




import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase		:				Tuple       			=		'▁'

__lowerCAmelCase		:				Optional[int]       			=		get_tests_dir('fixtures/test_sentencepiece.model')




@require_sentencepiece
class     snake_case__							(_UpperCamelCase    ,       unittest.TestCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							Optional[Any]							 =					BertGenerationTokenizer
				SCREAMING_SNAKE_CASE_       :							List[str]							 =					False
				SCREAMING_SNAKE_CASE_       :							str							 =					True





				def 							__UpperCAmelCase							(      self				:     int							)					->     List[Any]:
							super().setUp()

							a    =			BertGenerationTokenizer(__lowerCamelCase					,      keep_accents=__lowerCamelCase							)
							tokenizer.save_pretrained(self.tmpdirname							)





				def 							__UpperCAmelCase							(      self				:     Union[str, Any]							)					->     Union[str, Any]:
							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 							__UpperCAmelCase							(      self				:     Union[str, Any]							)					->     Tuple:
							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]					,      "<pad>"							)
							self.assertEqual(len(__lowerCamelCase							)					,      10_02							)





				def 							__UpperCAmelCase							(      self				:     str							)					->     Optional[int]:
							self.assertEqual(self.get_tokenizer().vocab_size					,      10_00							)





				def 							__UpperCAmelCase							(      self				:     List[str]							)					->     int:
							a    =			BertGenerationTokenizer(__lowerCamelCase					,      keep_accents=__lowerCamelCase							)

							a    =			tokenizer.tokenize("This is a test"							)
							self.assertListEqual(__lowerCamelCase					,      ["▁This", "▁is", "▁a", "▁t", "est"]							)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(__lowerCamelCase							)					,      [2_85, 46, 10, 1_70, 3_82]					,      )

							a    =			tokenizer.tokenize("I was born in 92000, and this is falsé."							)
							self.assertListEqual(
							    __lowerCamelCase					,      [
							        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",
							        ".",
							    ]					,      )
							a    =			tokenizer.convert_tokens_to_ids(__lowerCamelCase							)
							self.assertListEqual(
							    __lowerCamelCase					,      [8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]					,      )

							a    =			tokenizer.convert_ids_to_tokens(__lowerCamelCase							)
							self.assertListEqual(
							    __lowerCamelCase					,      [
							        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 							__UpperCAmelCase							(      self				:     Dict							)					->     int:
							return BertGenerationTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder"							)





				@slow
				def 							__UpperCAmelCase							(      self				:     List[Any]							)					->     int:
							a    =			"Hello World!"
							a    =			[1_85_36, 22_60, 1_01]

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





				@slow
				def 							__UpperCAmelCase							(      self				:     Optional[Any]							)					->     Any:
							a    =			(
							    "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"
							)
							a    =			[
							    8_71,
							    4_19,
							    3_58,
							    9_46,
							    9_91,
							    25_21,
							    4_52,
							    3_58,
							    13_57,
							    3_87,
							    77_51,
							    35_36,
							    1_12,
							    9_85,
							    4_56,
							    1_26,
							    8_65,
							    9_38,
							    54_00,
							    57_34,
							    4_58,
							    13_68,
							    4_67,
							    7_86,
							    24_62,
							    52_46,
							    11_59,
							    6_33,
							    8_65,
							    45_19,
							    4_57,
							    5_82,
							    8_52,
							    25_57,
							    4_27,
							    9_16,
							    5_08,
							    4_05,
							    3_43_24,
							    4_97,
							    3_91,
							    4_08,
							    1_13_42,
							    12_44,
							    3_85,
							    1_00,
							    9_38,
							    9_85,
							    4_56,
							    5_74,
							    3_62,
							    1_25_97,
							    32_00,
							    31_29,
							    11_72,
							]

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





				@require_torch
				@slow
				def 							__UpperCAmelCase							(      self				:     Dict							)					->     Any:
							import torch

							from transformers import BertGenerationConfig, BertGenerationEncoder

							# Build sequence
							a    =			list(self.big_tokenizer.get_vocab().keys()							)[:10]
							a    =			" ".join(__lowerCamelCase							)
							a    =			self.big_tokenizer.encode_plus(__lowerCamelCase					,      return_tensors="pt"					,      return_token_type_ids=__lowerCamelCase							)
							a    =			self.big_tokenizer.batch_encode_plus(
							    [sequence + " " + sequence]					,      return_tensors="pt"					,      return_token_type_ids=__lowerCamelCase							)

							a    =			BertGenerationConfig()
							a    =			BertGenerationEncoder(__lowerCamelCase							)

							assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

							with torch.no_grad():
										model(**__lowerCamelCase							)
										model(**__lowerCamelCase							)





				@slow
				def 							__UpperCAmelCase							(      self				:     Dict							)					->     Any:
							# fmt: off
							a    =			{"input_ids": [[3_92_86, 4_58, 3_63_35, 20_01, 4_56, 1_30_73, 1_32_66, 4_55, 1_13, 77_46, 17_41, 1_11_57, 3_91, 1_30_73, 1_32_66, 4_55, 1_13, 39_67, 3_54_12, 1_13, 49_36, 1_09, 38_70, 23_77, 1_13, 3_00_84, 4_57_20, 4_58, 1_34, 1_74_96, 1_12, 5_03, 1_16_72, 1_13, 1_18, 1_12, 56_65, 1_33_47, 3_86_87, 1_12, 14_96, 3_13_89, 1_12, 32_68, 4_72_64, 1_34, 9_62, 1_12, 1_63_77, 80_35, 2_31_30, 4_30, 1_21_69, 1_55_18, 2_85_92, 4_58, 1_46, 4_16_97, 1_09, 3_91, 1_21_69, 1_55_18, 1_66_89, 4_58, 1_46, 4_13_58, 1_09, 4_52, 7_26, 40_34, 1_11, 7_63, 3_54_12, 50_82, 3_88, 19_03, 1_11, 90_51, 3_91, 28_70, 4_89_18, 19_00, 11_23, 5_50, 9_98, 1_12, 95_86, 1_59_85, 4_55, 3_91, 4_10, 2_29_55, 3_76_36, 1_14], [4_48, 1_74_96, 4_19, 36_63, 3_85, 7_63, 1_13, 2_75_33, 28_70, 32_83, 1_30_43, 16_39, 2_47_13, 5_23, 6_56, 2_40_13, 1_85_50, 25_21, 5_17, 2_70_14, 2_12_44, 4_20, 12_12, 14_65, 3_91, 9_27, 48_33, 3_88, 5_78, 1_17_86, 1_14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [4_84, 21_69, 76_87, 2_19_32, 1_81_46, 7_26, 3_63, 1_70_32, 33_91, 1_14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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/bert_for_seq_generation_L-24_bbc_encoder"					,      revision="c817d1fd1be2ffa69431227a1fe320544943d4db"					,      )












from bisect import bisect
from itertools import accumulate




def 			__magic_name__				( A		:					Optional[Any],  A		:					List[str],  A		:					Tuple,  A		:					Optional[Any]   ):






			'''simple docstring'''







			a    =			sorted(zip(A,  A   ),  key=lambda A   : x[0] / x[1],  reverse=A   )
			a    ,		a    =			[i[0] for i in r], [i[1] for i in r]
			a    =			list(accumulate(A   )   )
			a    =			bisect(A,  A   )
			return (
			    0
			    if k == 0
			    else sum(vl[:k]   ) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
			    if k != n
			    else sum(vl[:k]   )
			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()






