
import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase			:     Any           =   get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model')




@require_sentencepiece
@require_tokenizers
class        UpperCAmelCase_			( _A  ,       unittest.TestCase     ):


  '''simple docstring'''







  a__           =		GPTSwaTokenizer
  a__           =		False
  a__           =		True
  a__           =		False
  def 							_lowercase							( self			: Any    )			->	List[str]:







    """simple docstring"""






    super().setUp()

    # We have a SentencePiece fixture for testing
    __magic_name__				     =       GPTSwaTokenizer(UpperCamelCase__			,							eos_token="""<unk>"""			,							bos_token="""<unk>"""			,							pad_token="""<unk>"""    )

    tokenizer.save_pretrained(self.tmpdirname    )
  def 							_lowercase							( self			: int			,							UpperCamelCase__			: List[str]    )			->	Dict:







    """simple docstring"""






    __magic_name__				     =       """This is a test"""
    __magic_name__				     =       """This is a test"""
    return input_text, output_text
  def 							_lowercase							( self			: Optional[int]    )			->	Tuple:







    """simple docstring"""






    __magic_name__				     =       """<s>"""
    __magic_name__				     =       1

    self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase__    )			,							UpperCamelCase__    )
    self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase__    )			,							UpperCamelCase__    )
  def 							_lowercase							( self			: Optional[Any]    )			->	List[Any]:







    """simple docstring"""






    __magic_name__				     =       list(self.get_tokenizer().get_vocab().keys()    )

    self.assertEqual(vocab_keys[0]			,							"""<unk>"""    )
    self.assertEqual(vocab_keys[1]			,							"""<s>"""    )
    self.assertEqual(vocab_keys[-1]			,							"""j"""    )
    self.assertEqual(len(UpperCamelCase__    )			,							2000    )
  def 							_lowercase							( self			: Dict    )			->	Any:







    """simple docstring"""






    self.assertEqual(self.get_tokenizer().vocab_size			,							2000    )
  def 							_lowercase							( self			: Any    )			->	str:







    """simple docstring"""






    __magic_name__				     =       GPTSwaTokenizer(UpperCamelCase__    )

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

    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__    )			,							[465, 287, 265, 631, 842]    )

    __magic_name__				     =       tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
    # fmt: off
    self.assertListEqual(
        UpperCamelCase__			,							["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]			,							)
    # fmt: on

    __magic_name__				     =       tokenizer.convert_tokens_to_ids(UpperCamelCase__    )
    self.assertListEqual(
        UpperCamelCase__			,							[262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]			,							)

    __magic_name__				     =       tokenizer.convert_ids_to_tokens(UpperCamelCase__    )
    # fmt: off
    self.assertListEqual(
        UpperCamelCase__			,							["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]    )
    # fmt: on
  def 							_lowercase							( self			: Optional[int]    )			->	Dict:







    """simple docstring"""






    __magic_name__				     =       GPTSwaTokenizer(UpperCamelCase__    )
    __magic_name__				     =       ["""This is a test""", """I was born in 92000, and this is falsé."""]
    __magic_name__				     =       [
        [465, 287, 265, 631, 842],
        [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
    ]

    # Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
    for text, expected_ids in zip(UpperCamelCase__			,							UpperCamelCase__    ):
      self.assertListEqual(tokenizer.encode_fast(UpperCamelCase__    )			,							UpperCamelCase__    )

    # Test that decode_fast returns the input text
    for text, token_ids in zip(UpperCamelCase__			,							UpperCamelCase__    ):
      self.assertEqual(tokenizer.decode_fast(UpperCamelCase__    )			,							UpperCamelCase__    )





  @slow
  def 							_lowercase							( self			: Dict    )			->	Optional[Any]:







    """simple docstring"""






    __magic_name__				     =       [
        """<|python|>def fibonacci(n)\n    if n < 0:\n        print('Incorrect input')""",
        """Hey there, how are you doing this fine day?""",
        """This is a text with a trailing spaces followed by a dot     .""",
        """Häj sväjs lillebrör! =)""",
        """Det är inget fel på Mr. Cool""",
    ]

    # fmt: off
    __magic_name__				     =       {"""input_ids""": [[6_3423, 5, 6811, 1_4954, 282, 816, 3821, 6_3466, 6_3425, 6_3462, 18, 6_3978, 678, 301, 1320, 6_3423, 6_3455, 6_3458, 18, 6_3982, 4246, 3940, 1901, 4_7789, 5547, 1_8994], [1_9630, 1100, 6_3446, 1342, 633, 544, 4488, 593, 5102, 2416, 6_3495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 5_8593, 2_2413, 9106, 546, 268, 3_3213, 6_3979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_5130, 6_3450, 924, 6_3449, 2249, 4062, 1558, 318, 6_3504, 2_1498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 6_3443, 2_6801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
    # fmt: on
    self.tokenizer_integration_test_util(
        expected_encoding=UpperCamelCase__			,							model_name="""AI-Sweden/gpt-sw3-126m"""			,							sequences=UpperCamelCase__			,							)



import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu




@require_cpu
class        UpperCAmelCase_			( unittest.TestCase     ):


  '''simple docstring'''







  def 							_lowercase							( self			: List[Any]    )			->	Union[str, Any]:







    """simple docstring"""






    __magic_name__				     =       torch.nn.Linear(10			,							10    )
    __magic_name__				     =       torch.optim.SGD(model.parameters()			,							0.1    )
    __magic_name__				     =       Accelerator()
    __magic_name__				     =       accelerator.prepare(UpperCamelCase__    )
    try:
      pickle.loads(pickle.dumps(UpperCamelCase__    )    )
    except Exception as e:
      self.fail(F'''Accelerated optimizer pickling failed with {e}'''    )
    AcceleratorState._reset_state()

