import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    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			: Union[str, Any]							   =		get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
   from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__lowerCamelCase			: Optional[int]							   =		25_6047
__lowerCamelCase			: int							   =		25_6145







@require_sentencepiece
@require_tokenizers
class __snake_case				(						lowerCamelCase_   ,		unittest.TestCase		):
   lowerCAmelCase_														=							NllbTokenizer
   lowerCAmelCase_														=							NllbTokenizerFast
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							{}




   def 	__a						(    self			:				Tuple      ):



     """simple docstring"""






     super().setUp()

     # We have a SentencePiece fixture for testing
     SCREAMING_SNAKE_CASE__										=      NllbTokenizer(_lowercase       ,	keep_accents=_lowercase      )
     tokenizer.save_pretrained(self.tmpdirname      )




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      NllbTokenizer(_lowercase       ,	keep_accents=_lowercase      )

     SCREAMING_SNAKE_CASE__										=      tokenizer.tokenize("""This is a test"""      )
     self.assertListEqual(_lowercase       ,	["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]      )

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

     SCREAMING_SNAKE_CASE__										=      tokenizer.tokenize("""I was born in 92000, and this is falsé."""      )
     self.assertListEqual(
         _lowercase       ,	[
             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""",
             """.""",
         ]       ,	)
     SCREAMING_SNAKE_CASE__										=      tokenizer.convert_tokens_to_ids(_lowercase      )
     self.assertListEqual(
         _lowercase       ,	[
             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]
         ]       ,	)

     SCREAMING_SNAKE_CASE__										=      tokenizer.convert_ids_to_tokens(_lowercase      )
     self.assertListEqual(
         _lowercase       ,	[
             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 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      (self.rust_tokenizer_class, """hf-internal-testing/tiny-random-nllb""", {})
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
         SCREAMING_SNAKE_CASE__										=      self.rust_tokenizer_class.from_pretrained(_lowercase       ,	**_lowercase      )
         SCREAMING_SNAKE_CASE__										=      self.tokenizer_class.from_pretrained(_lowercase       ,	**_lowercase      )

         SCREAMING_SNAKE_CASE__										=      tempfile.mkdtemp()

         SCREAMING_SNAKE_CASE__										=      tokenizer_r.save_pretrained(_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.save_pretrained(_lowercase      )

         # 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      )      )
         SCREAMING_SNAKE_CASE__										=      tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f      )
         self.assertSequenceEqual(_lowercase       ,	_lowercase      )

         # Checks everything loads correctly in the same way
         SCREAMING_SNAKE_CASE__										=      tokenizer_r.from_pretrained(_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.from_pretrained(_lowercase      )

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

         shutil.rmtree(_lowercase      )

         # Save tokenizer rust, legacy_format=True
         SCREAMING_SNAKE_CASE__										=      tempfile.mkdtemp()

         SCREAMING_SNAKE_CASE__										=      tokenizer_r.save_pretrained(_lowercase       ,	legacy_format=_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.save_pretrained(_lowercase      )

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

         # Checks everything loads correctly in the same way
         SCREAMING_SNAKE_CASE__										=      tokenizer_r.from_pretrained(_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.from_pretrained(_lowercase      )

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

         shutil.rmtree(_lowercase      )

         # Save tokenizer rust, legacy_format=False
         SCREAMING_SNAKE_CASE__										=      tempfile.mkdtemp()

         SCREAMING_SNAKE_CASE__										=      tokenizer_r.save_pretrained(_lowercase       ,	legacy_format=_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.save_pretrained(_lowercase      )

         # 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
         SCREAMING_SNAKE_CASE__										=      tokenizer_r.from_pretrained(_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_p.from_pretrained(_lowercase      )

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

         shutil.rmtree(_lowercase      )




   @require_torch
   def 	__a						(    self			:				Tuple      ):



     """simple docstring"""






     if not self.test_seqaseq:
       return

     SCREAMING_SNAKE_CASE__										=      self.get_tokenizers()
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""      ):
         # Longer text that will definitely require truncation.
         SCREAMING_SNAKE_CASE__										=      [
             """ 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.""",
         ]
         SCREAMING_SNAKE_CASE__										=      [
             """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.""",
         ]
         try:
           SCREAMING_SNAKE_CASE__										=      tokenizer.prepare_seqaseq_batch(
               src_texts=_lowercase       ,	tgt_texts=_lowercase       ,	max_length=3       ,	max_target_length=10       ,	return_tensors="""pt"""       ,	src_lang="""eng_Latn"""       ,	tgt_lang="""ron_Latn"""       ,	)
         except NotImplementedError:
           return
         self.assertEqual(batch.input_ids.shape[1]       ,	3      )
         self.assertEqual(batch.labels.shape[1]       ,	10      )
         # max_target_length will default to max_length if not specified
         SCREAMING_SNAKE_CASE__										=      tokenizer.prepare_seqaseq_batch(
             _lowercase       ,	tgt_texts=_lowercase       ,	max_length=3       ,	return_tensors="""pt"""      )
         self.assertEqual(batch.input_ids.shape[1]       ,	3      )
         self.assertEqual(batch.labels.shape[1]       ,	3      )

         SCREAMING_SNAKE_CASE__										=      tokenizer.prepare_seqaseq_batch(
             src_texts=_lowercase       ,	max_length=3       ,	max_target_length=10       ,	return_tensors="""pt"""      )
         self.assertEqual(batch_encoder_only.input_ids.shape[1]       ,	3      )
         self.assertEqual(batch_encoder_only.attention_mask.shape[1]       ,	3      )
         self.assertNotIn("""decoder_input_ids"""       ,	_lowercase      )




   @unittest.skip("""Unfortunately way too slow to build a BPE with SentencePiece."""      )
   def 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     pass




   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
         SCREAMING_SNAKE_CASE__										=      [AddedToken("""<special>"""       ,	lstrip=_lowercase      )]

         SCREAMING_SNAKE_CASE__										=      self.rust_tokenizer_class.from_pretrained(
             _lowercase       ,	additional_special_tokens=_lowercase       ,	**_lowercase      )
         SCREAMING_SNAKE_CASE__										=      tokenizer_r.encode("""Hey this is a <special> token"""      )

         SCREAMING_SNAKE_CASE__										=      tokenizer_r.encode("""<special>"""       ,	add_special_tokens=_lowercase      )[0]

         self.assertTrue(special_token_id in r_output      )

         if self.test_slow_tokenizer:
           SCREAMING_SNAKE_CASE__										=      self.rust_tokenizer_class.from_pretrained(
               _lowercase       ,	additional_special_tokens=_lowercase       ,	**_lowercase       ,	)
           SCREAMING_SNAKE_CASE__										=      self.tokenizer_class.from_pretrained(
               _lowercase       ,	additional_special_tokens=_lowercase       ,	**_lowercase      )

           SCREAMING_SNAKE_CASE__										=      tokenizer_p.encode("""Hey this is a <special> token"""      )

           SCREAMING_SNAKE_CASE__										=      tokenizer_cr.encode("""Hey this is a <special> token"""      )

           self.assertEqual(_lowercase       ,	_lowercase      )
           self.assertEqual(_lowercase       ,	_lowercase      )
           self.assertTrue(special_token_id in p_output      )
           self.assertTrue(special_token_id in cr_output      )







@require_torch
@require_sentencepiece
@require_tokenizers
class __snake_case				(						unittest.TestCase		):
   lowerCAmelCase_														=							"facebook/nllb-200-distilled-600M"
   lowerCAmelCase_														=							[
       " 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.",
   ]
   lowerCAmelCase_														=							[
       "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.",
   ]
   lowerCAmelCase_														=							[
       25_60_47,
       1_62_97,
       13_44_08,
       81_65,
       24_80_66,
       1_47_34,
       9_50,
       11_35,
       10_57_21,
       35_73,
       83,
       2_73_52,
       1_08,
       4_94_86,
       2,
   ]




   @classmethod
   def 	__a						(    cls			:				List[str]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      NllbTokenizer.from_pretrained(
         cls.checkpoint_name       ,	src_lang="""eng_Latn"""       ,	tgt_lang="""ron_Latn"""      )
     SCREAMING_SNAKE_CASE__										=      1
     return cls




   def 	__a						(    self			:				Tuple      ):



     """simple docstring"""






     self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Arab"""]       ,	25_60_01      )
     self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Latn"""]       ,	25_60_02      )
     self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""fra_Latn"""]       ,	25_60_57      )




   def 	__a						(    self			:				List[str]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
     self.assertListEqual(self.expected_src_tokens       ,	_lowercase      )




   def 	__a						(    self			:				List[str]      ):



     """simple docstring"""






     self.assertIn(_lowercase       ,	self.tokenizer.all_special_ids      )
     # fmt: off
     SCREAMING_SNAKE_CASE__										=      [RO_CODE, 42_54, 9_80_68, 11_29_23, 3_90_72, 39_09, 7_13, 10_27_67, 26, 1_73_14, 3_56_42, 1_46_83, 3_31_18, 20_22, 6_69_87, 2, 25_60_47]
     # fmt: on

     SCREAMING_SNAKE_CASE__										=      self.tokenizer.decode(_lowercase       ,	skip_special_tokens=_lowercase      )
     SCREAMING_SNAKE_CASE__										=      self.tokenizer.decode(generated_ids[1:]       ,	skip_special_tokens=_lowercase      )
     self.assertEqual(_lowercase       ,	_lowercase      )
     self.assertNotIn(self.tokenizer.eos_token       ,	_lowercase      )




   def 	__a						(    self			:				Union[str, Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      ["""this is gunna be a long sentence """ * 20]
     assert isinstance(src_text[0]       ,	_lowercase      )
     SCREAMING_SNAKE_CASE__										=      10
     SCREAMING_SNAKE_CASE__										=      self.tokenizer(_lowercase       ,	max_length=_lowercase       ,	truncation=_lowercase      ).input_ids[0]
     self.assertEqual(ids[-1]       ,	2      )
     self.assertEqual(ids[0]       ,	_lowercase      )
     self.assertEqual(len(_lowercase      )       ,	_lowercase      )




   def 	__a						(    self			:				Union[str, Any]      ):



     """simple docstring"""






     self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]      )       ,	[25_62_03, 3]      )




   def 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      tempfile.mkdtemp()
     SCREAMING_SNAKE_CASE__										=      self.tokenizer.fairseq_tokens_to_ids
     self.tokenizer.save_pretrained(_lowercase      )
     SCREAMING_SNAKE_CASE__										=      NllbTokenizer.from_pretrained(_lowercase      )
     self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,	_lowercase      )




   @require_torch
   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.tokenizer(
         self.src_text       ,	text_target=self.tgt_text       ,	padding=_lowercase       ,	truncation=_lowercase       ,	max_length=len(self.expected_src_tokens      )       ,	return_tensors="""pt"""       ,	)
     SCREAMING_SNAKE_CASE__										=      shift_tokens_right(
         batch["""labels"""]       ,	self.tokenizer.pad_token_id       ,	self.tokenizer.lang_code_to_id["""ron_Latn"""]      )

     self.assertIsInstance(_lowercase       ,	_lowercase      )

     self.assertEqual((2, 15)       ,	batch.input_ids.shape      )
     self.assertEqual((2, 15)       ,	batch.attention_mask.shape      )
     SCREAMING_SNAKE_CASE__										=      batch.input_ids.tolist()[0]
     self.assertListEqual(self.expected_src_tokens       ,	_lowercase      )
     self.assertEqual(_lowercase       ,	batch.decoder_input_ids[0, 0]      )  # EOS
     # Test that special tokens are reset
     self.assertEqual(self.tokenizer.prefix_tokens       ,	[EN_CODE]      )
     self.assertEqual(self.tokenizer.suffix_tokens       ,	[self.tokenizer.eos_token_id]      )




   def 	__a						(    self			:				List[str]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.tokenizer(self.src_text       ,	padding=_lowercase       ,	truncation=_lowercase       ,	max_length=3       ,	return_tensors="""pt"""      )
     SCREAMING_SNAKE_CASE__										=      self.tokenizer(
         text_target=self.tgt_text       ,	padding=_lowercase       ,	truncation=_lowercase       ,	max_length=10       ,	return_tensors="""pt"""      )
     SCREAMING_SNAKE_CASE__										=      targets["""input_ids"""]
     SCREAMING_SNAKE_CASE__										=      shift_tokens_right(
         _lowercase       ,	self.tokenizer.pad_token_id       ,	decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]       ,	)

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




   @require_torch
   def 	__a						(    self			:				str      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      self.tokenizer._build_translation_inputs(
         """A test"""       ,	return_tensors="""pt"""       ,	src_lang="""eng_Latn"""       ,	tgt_lang="""fra_Latn"""      )

     self.assertEqual(
         nested_simplify(_lowercase      )       ,	{
             # A, test, EOS, en_XX
             """input_ids""": [[25_60_47, 70, 73_56, 2]],
             """attention_mask""": [[1, 1, 1, 1]],
             # ar_AR
             """forced_bos_token_id""": 25_60_57,
         }       ,	)




   @require_torch
   def 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      True
     SCREAMING_SNAKE_CASE__										=      self.tokenizer(
         """UN Chief says there is no military solution in Syria"""       ,	src_lang="""eng_Latn"""       ,	tgt_lang="""fra_Latn"""      )
     self.assertEqual(
         inputs.input_ids       ,	[1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2, 25_60_47]      )

     SCREAMING_SNAKE_CASE__										=      False
     SCREAMING_SNAKE_CASE__										=      self.tokenizer(
         """UN Chief says there is no military solution in Syria"""       ,	src_lang="""eng_Latn"""       ,	tgt_lang="""fra_Latn"""      )
     self.assertEqual(
         inputs.input_ids       ,	[25_60_47, 1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2]      )

import socket



def 	__SCREAMING_SNAKE_CASE  (					)							->					Optional[int]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      socket.socket(socket.AF_INET ,     socket.SOCK_STREAM	)
  SCREAMING_SNAKE_CASE__										=      socket.gethostname()
  SCREAMING_SNAKE_CASE__										=      1_23_12

  sock.connect((host, port)	)
  sock.send(B"""Hello server!"""	)

  with open("""Received_file""" ,     """wb"""	) as out_file:
    print("""File opened"""	)
    print("""Receiving data..."""	)
    while True:
      SCREAMING_SNAKE_CASE__										=      sock.recv(10_24	)
      if not data:
        break
      out_file.write(__UpperCamelCase	)

  print("""Successfully received the file"""	)
  sock.close()
  print("""Connection closed"""	)


if __name__ == "__main__":
   main()
