



import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase_		 =					get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")


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



 """simple docstring"""

 a__					: Any =  PegasusTokenizer
 a__					: Any =  PegasusTokenizerFast
 a__					: int =  True
 a__					: Union[str, Any] =  True

 def     snake_case_      (    self					:					Tuple      )   ->	List[Any]:
    super().setUp()

    # We have a SentencePiece fixture for testing
    _A      =       PegasusTokenizer(__lowerCAmelCase      )
    tokenizer.save_pretrained(self.tmpdirname      )

 @cached_property
 def     snake_case_      (    self					:					Union[str, Any]      )   ->	int:
    return PegasusTokenizer.from_pretrained('''google/pegasus-large'''      )

 def     snake_case_      (    self					:					Union[str, Any]			,						**__lowerCAmelCase					:					Any      )   ->	PegasusTokenizer:
    return PegasusTokenizer.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					Optional[Any]      )   ->	List[Any]:
    return ("This is a test", "This is a test")

 def     snake_case_      (    self					:					Dict      )   ->	Dict:
    _A      =       '''</s>'''
    _A      =       1

    self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCAmelCase      )			,						__lowerCAmelCase      )
    self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCAmelCase      )			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					Optional[Any]      )   ->	List[str]:
    _A      =       list(self.get_tokenizer().get_vocab().keys()      )

    self.assertEqual(vocab_keys[0]			,						'''<pad>'''      )
    self.assertEqual(vocab_keys[1]			,						'''</s>'''      )
    self.assertEqual(vocab_keys[-1]			,						'''v'''      )
    self.assertEqual(len(__lowerCAmelCase      )			,						11_03      )

 def     snake_case_      (    self					:					Optional[int]      )   ->	Union[str, Any]:
    self.assertEqual(self.get_tokenizer().vocab_size			,						11_03      )

 def     snake_case_      (    self					:					Any      )   ->	int:
    _A      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
    _A      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
    _A      =       (
        '''Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'''
        ''' </s> <pad> <pad> <pad>'''
    )
    _A      =       rust_tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase			,						add_special_tokens=__lowerCAmelCase      ).input_ids[0]
    _A      =       py_tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase			,						add_special_tokens=__lowerCAmelCase      ).input_ids[0]
    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					List[str]      )   ->	Optional[Any]:
    _A      =       self._large_tokenizer
    # <mask_1> masks whole sentence while <mask_2> masks single word
    _A      =       '''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
    _A      =       [2, 4_13, 6_15, 1_14, 3, 19_71, 1_13, 16_79, 1_07_10, 1_07, 1]
    _A      =       tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase      ).input_ids[0]
    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					Any      )   ->	Union[str, Any]:
    _A      =       self._large_tokenizer
    # The tracebacks for the following asserts are **better** without messages or self.assertEqual
    assert tokenizer.vocab_size == 9_61_03
    assert tokenizer.pad_token_id == 0
    assert tokenizer.eos_token_id == 1
    assert tokenizer.offset == 1_03
    assert tokenizer.unk_token_id == tokenizer.offset + 2 == 1_05
    assert tokenizer.unk_token == "<unk>"
    assert tokenizer.model_max_length == 10_24
    _A      =       '''To ensure a smooth flow of bank resolutions.'''
    _A      =       [4_13, 6_15, 1_14, 22_91, 19_71, 1_13, 16_79, 1_07_10, 1_07, 1]
    _A      =       tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase      ).input_ids[0]
    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )
    assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]      ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]

 @require_torch
 def     snake_case_      (    self					:					Dict      )   ->	Any:
    _A      =       ['''This is going to be way too long.''' * 1_50, '''short example''']
    _A      =       ['''not super long but more than 5 tokens''', '''tiny''']
    _A      =       self._large_tokenizer(__lowerCAmelCase			,						padding=__lowerCAmelCase			,						truncation=__lowerCAmelCase			,						return_tensors='''pt'''      )
    _A      =       self._large_tokenizer(
        text_target=__lowerCAmelCase			,						max_length=5			,						padding=__lowerCAmelCase			,						truncation=__lowerCAmelCase			,						return_tensors='''pt'''      )

    assert batch.input_ids.shape == (2, 10_24)
    assert batch.attention_mask.shape == (2, 10_24)
    assert targets["input_ids"].shape == (2, 5)
    assert len(__lowerCAmelCase      ) == 2  # input_ids, attention_mask.

 @slow
 def     snake_case_      (    self					:					Union[str, Any]      )   ->	Tuple:
    # fmt: off
    _A      =       {'''input_ids''': [[3_89_79, 1_43, 1_84_85, 6_06, 1_30, 2_66_69, 8_76_86, 1_21, 5_41_89, 11_29, 1_11, 2_66_69, 8_76_86, 1_21, 91_14, 1_47_87, 1_21, 1_32_49, 1_58, 5_92, 9_56, 1_21, 1_46_21, 3_15_76, 1_43, 6_26_13, 1_08, 96_88, 9_30, 4_34_30, 1_15_62, 6_26_13, 3_04, 1_08, 1_14_43, 8_97, 1_08, 93_14, 1_74_15, 6_33_99, 1_08, 1_14_43, 76_14, 1_83_16, 1_18, 42_84, 71_48, 1_24_30, 1_43, 14_00, 2_57_03, 1_58, 1_11, 42_84, 71_48, 1_17_72, 1_43, 2_12_97, 10_64, 1_58, 1_22, 2_04, 35_06, 17_54, 11_33, 1_47_87, 15_81, 1_15, 3_32_24, 44_82, 1_11, 13_55, 1_10, 2_91_73, 3_17, 5_08_33, 1_08, 2_01_47, 9_46_65, 1_11, 7_71_98, 1_07, 1], [1_10, 6_26_13, 1_17, 6_38, 1_12, 11_33, 1_21, 2_00_98, 13_55, 7_90_50, 1_38_72, 1_35, 15_96, 5_35_41, 13_52, 1_41, 1_30_39, 55_42, 1_24, 3_02, 5_18, 1_11, 2_68, 29_56, 1_15, 1_49, 44_27, 1_07, 1, 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], [1_39, 12_35, 27_99, 1_82_89, 1_77_80, 2_04, 1_09, 94_74, 12_96, 1_07, 1, 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, 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, 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, 1, 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], [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, 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]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=__lowerCAmelCase			,						model_name='''google/bigbird-pegasus-large-arxiv'''			,						revision='''ba85d0851d708441f91440d509690f1ab6353415'''			,						)


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



 """simple docstring"""

 a__					: List[str] =  PegasusTokenizer
 a__					: Dict =  PegasusTokenizerFast
 a__					: Optional[int] =  True
 a__					: Any =  True

 def     snake_case_      (    self					:					int      )   ->	Any:
    super().setUp()

    # We have a SentencePiece fixture for testing
    _A      =       PegasusTokenizer(__lowerCAmelCase			,						offset=0			,						mask_token_sent=__lowerCAmelCase			,						mask_token='''[MASK]'''      )
    tokenizer.save_pretrained(self.tmpdirname      )

 @cached_property
 def     snake_case_      (    self					:					Dict      )   ->	str:
    return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''      )

 def     snake_case_      (    self					:					Any			,						**__lowerCAmelCase					:					Tuple      )   ->	PegasusTokenizer:
    return PegasusTokenizer.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					Union[str, Any]			,						__lowerCAmelCase					:					Union[str, Any]      )   ->	Optional[int]:
    return ("This is a test", "This is a test")

 def     snake_case_      (    self					:					Any      )   ->	Optional[Any]:
    _A      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
    _A      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
    _A      =       (
        '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
        ''' <pad> <pad> <pad>'''
    )
    _A      =       rust_tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase			,						add_special_tokens=__lowerCAmelCase      ).input_ids[0]
    _A      =       py_tokenizer([raw_input_str]			,						return_tensors=__lowerCAmelCase			,						add_special_tokens=__lowerCAmelCase      ).input_ids[0]
    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )

 @require_torch
 def     snake_case_      (    self					:					List[Any]      )   ->	str:
    _A      =       ['''This is going to be way too long.''' * 10_00, '''short example''']
    _A      =       ['''not super long but more than 5 tokens''', '''tiny''']
    _A      =       self._large_tokenizer(__lowerCAmelCase			,						padding=__lowerCAmelCase			,						truncation=__lowerCAmelCase			,						return_tensors='''pt'''      )
    _A      =       self._large_tokenizer(
        text_target=__lowerCAmelCase			,						max_length=5			,						padding=__lowerCAmelCase			,						truncation=__lowerCAmelCase			,						return_tensors='''pt'''      )

    assert batch.input_ids.shape == (2, 40_96)
    assert batch.attention_mask.shape == (2, 40_96)
    assert targets["input_ids"].shape == (2, 5)
    assert len(__lowerCAmelCase      ) == 2  # input_ids, attention_mask.

 def     snake_case_      (    self					:					Optional[int]      )   ->	Dict:
    _A      =       (
        '''This is an example string that is used to test the original TF implementation against the HF'''
        ''' implementation'''
    )

    _A      =       self._large_tokenizer(__lowerCAmelCase      ).input_ids

    self.assertListEqual(
        __lowerCAmelCase			,						[1_82, 1_17, 1_42, 5_87, 42_11, 1_20, 1_17, 2_63, 1_12, 8_04, 1_09, 8_56, 2_50_16, 31_37, 4_64, 1_09, 2_69_55, 31_37, 1]			,						)







'''simple docstring'''





from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
__lowerCamelCase												=						Lock()


def        a__     (					UpperCamelCase_						:      str,   UpperCamelCase_						:      Any,   UpperCamelCase_						:      Any,   UpperCamelCase_						:      int,   UpperCamelCase_						:      Union[str, Any],   UpperCamelCase_						:      List[str],   UpperCamelCase_						:      Optional[int]						):
   global process_lock

   # we perform n swaps since after n swaps we know we are sorted
   # we *could* stop early if we are sorted already, but it takes as long to
   # find out we are sorted as it does to sort the list with this algorithm
   for i in range(0,   10						):
      if (i + position) % 2 == 0 and r_send is not None:
         # send your value to your right neighbor
         process_lock.acquire()
         r_send[1].send(UpperCamelCase_						)
         process_lock.release()

         # receive your right neighbor's value
         process_lock.acquire()
         UpperCAmelCase__	:Union[str, Any]      =      rr_cv[0].recv()
         process_lock.release()

         # take the lower value since you are on the left
         UpperCAmelCase__	:List[Any]      =      min(UpperCamelCase_,   UpperCamelCase_						)
      elif (i + position) % 2 != 0 and l_send is not None:
         # send your value to your left neighbor
         process_lock.acquire()
         l_send[1].send(UpperCamelCase_						)
         process_lock.release()

         # receive your left neighbor's value
         process_lock.acquire()
         UpperCAmelCase__	:List[str]      =      lr_cv[0].recv()
         process_lock.release()

         # take the higher value since you are on the right
         UpperCAmelCase__	:List[Any]      =      max(UpperCamelCase_,   UpperCamelCase_						)
    # after all swaps are performed, send the values back to main
   result_pipe[1].send(UpperCamelCase_						)


def        a__     (					UpperCamelCase_						:      int						):
   UpperCAmelCase__	:List[str]      =      []
   UpperCAmelCase__	:Any      =      []
   # initialize the list of pipes where the values will be retrieved
   for _ in arr:
      result_pipe.append(Pipe()						)
   # creates the processes
   # the first and last process only have one neighbor so they are made outside
   # of the loop
   UpperCAmelCase__	:str      =      Pipe()
   UpperCAmelCase__	:Dict      =      Pipe()
   process_array_.append(
       Process(
           target=UpperCamelCase_,   args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0]),   )						)
   UpperCAmelCase__	:Optional[Any]      =      temp_rs
   UpperCAmelCase__	:Any      =      temp_rr

   for i in range(1,   len(UpperCamelCase_						) - 1						):
      UpperCAmelCase__	:Optional[int]      =      Pipe()
      UpperCAmelCase__	:List[str]      =      Pipe()
      process_array_.append(
          Process(
              target=UpperCamelCase_,   args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i]),   )						)
      UpperCAmelCase__	:Optional[Any]      =      temp_rs
      UpperCAmelCase__	:str      =      temp_rr

   process_array_.append(
       Process(
           target=UpperCamelCase_,   args=(
               len(UpperCamelCase_						) - 1,
               arr[len(UpperCamelCase_						) - 1],
               temp_ls,
               None,
               temp_lr,
               None,
               result_pipe[len(UpperCamelCase_						) - 1],
           ),   )						)

   # start the processes
   for p in process_array_:
      p.start()

   # wait for the processes to end and write their values to the list
   for p in range(0,   len(UpperCamelCase_						)						):
      UpperCAmelCase__	:List[str]      =      result_pipe[p][0].recv()
      process_array_[p].join()
   return arr


def        a__     (					):
   UpperCAmelCase__	:Optional[Any]      =      list(range(10,   0,   -1						)						)
   print('''Initial List'''						)
   print(*UpperCamelCase_						)
   UpperCAmelCase__	:str      =      odd_even_transposition(UpperCamelCase_						)
   print('''Sorted List\n'''						)
   print(*UpperCamelCase_						)


if __name__ == "__main__":
    main()



