
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase				=			get_tests_dir("""fixtures/test_sentencepiece.model""")


if is_torch_available():
   from transformers.models.mbart.modeling_mbart import shift_tokens_right

__lowerCamelCase				=			25_00_04
__lowerCamelCase				=			25_00_20






@require_sentencepiece
@require_tokenizers
class     UpperCAmelCase						(		A_			,unittest.TestCase					):
   A__   :						Dict			=	MBartTokenizer
   A__   :						List[Any]			=	MBartTokenizerFast
   A__   :						Any			=	True
   A__   :						Dict			=	True



   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      Any:


          '''simple docstring'''


          super().setUp()

          # We have a SentencePiece fixture for testing
          snake_case			:  List[Any]     							= MBartTokenizer(snake_case__       ,		keep_accents=snake_case__					)
          tokenizer.save_pretrained(self.tmpdirname					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      Dict:


          '''simple docstring'''


          snake_case			:  Union[str, Any]     							= MBartTokenizer(snake_case__       ,		keep_accents=snake_case__					)

          snake_case			:  Optional[Any]     							= tokenizer.tokenize("This is a test"					)
          self.assertListEqual(snake_case__       ,		["▁This", "▁is", "▁a", "▁t", "est"]					)

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(snake_case__					)       ,		[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]       ,		)

          snake_case			:  Optional[int]     							= tokenizer.tokenize("I was born in 92000, and this is falsé."					)
          self.assertListEqual(
              snake_case__       ,		[
                  SPIECE_UNDERLINE + "I",
                  SPIECE_UNDERLINE + "was",
                  SPIECE_UNDERLINE + "b",
                  "or",
                  "n",
                  SPIECE_UNDERLINE + "in",
                  SPIECE_UNDERLINE + "",
                  "9",
                  "2",
                  "0",
                  "0",
                  "0",
                  ",",
                  SPIECE_UNDERLINE + "and",
                  SPIECE_UNDERLINE + "this",
                  SPIECE_UNDERLINE + "is",
                  SPIECE_UNDERLINE + "f",
                  "al",
                  "s",
                  "é",
                  ".",
              ]       ,		)
          snake_case			:  Any     							= tokenizer.convert_tokens_to_ids(snake_case__					)
          self.assertListEqual(
              snake_case__       ,		[
                  value + tokenizer.fairseq_offset
                  for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                  #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
              ]       ,		)

          snake_case			:  Any     							= tokenizer.convert_ids_to_tokens(snake_case__					)
          self.assertListEqual(
              snake_case__       ,		[
                  SPIECE_UNDERLINE + "I",
                  SPIECE_UNDERLINE + "was",
                  SPIECE_UNDERLINE + "b",
                  "or",
                  "n",
                  SPIECE_UNDERLINE + "in",
                  SPIECE_UNDERLINE + "",
                  "<unk>",
                  "2",
                  "0",
                  "0",
                  "0",
                  ",",
                  SPIECE_UNDERLINE + "and",
                  SPIECE_UNDERLINE + "this",
                  SPIECE_UNDERLINE + "is",
                  SPIECE_UNDERLINE + "f",
                  "al",
                  "s",
                  "<unk>",
                  ".",
              ]       ,		)



   def 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      Tuple:


          '''simple docstring'''


          if not self.test_slow_tokenizer:
                 # as we don't have a slow version, we can't compare the outputs between slow and fast versions
                 return

          snake_case			:  str     							= (self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart", {})
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
                        snake_case			:  Any     							= self.rust_tokenizer_class.from_pretrained(snake_case__       ,		**snake_case__					)
                        snake_case			:  Optional[Any]     							= self.tokenizer_class.from_pretrained(snake_case__       ,		**snake_case__					)

                        snake_case			:  Dict     							= tempfile.mkdtemp()

                        snake_case			:  List[Any]     							= tokenizer_r.save_pretrained(snake_case__					)
                        snake_case			:  List[str]     							= tokenizer_p.save_pretrained(snake_case__					)

                        # Checks it save with the same files + the tokenizer.json file for the fast one
                        self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files					)					)
                        snake_case			:  Any     							= tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f					)
                        self.assertSequenceEqual(snake_case__       ,		snake_case__					)

                        # Checks everything loads correctly in the same way
                        snake_case			:  Tuple     							= tokenizer_r.from_pretrained(snake_case__					)
                        snake_case			:  Optional[int]     							= tokenizer_p.from_pretrained(snake_case__					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                               self.assertTrue(hasattr(snake_case__       ,		snake_case__					)					)
                               # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                               # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                        shutil.rmtree(snake_case__					)

                        # Save tokenizer rust, legacy_format=True
                        snake_case			:  int     							= tempfile.mkdtemp()

                        snake_case			:  str     							= tokenizer_r.save_pretrained(snake_case__       ,		legacy_format=snake_case__					)
                        snake_case			:  int     							= tokenizer_p.save_pretrained(snake_case__					)

                        # Checks it save with the same files
                        self.assertSequenceEqual(snake_case__       ,		snake_case__					)

                        # Checks everything loads correctly in the same way
                        snake_case			:  List[Any]     							= tokenizer_r.from_pretrained(snake_case__					)
                        snake_case			:  Union[str, Any]     							= tokenizer_p.from_pretrained(snake_case__					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                               self.assertTrue(hasattr(snake_case__       ,		snake_case__					)					)

                        shutil.rmtree(snake_case__					)

                        # Save tokenizer rust, legacy_format=False
                        snake_case			:  int     							= tempfile.mkdtemp()

                        snake_case			:  Optional[int]     							= tokenizer_r.save_pretrained(snake_case__       ,		legacy_format=snake_case__					)
                        snake_case			:  Dict     							= tokenizer_p.save_pretrained(snake_case__					)

                        # Checks it saved the tokenizer.json file
                        self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files					)					)

                        # Checks everything loads correctly in the same way
                        snake_case			:  List[str]     							= tokenizer_r.from_pretrained(snake_case__					)
                        snake_case			:  Optional[Any]     							= tokenizer_p.from_pretrained(snake_case__					)

                        # Check special tokens are set accordingly on Rust and Python
                        for key in tokenizer_pp.special_tokens_map:
                               self.assertTrue(hasattr(snake_case__       ,		snake_case__					)					)

                        shutil.rmtree(snake_case__					)






@require_torch
@require_sentencepiece
@require_tokenizers
class     UpperCAmelCase						(		unittest.TestCase					):
   A__   :						Tuple			=	"facebook/mbart-large-en-ro"
   A__   :						Tuple			=	[
       " UN Chief Says There Is No Military Solution in Syria",
       " Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.",
   ]
   A__   :						int			=	[
       "Şeful ONU declară că nu există o soluţie militară în Siria",
       "Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"
       " pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"
       " face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.",
   ]
   A__   :						Any			=	[82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2, EN_CODE]



   @classmethod
   def 							_SCREAMING_SNAKE_CASE  (cls						:   int					)						->      Union[str, Any]:


          '''simple docstring'''


          snake_case			:  MBartTokenizer     							= MBartTokenizer.from_pretrained(
              cls.checkpoint_name       ,		src_lang="en_XX"       ,		tgt_lang="ro_RO"					)
          snake_case			:  Optional[int]     							= 1
          return cls



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


          '''simple docstring'''


          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]       ,		25_00_01					)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]       ,		25_00_04					)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]       ,		25_00_20					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[int]					)						->      Dict:


          '''simple docstring'''


          snake_case			:  List[Any]     							= self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
          self.assertListEqual(self.expected_src_tokens       ,		snake_case__					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   List[Any]					)						->      Optional[Any]:


          '''simple docstring'''


          self.assertIn(snake_case__       ,		self.tokenizer.all_special_ids					)
          snake_case			:  List[Any]     							= [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
          snake_case			:  Optional[Any]     							= self.tokenizer.decode(snake_case__       ,		skip_special_tokens=snake_case__					)
          snake_case			:  Union[str, Any]     							= self.tokenizer.decode(generated_ids[1:]       ,		skip_special_tokens=snake_case__					)
          self.assertEqual(snake_case__       ,		snake_case__					)
          self.assertNotIn(self.tokenizer.eos_token       ,		snake_case__					)



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


          '''simple docstring'''


          snake_case			:  Union[str, Any]     							= ["this is gunna be a long sentence " * 20]
          assert isinstance(src_text[0]       ,		snake_case__					)
          snake_case			:  Dict     							= 10
          snake_case			:  Union[str, Any]     							= self.tokenizer(snake_case__       ,		max_length=snake_case__       ,		truncation=snake_case__					).input_ids[0]
          self.assertEqual(ids[-2]       ,		2					)
          self.assertEqual(ids[-1]       ,		snake_case__					)
          self.assertEqual(len(snake_case__					)       ,		snake_case__					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      Any:


          '''simple docstring'''


          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]					)       ,		[25_00_26, 25_00_01]					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      Dict:


          '''simple docstring'''


          snake_case			:  Tuple     							= tempfile.mkdtemp()
          snake_case			:  List[Any]     							= self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(snake_case__					)
          snake_case			:  Union[str, Any]     							= MBartTokenizer.from_pretrained(snake_case__					)
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,		snake_case__					)



   @require_torch
   def 							_SCREAMING_SNAKE_CASE  (self						:   List[Any]					)						->      Union[str, Any]:


          '''simple docstring'''


          snake_case			:  str     							= self.tokenizer(self.src_text       ,		text_target=self.tgt_text       ,		padding=snake_case__       ,		return_tensors="pt"					)
          snake_case			:  List[Any]     							= shift_tokens_right(batch["labels"]       ,		self.tokenizer.pad_token_id					)

          # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
          assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
          assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
          assert batch.decoder_input_ids[1][-1] == 2
          assert batch.labels[1][-2:].tolist() == [2, RO_CODE]



   @require_torch
   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      List[str]:


          '''simple docstring'''


          snake_case			:  str     							= self.tokenizer(
              self.src_text       ,		text_target=self.tgt_text       ,		padding=snake_case__       ,		truncation=snake_case__       ,		max_length=len(self.expected_src_tokens					)       ,		return_tensors="pt"       ,		)

          snake_case			:  Tuple     							= shift_tokens_right(batch["labels"]       ,		self.tokenizer.pad_token_id					)

          self.assertIsInstance(snake_case__       ,		snake_case__					)

          self.assertEqual((2, 14)       ,		batch.input_ids.shape					)
          self.assertEqual((2, 14)       ,		batch.attention_mask.shape					)
          snake_case			:  List[Any]     							= batch.input_ids.tolist()[0]
          self.assertListEqual(self.expected_src_tokens       ,		snake_case__					)
          self.assertEqual(2       ,		batch.decoder_input_ids[0, -1]					)  # EOS
          # Test that special tokens are reset
          self.assertEqual(self.tokenizer.prefix_tokens       ,		[]					)
          self.assertEqual(self.tokenizer.suffix_tokens       ,		[self.tokenizer.eos_token_id, EN_CODE]					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      Dict:


          '''simple docstring'''


          snake_case			:  int     							= self.tokenizer(self.src_text       ,		padding=snake_case__       ,		truncation=snake_case__       ,		max_length=3       ,		return_tensors="pt"					)
          snake_case			:  str     							= self.tokenizer(
              text_target=self.tgt_text       ,		padding=snake_case__       ,		truncation=snake_case__       ,		max_length=10       ,		return_tensors="pt"					)
          snake_case			:  Tuple     							= targets["input_ids"]
          snake_case			:  List[str]     							= shift_tokens_right(snake_case__       ,		self.tokenizer.pad_token_id					)

          self.assertEqual(batch.input_ids.shape[1]       ,		3					)
          self.assertEqual(batch.decoder_input_ids.shape[1]       ,		10					)



   @require_torch
   def 							_SCREAMING_SNAKE_CASE  (self						:   List[str]					)						->      str:


          '''simple docstring'''


          snake_case			:  int     							= self.tokenizer._build_translation_inputs(
              "A test"       ,		return_tensors="pt"       ,		src_lang="en_XX"       ,		tgt_lang="ar_AR"					)

          self.assertEqual(
              nested_simplify(snake_case__					)       ,		{
                  # A, test, EOS, en_XX
                  "input_ids": [[62, 30_34, 2, 25_00_04]],
                  "attention_mask": [[1, 1, 1, 1]],
                  # ar_AR
                  "forced_bos_token_id": 25_00_01,
              }       ,		)







__lowerCamelCase				=			{
    0: """0""",
    1: """1""",
    2: """2""",
    3: """3""",
    4: """4""",
    5: """5""",
    6: """6""",
    7: """7""",
    8: """8""",
    9: """9""",
    10: """a""",
    11: """b""",
    12: """c""",
    13: """d""",
    14: """e""",
    15: """f""",
}


def      UpperCamelCase   (       __lowerCamelCase	:					float       ):
       assert type(__lowerCamelCase       ) in (int, float) and decimal == int(__lowerCamelCase       )
       snake_case			:  str     							= int(__lowerCamelCase       )
       snake_case			:  str     							= ""
       snake_case			:  str     							= False
       if decimal < 0:
              snake_case			:  Optional[Any]     							= True
              decimal *= -1
       while decimal > 0:
              snake_case							,   snake_case			:  Union[str, Any]     							= divmod(__lowerCamelCase							,   16       )
              snake_case			:  Tuple     							= values[remainder] + hexadecimal
       snake_case			:  Tuple     							= "0x" + hexadecimal
       if negative:
              snake_case			:  Any     							= "-" + hexadecimal
       return hexadecimal


if __name__ == "__main__":
   import doctest

   doctest.testmod()





