



from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
__snake_case		:Optional[int]   	=  Lock()





def   __snake_case			(    _UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase       ):
    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()
            __a		 =       rr_cv[0].recv()
            process_lock.release()

            # take the lower value since you are on the left
            __a		 =       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()
            __a		 =       lr_cv[0].recv()
            process_lock.release()

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





def   __snake_case			(    _UpperCAmelCase       ):
    __a		 =       []
    __a		 =       []
    # 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
    __a		 =       Pipe()
    __a		 =       Pipe()
    process_array_.append(
        Process(
            target=_UpperCAmelCase     ,				args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])     ,				)       )
    __a		 =       temp_rs
    __a		 =       temp_rr

    for i in range(1     ,				len(_UpperCAmelCase       ) - 1       ):
        __a		 =       Pipe()
        __a		 =       Pipe()
        process_array_.append(
            Process(
                target=_UpperCAmelCase     ,				args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])     ,				)       )
        __a		 =       temp_rs
        __a		 =       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       )       ):
        __a		 =       result_pipe[p][0].recv()
        process_array_[p].join()
    return arr





def   __snake_case			(    ):
    __a		 =       list(range(10     ,				0     ,				-1       )       )
    print('''Initial List'''       )
    print(*_UpperCAmelCase       )
    __a		 =       odd_even_transposition(_UpperCAmelCase       )
    print('''Sorted List\n'''       )
    print(*_UpperCAmelCase       )


if __name__ == "__main__":
 main()










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


__snake_case		:Dict   	=  get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model''')

@require_sentencepiece
@require_tokenizers
class 					_A (			__UpperCAmelCase   ,unittest.TestCase					):
       UpperCamelCase__						:					List[str]		      =		GPTSwaTokenizer
       UpperCamelCase__						:					Dict		      =		False
       UpperCamelCase__						:					int		      =		True
       UpperCamelCase__						:					List[Any]		      =		False



       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           super().setUp()

           # We have a SentencePiece fixture for testing
           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE  ,	eos_token='''<unk>'''  ,	bos_token='''<unk>'''  ,	pad_token='''<unk>''')

           tokenizer.save_pretrained(self.tmpdirname)



       def 	_lowerCamelCase    (	self							:  Tuple  ,	__SCREAMING_SNAKE_CASE							:  int):


           '''simple docstring'''

           __a		 =       '''This is a test'''
           __a		 =       '''This is a test'''
           return input_text, output_text



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           __a		 =       '''<s>'''
           __a		 =       1

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



       def 	_lowerCamelCase    (	self							:  List[Any]):


           '''simple docstring'''

           __a		 =       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(__SCREAMING_SNAKE_CASE)  ,	2_000)



       def 	_lowerCamelCase    (	self							:  Dict):


           '''simple docstring'''

           self.assertEqual(self.get_tokenizer().vocab_size  ,	2_000)



       def 	_lowerCamelCase    (	self							:  List[str]):


           '''simple docstring'''

           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE)

           __a		 =       tokenizer.tokenize('''This is a test''')
           self.assertListEqual(__SCREAMING_SNAKE_CASE  ,	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''])

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

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

           __a		 =       tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE)
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE  ,	[262, 272, 1_525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]  ,	)

           __a		 =       tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE)
           # fmt: off
           self.assertListEqual(
               __SCREAMING_SNAKE_CASE  ,	['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.'''])
           # fmt: on



       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       GPTSwaTokenizer(__SCREAMING_SNAKE_CASE)
           __a		 =       ['''This is a test''', '''I was born in 92000, and this is falsé.''']
           __a		 =       [
               [465, 287, 265, 631, 842],
               [262, 272, 1_525, 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(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE):
               self.assertListEqual(tokenizer.encode_fast(__SCREAMING_SNAKE_CASE)  ,	__SCREAMING_SNAKE_CASE)

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





       @slow
       def 	_lowerCamelCase    (	self							:  Any):


           '''simple docstring'''

           __a		 =       [
               '''<|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
           __a		 =       {'''input_ids''': [[63_423, 5, 6_811, 14_954, 282, 816, 3_821, 63_466, 63_425, 63_462, 18, 63_978, 678, 301, 1_320, 63_423, 63_455, 63_458, 18, 63_982, 4_246, 3_940, 1_901, 47_789, 5_547, 18_994], [19_630, 1_100, 63_446, 1_342, 633, 544, 4_488, 593, 5_102, 2_416, 63_495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1_652, 428, 268, 1_936, 515, 268, 58_593, 22_413, 9_106, 546, 268, 33_213, 63_979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [55_130, 63_450, 924, 63_449, 2_249, 4_062, 1_558, 318, 63_504, 21_498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2_827, 2_559, 332, 6_575, 63_443, 26_801, 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=__SCREAMING_SNAKE_CASE  ,	model_name='''AI-Sweden/gpt-sw3-126m'''  ,	sequences=__SCREAMING_SNAKE_CASE  ,	)





