






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


UpperCamelCase								=		"▁"

UpperCamelCase								=		get_tests_dir("fixtures/test_sentencepiece.model")

@require_sentencepiece
class 				lowerCAmelCase_	(		__snake_case   ,		unittest.TestCase			):
				_UpperCamelCase					:       int							       = BertGenerationTokenizer
				_UpperCamelCase					:       List[str]							       = False
				_UpperCamelCase					:       Union[str, Any]							       = True


				def 						__a					(					self      ):
											super().setUp()

											_lowercase							:   Union[str, Any] 							=   BertGenerationTokenizer(_lowerCAmelCase ,						keep_accents=_lowerCAmelCase      )
											tokenizer.save_pretrained(self.tmpdirname      )


				def 						__a					(					self      ):
											_lowercase							:   str 							=   '<s>'
											_lowercase							:   Dict 							=   1

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


				def 						__a					(					self      ):
											_lowercase							:   Optional[int] 							=   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      ) ,						1_0_0_2      )


				def 						__a					(					self      ):
											self.assertEqual(self.get_tokenizer().vocab_size ,						1_0_0_0      )


				def 						__a					(					self      ):
											_lowercase							:   int 							=   BertGenerationTokenizer(_lowerCAmelCase ,						keep_accents=_lowerCAmelCase      )

											_lowercase							:   Tuple 							=   tokenizer.tokenize('This is a test'      )
											self.assertListEqual(_lowerCAmelCase ,						['▁This', '▁is', '▁a', '▁t', 'est']      )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(_lowerCAmelCase      ) ,						[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2] ,						)

											_lowercase							:   str 							=   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',
											        '.',
											    ] ,						)
											_lowercase							:   int 							=   tokenizer.convert_tokens_to_ids(_lowerCAmelCase      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4] ,						)

											_lowercase							:   Optional[Any] 							=   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 						__a					(					self      ):
											return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'      )


				@slow
				def 						__a					(					self      ):
											_lowercase							:   Union[str, Any] 							=   'Hello World!'
											_lowercase							:   Dict 							=   [1_8_5_3_6, 2_2_6_0, 1_0_1]

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


				@slow
				def 						__a					(					self      ):
											_lowercase							:   Any 							=   (
											    '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'
											)
											_lowercase							:   int 							=   [
											    8_7_1,
											    4_1_9,
											    3_5_8,
											    9_4_6,
											    9_9_1,
											    2_5_2_1,
											    4_5_2,
											    3_5_8,
											    1_3_5_7,
											    3_8_7,
											    7_7_5_1,
											    3_5_3_6,
											    1_1_2,
											    9_8_5,
											    4_5_6,
											    1_2_6,
											    8_6_5,
											    9_3_8,
											    5_4_0_0,
											    5_7_3_4,
											    4_5_8,
											    1_3_6_8,
											    4_6_7,
											    7_8_6,
											    2_4_6_2,
											    5_2_4_6,
											    1_1_5_9,
											    6_3_3,
											    8_6_5,
											    4_5_1_9,
											    4_5_7,
											    5_8_2,
											    8_5_2,
											    2_5_5_7,
											    4_2_7,
											    9_1_6,
											    5_0_8,
											    4_0_5,
											    3_4_3_2_4,
											    4_9_7,
											    3_9_1,
											    4_0_8,
											    1_1_3_4_2,
											    1_2_4_4,
											    3_8_5,
											    1_0_0,
											    9_3_8,
											    9_8_5,
											    4_5_6,
											    5_7_4,
											    3_6_2,
											    1_2_5_9_7,
											    3_2_0_0,
											    3_1_2_9,
											    1_1_7_2,
											]

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


				@require_torch
				@slow
				def 						__a					(					self      ):
											import torch

											from transformers import BertGenerationConfig, BertGenerationEncoder

											# Build sequence
											_lowercase							:   List[str] 							=   list(self.big_tokenizer.get_vocab().keys()      )[:1_0]
											_lowercase							:   Union[str, Any] 							=   ' '.join(_lowerCAmelCase      )
											_lowercase							:   int 							=   self.big_tokenizer.encode_plus(_lowerCAmelCase ,						return_tensors='pt' ,						return_token_type_ids=_lowerCAmelCase      )
											_lowercase							:   Any 							=   self.big_tokenizer.batch_encode_plus(
											    [sequence + ' ' + sequence] ,						return_tensors='pt' ,						return_token_type_ids=_lowerCAmelCase      )

											_lowercase							:   Optional[int] 							=   BertGenerationConfig()
											_lowercase							:   Any 							=   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 						__a					(					self      ):
											# fmt: off
											_lowercase							:   List[Any] 							=   {'input_ids': [[3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4], [4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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' ,						)







"""simple docstring"""

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


_UpperCamelCase		     =    logging.get_logger(__name__)

_UpperCamelCase		     =    {
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}






class 			__a					(						__magic_name__       ):





       """simple docstring"""


       __UpperCamelCase					:      str    =						'dpr'






       def __init__(   self			,					snake_case=30_522			,					snake_case=768			,					snake_case=12			,					snake_case=12			,					snake_case=3_072			,					snake_case="gelu"			,					snake_case=0.1			,					snake_case=0.1			,					snake_case=512			,					snake_case=2			,					snake_case=0.02			,					snake_case=1e-12			,					snake_case=0			,					snake_case="absolute"			,					snake_case = 0			,					**snake_case			,					):





        """simple docstring"""

        super().__init__(pad_token_id=snake_case			,					**snake_case   )

        lowerCAmelCase__   :				Dict 			=				vocab_size
        lowerCAmelCase__   :				int 			=				hidden_size
        lowerCAmelCase__   :				List[str] 			=				num_hidden_layers
        lowerCAmelCase__   :				List[Any] 			=				num_attention_heads
        lowerCAmelCase__   :				Any 			=				hidden_act
        lowerCAmelCase__   :				Any 			=				intermediate_size
        lowerCAmelCase__   :				str 			=				hidden_dropout_prob
        lowerCAmelCase__   :				List[str] 			=				attention_probs_dropout_prob
        lowerCAmelCase__   :				List[Any] 			=				max_position_embeddings
        lowerCAmelCase__   :				Optional[Any] 			=				type_vocab_size
        lowerCAmelCase__   :				Tuple 			=				initializer_range
        lowerCAmelCase__   :				Dict 			=				layer_norm_eps
        lowerCAmelCase__   :				Dict 			=				projection_dim
        lowerCAmelCase__   :				Any 			=				position_embedding_type






