




'''simple docstring'''







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


lowercase      :   Union[str, Any]      =       get_tests_dir("""fixtures/test_sentencepiece_with_bytefallback.model""")







@require_sentencepiece
@require_tokenizers
class 					_a (UpperCamelCase_,		unittest.TestCase	):





     '''simple docstring'''



     lowerCAmelCase_  :     Any          =					GPTSwaTokenizer
     lowerCAmelCase_  :     Dict          =					False
     lowerCAmelCase_  :     Any          =					True
     lowerCAmelCase_  :     Union[str, Any]          =					False







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

          # We have a SentencePiece fixture for testing
          snake_case			:      Union[str, Any]        =			GPTSwaTokenizer(a__							,eos_token="""<unk>"""							,bos_token="""<unk>"""							,pad_token="""<unk>"""							)

          tokenizer.save_pretrained(self.tmpdirname							)







     def 			snake_case_      (				self							,__a							)      ->				Any:
          snake_case			:      Dict        =			"This is a test"
          snake_case			:      List[str]        =			"This is a test"
          return input_text, output_text







     def 			snake_case_      (				self							)      ->				Optional[int]:
          snake_case			:      str        =			"<s>"
          snake_case			:      Any        =			1

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







     def 			snake_case_      (				self							)      ->				str:
          snake_case			:      str        =			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__							)							,2_000							)







     def 			snake_case_      (				self							)      ->				Tuple:
          self.assertEqual(self.get_tokenizer().vocab_size							,2_000							)







     def 			snake_case_      (				self							)      ->				int:
          snake_case			:      Optional[Any]        =			GPTSwaTokenizer(a__							)

          snake_case			:      List[Any]        =			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]							)

          snake_case			:      List[str]        =			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

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

          snake_case			:      str        =			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 			snake_case_      (				self							)      ->				Optional[Any]:
          snake_case			:      Dict        =			GPTSwaTokenizer(a__							)
          snake_case			:      str        =			["This is a test", "I was born in 92000, and this is falsé."]
          snake_case			:      Any        =			[
              [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(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 			snake_case_      (				self							)      ->				Union[str, Any]:
          snake_case			:      str        =			[
              "<|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
          snake_case			:      Union[str, Any]        =			{"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=a__							,model_name="""AI-Sweden/gpt-sw3-126m"""							,sequences=a__							,)





'''simple docstring'''

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


snake_case									=    logging.get_logger(__name__)

snake_case									=    {
    """Visual-Attention-Network/van-base""": (
        """https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
    ),
}




class    lowerCAmelCase       (     UpperCamelCase_  ):
 A_				:				Tuple	=			"""van"""


 def __init__(    self  : List[Any]			,							a__  : Dict=224			,							a__  : Dict=3			,							a__  : Union[str, Any]=[7, 3, 3, 3]			,							a__  : Optional[Any]=[4, 2, 2, 2]			,							a__  : Optional[Any]=[64, 128, 320, 512]			,							a__  : List[str]=[3, 3, 12, 3]			,							a__  : Any=[8, 8, 4, 4]			,							a__  : Optional[int]="gelu"			,							a__  : List[Any]=0.02			,							a__  : Tuple=1e-6			,							a__  : List[str]=1e-2			,							a__  : List[str]=0.0			,							a__  : List[Any]=0.0			,							**a__  : Tuple			,							):
  '''simple docstring'''

  super().__init__(**a__    )
  lowerCAmelCase__     :   Any     		=	image_size
  lowerCAmelCase__     :   Tuple     		=	num_channels
  lowerCAmelCase__     :   List[Any]     		=	patch_sizes
  lowerCAmelCase__     :   Dict     		=	strides
  lowerCAmelCase__     :   List[str]     		=	hidden_sizes
  lowerCAmelCase__     :   Union[str, Any]     		=	depths
  lowerCAmelCase__     :   Tuple     		=	mlp_ratios
  lowerCAmelCase__     :   Optional[Any]     		=	hidden_act
  lowerCAmelCase__     :   Dict     		=	initializer_range
  lowerCAmelCase__     :   int     		=	layer_norm_eps
  lowerCAmelCase__     :   Optional[Any]     		=	layer_scale_init_value
  lowerCAmelCase__     :   List[str]     		=	drop_path_rate
  lowerCAmelCase__     :   Any     		=	dropout_rate





