




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       :	Dict									=     get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model")







@require_sentencepiece
@require_tokenizers
class 						A(		UpperCamelCase							,   unittest.TestCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		GPTSwaTokenizer
 UpperCamelCase		     =		False
 UpperCamelCase		     =		True
 UpperCamelCase		     =		False

 def        a__				(       self      :						Optional[int]						)     ->			Any:

       """simple docstring"""






       super().setUp()

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

       tokenizer.save_pretrained(self.tmpdirname						)

 def        a__				(       self      :						str		,							A_      :						Union[str, Any]						)     ->			str:

       """simple docstring"""






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

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

       """simple docstring"""






       lowerCamelCase_	  =					'<s>'
       lowerCamelCase_	  =					1

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

 def        a__				(       self      :						Optional[int]						)     ->			Any:

       """simple docstring"""






       lowerCamelCase_	  =					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(A_						)		,							2000						)

 def        a__				(       self      :						Optional[int]						)     ->			Any:

       """simple docstring"""






       self.assertEqual(self.get_tokenizer().vocab_size		,							2000						)

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

       """simple docstring"""






       lowerCamelCase_	  =					GPTSwaTokenizer(A_						)

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

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

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

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

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

 def        a__				(       self      :						List[str]						)     ->			List[str]:

       """simple docstring"""






       lowerCamelCase_	  =					GPTSwaTokenizer(A_						)
       lowerCamelCase_	  =					['This is a test', 'I was born in 92000, and this is falsé.']
       lowerCamelCase_	  =					[
           [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(A_		,							A_						):
             self.assertListEqual(tokenizer.encode_fast(A_						)		,							A_						)

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





 @slow
 def        a__				(       self      :						Optional[int]						)     ->			Tuple:

       """simple docstring"""






       lowerCamelCase_	  =					[
           '<|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
       lowerCamelCase_	  =					{'input_ids': [[63423, 5, 6811, 14954, 282, 816, 3821, 63466, 63425, 63462, 18, 63978, 678, 301, 1320, 63423, 63455, 63458, 18, 63982, 4246, 3940, 1901, 47789, 5547, 18994], [19630, 1100, 63446, 1342, 633, 544, 4488, 593, 5102, 2416, 63495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 58593, 22413, 9106, 546, 268, 33213, 63979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [55130, 63450, 924, 63449, 2249, 4062, 1558, 318, 63504, 21498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 63443, 26801, 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=A_		,							model_name='AI-Sweden/gpt-sw3-126m'		,							sequences=A_		,							)









from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase       :	str									=     logging.get_logger(__name__)

lowerCamelCase       :	List[str]									=     {
    "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
}







class 						A(		UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		'''gpt_neox_japanese'''

 def __init__(       self      :						int		,							A_      :						Dict=32000		,							A_      :						List[Any]=2560		,							A_      :						Dict=32		,							A_      :						Union[str, Any]=32		,							A_      :						List[Any]=4		,							A_      :						List[str]="gelu"		,							A_      :						Dict=1.00		,							A_      :						int=10000		,							A_      :						Dict=2048		,							A_      :						Dict=0.02		,							A_      :						Any=1E-5		,							A_      :						Union[str, Any]=True		,							A_      :						int=31996		,							A_      :						List[str]=31999		,							A_      :						List[Any]=0.1		,							A_      :						List[Any]=0.0		,							**A_      :						Tuple		,							)     ->			Dict:

       """simple docstring"""






       super().__init__(bos_token_id=A_		,							eos_token_id=A_		,							**A_						)
       lowerCamelCase_	  =					vocab_size
       lowerCamelCase_	  =					max_position_embeddings
       lowerCamelCase_	  =					hidden_size
       lowerCamelCase_	  =					num_hidden_layers
       lowerCamelCase_	  =					num_attention_heads
       lowerCamelCase_	  =					intermediate_multiple_size
       lowerCamelCase_	  =					hidden_act
       lowerCamelCase_	  =					rotary_pct
       lowerCamelCase_	  =					rotary_emb_base
       lowerCamelCase_	  =					initializer_range
       lowerCamelCase_	  =					layer_norm_eps
       lowerCamelCase_	  =					use_cache
       lowerCamelCase_	  =					attention_dropout
       lowerCamelCase_	  =					hidden_dropout



