import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase    :				Optional[Any]							     =	get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
@require_tokenizers
class __snake_case       (		__lowerCamelCase     ,	unittest.TestCase	):
			lowerCAmelCase_														=							XGLMTokenizer
			lowerCAmelCase_														=							XGLMTokenizerFast
			lowerCAmelCase_														=							True
			lowerCAmelCase_														=							True




			def 			__a		(					self    :       Optional[int]   ):



					"""simple docstring"""






					super().setUp()

					# We have a SentencePiece fixture for testing
					SCREAMING_SNAKE_CASE__    							=   XGLMTokenizer(SCREAMING_SNAKE_CASE_ ,			keep_accents=SCREAMING_SNAKE_CASE_   )
					tokenizer.save_pretrained(self.tmpdirname   )




			def 			__a		(					self    :       Optional[int]   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   """<pad>"""
					SCREAMING_SNAKE_CASE__    							=   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 			__a		(					self    :       Optional[Any]   ):



					"""simple docstring"""






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

					self.assertEqual(vocab_keys[0] ,			"""<s>"""   )
					self.assertEqual(vocab_keys[1] ,			"""<pad>"""   )
					self.assertEqual(len(SCREAMING_SNAKE_CASE_   ) ,			10_08   )




			def 			__a		(					self    :       Any   ):



					"""simple docstring"""






					self.assertEqual(self.get_tokenizer().vocab_size ,			10_08   )




			def 			__a		(					self    :       Any   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   XGLMTokenizer(SCREAMING_SNAKE_CASE_ ,			keep_accents=SCREAMING_SNAKE_CASE_   )

					SCREAMING_SNAKE_CASE__    							=   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_   ) ,			[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]] ,			)

					SCREAMING_SNAKE_CASE__    							=   tokenizer.tokenize("""I was born in 92000, and this is falsé."""   )
					self.assertListEqual(
					    SCREAMING_SNAKE_CASE_ ,			[
					        SPIECE_UNDERLINE + """I""",
					        SPIECE_UNDERLINE + """was""",
					        SPIECE_UNDERLINE + """b""",
					        """or""",
					        """n""",
					        SPIECE_UNDERLINE + """in""",
					        SPIECE_UNDERLINE + """""",
					        """9""",
					        """2""",
					        """0""",
					        """0""",
					        """0""",
					        """,""",
					        SPIECE_UNDERLINE + """and""",
					        SPIECE_UNDERLINE + """this""",
					        SPIECE_UNDERLINE + """is""",
					        SPIECE_UNDERLINE + """f""",
					        """al""",
					        """s""",
					        """é""",
					        """.""",
					    ] ,			)
					SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_   )
					self.assertListEqual(
					    SCREAMING_SNAKE_CASE_ ,			[
					        value + tokenizer.fairseq_offset
					        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
					    ] ,			)

					SCREAMING_SNAKE_CASE__    							=   tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_   )
					self.assertListEqual(
					    SCREAMING_SNAKE_CASE_ ,			[
					        SPIECE_UNDERLINE + """I""",
					        SPIECE_UNDERLINE + """was""",
					        SPIECE_UNDERLINE + """b""",
					        """or""",
					        """n""",
					        SPIECE_UNDERLINE + """in""",
					        SPIECE_UNDERLINE + """""",
					        """<unk>""",
					        """2""",
					        """0""",
					        """0""",
					        """0""",
					        """,""",
					        SPIECE_UNDERLINE + """and""",
					        SPIECE_UNDERLINE + """this""",
					        SPIECE_UNDERLINE + """is""",
					        SPIECE_UNDERLINE + """f""",
					        """al""",
					        """s""",
					        """<unk>""",
					        """.""",
					    ] ,			)




			@cached_property
			def 			__a		(					self    :       Tuple   ):



					"""simple docstring"""






					return XGLMTokenizer.from_pretrained("""facebook/xglm-564M"""   )




			def 			__a		(					self    :       Optional[Any]   ):



					"""simple docstring"""






					with tempfile.NamedTemporaryFile() as f:
							shutil.copyfile(SCREAMING_SNAKE_CASE_ ,			f.name   )
							SCREAMING_SNAKE_CASE__    							=   XGLMTokenizer(f.name ,			keep_accents=SCREAMING_SNAKE_CASE_   )
							SCREAMING_SNAKE_CASE__    							=   pickle.dumps(SCREAMING_SNAKE_CASE_   )
					pickle.loads(SCREAMING_SNAKE_CASE_   )




			def 			__a		(					self    :       List[Any]   ):



					"""simple docstring"""






					if not self.test_rust_tokenizer:
							return

					SCREAMING_SNAKE_CASE__    							=   self.get_tokenizer()
					SCREAMING_SNAKE_CASE__    							=   self.get_rust_tokenizer()

					SCREAMING_SNAKE_CASE__    							=   """I was born in 92000, and this is falsé."""

					SCREAMING_SNAKE_CASE__    							=   tokenizer.tokenize(SCREAMING_SNAKE_CASE_   )
					SCREAMING_SNAKE_CASE__    							=   rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_   )
					self.assertListEqual(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_   )

					SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(SCREAMING_SNAKE_CASE_ ,			add_special_tokens=SCREAMING_SNAKE_CASE_   )
					SCREAMING_SNAKE_CASE__    							=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_ ,			add_special_tokens=SCREAMING_SNAKE_CASE_   )
					self.assertListEqual(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_   )

					SCREAMING_SNAKE_CASE__    							=   self.get_rust_tokenizer()
					SCREAMING_SNAKE_CASE__    							=   tokenizer.encode(SCREAMING_SNAKE_CASE_   )
					SCREAMING_SNAKE_CASE__    							=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_   )
					self.assertListEqual(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_   )




			@slow
			def 			__a		(					self    :       Tuple   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   """Hello World!"""
					SCREAMING_SNAKE_CASE__    							=   [2, 3_12_27, 44_47, 35]

					self.assertListEqual(SCREAMING_SNAKE_CASE_ ,			self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_   )   )




			@slow
			def 			__a		(					self    :       Optional[Any]   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   (
					    """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
					    """ add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"""
					)
					# fmt: off
					SCREAMING_SNAKE_CASE__    							=   [2, 10_18, 67, 11, 19_88, 26_17, 56_31, 2_78, 11, 34_07, 48, 7_16_30, 2_80_85, 4, 32_34, 1_57, 13, 6, 5, 6, 4, 35_26, 7_68, 15, 6_59, 57, 2_98, 39_83, 8_64, 1_29, 21, 6, 5, 1_36_75, 3_77, 6_52, 75_80, 1_03_41, 1_55, 28_17, 4_22, 16_66, 7, 16_74, 53, 1_13, 20_22_77, 1_78_92, 33, 60, 87, 4, 32_34, 1_57, 61, 26_67, 5_23_76, 19, 88, 23, 7_35]
					# fmt: on

					self.assertListEqual(SCREAMING_SNAKE_CASE_ ,			self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_   )   )




			@slow
			def 			__a		(					self    :       Tuple   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   {
					    """input_ids""": [[2, 10_88_25, 11_63, 15, 8_80_10, 4_73, 1_58_98, 1_57, 1_36_72, 18_57, 3_12, 8, 23_80_21, 11_63, 53, 1_36_72, 18_57, 3_12, 8, 5_32_83, 18_23_96, 8, 1_85_66, 16, 3_67_33, 41_01, 8, 2_30, 24_40_17, 12_25_53, 7, 15, 13_25_97, 4, 2_93, 1_25_11, 76_10, 4, 34_14, 13_25_97, 9, 4, 3_23_61, 3_62, 4, 7_34, 2_85_12, 3_25_69, 18, 4, 3_23_61, 2_60_96, 1_49_82, 73, 1_87_15, 2_14_33, 23_52_61, 15, 4_92, 1_24_27, 16, 53, 1_87_15, 2_14_33, 6_54_54, 15, 2_36_59, 5_63, 16, 2_78, 5_97, 28_43, 5_95, 79_31, 18_23_96, 6_41_86, 22, 8_86, 5_95, 13_29_81, 53, 2_55_40, 34_49, 4_39_82, 3_99_01, 59_51, 8_78, 3_30, 4, 2_76_94, 8_02_69, 3_12, 53, 65_17, 1_17_80, 6_11, 2_04_08, 5], [2, 6, 13_25_97, 67, 4_28_97, 33, 5_92, 8, 16_37_29, 2_55_40, 3_61, 13_69_97, 10_95_14, 17_32_30, 7, 5_01, 60, 10_29_13, 1_96, 56_31, 2_35, 6_32_43, 4_73, 6, 23_17_57, 74, 52_77, 79_05, 53, 30_95, 3_73_17, 22, 4_54, 18_38_74, 5], [2, 2_68, 3_12_98, 4_65_30, 6, 13_29_35, 4_38_31, 7, 5_97, 32, 24, 36_88, 98_65, 5]],
					    """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, 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]]
					}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=SCREAMING_SNAKE_CASE_ ,			model_name="""facebook/xglm-564M""" ,			padding=SCREAMING_SNAKE_CASE_ ,			)

def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: list				,  __UpperCamelCase					: list				,  __UpperCamelCase					: int				,  __UpperCamelCase					: int				,  __UpperCamelCase					: int			)							->      int:







  """simple docstring"""





  if index == number_of_items:
    return 0
  SCREAMING_SNAKE_CASE__    							=   0
  SCREAMING_SNAKE_CASE__    							=   0
  SCREAMING_SNAKE_CASE__    							=   knapsack(__UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  index + 1			)
  if weights[index] <= max_weight:
    SCREAMING_SNAKE_CASE__    							=   values[index] + knapsack(
        __UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  max_weight - weights[index]				,  index + 1			)
  return max(__UpperCamelCase				,  __UpperCamelCase			)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
