more than 0 times to play FizzBuzz"       )

     __lowerCAmelCase								=					""
     while number <= iterations:
          if number % 3 == 0:
               out += "Fizz"
          if number % 5 == 0:
               out += "Buzz"
          if 0 not in (number % 3, number % 5):
               out += str(__snake_case       )

          # print(out)
          number += 1
          out += " "
     return out


if __name__ == "__main__":
 import doctest

 doctest.testmod()






