


from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest





@require_tokenizers
class    lowerCAmelCase__				(			__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	DPRContextEncoderTokenizer
						__UpperCAmelCase   :		List[str]  					=	DPRContextEncoderTokenizerFast
						__UpperCAmelCase   :		Optional[int]  					=	True





@require_tokenizers
class    lowerCAmelCase__				(			__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	DPRQuestionEncoderTokenizer
						__UpperCAmelCase   :		str  					=	DPRQuestionEncoderTokenizerFast
						__UpperCAmelCase   :		List[str]  					=	True





@require_tokenizers
class    lowerCAmelCase__				(			__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	DPRReaderTokenizer
						__UpperCAmelCase   :		List[str]  					=	DPRReaderTokenizerFast
						__UpperCAmelCase   :		str  					=	True




						@slow
						def 					_UpperCamelCase			(   self     ):
							lowerCamelCase_			:							Optional[int]      =       self.tokenizer_class.from_pretrained("bert-base-uncased"     )

							lowerCamelCase_			:							str      =       tokenizer.encode("question sequence"				,							add_special_tokens=a_     )
							lowerCamelCase_			:							Optional[Any]      =       tokenizer.encode("title sequence"				,							add_special_tokens=a_     )
							lowerCamelCase_			:							List[str]      =       tokenizer.encode("text sequence " * 4				,							add_special_tokens=a_     )
							lowerCamelCase_			:							str      =       [[101] + text_a + [102] + text_a + [102] + text_a]
							lowerCamelCase_			:							str      =       BatchEncoding({"input_ids": input_ids}     )

							lowerCamelCase_			:							Dict      =       [[0] * len(input_ids[0]     )]
							lowerCamelCase_			:							List[Any]      =       [[0] * len(input_ids[0]     )]
							lowerCamelCase_			:							List[Any]      =       [0]
							lowerCamelCase_			:							Tuple      =       DPRReaderOutput(a_				,							a_				,							a_     )

							lowerCamelCase_   ,lowerCamelCase_			:							Optional[int]      =       8, 9
							lowerCamelCase_			:							List[str]      =       10
							lowerCamelCase_			:							Any      =       10
							lowerCamelCase_			:							List[Any]      =       tokenizer.decode_best_spans(a_				,							a_     )
							self.assertEqual(predicted_spans[0].start_index				,							a_     )
							self.assertEqual(predicted_spans[0].end_index				,							a_     )
							self.assertEqual(predicted_spans[0].doc_id				,							0     )




						@slow
						def 					_UpperCamelCase			(   self     ):
							lowerCamelCase_			:							List[Any]      =       self.tokenizer_class.from_pretrained("bert-base-uncased"     )

							lowerCamelCase_			:							Any      =       tokenizer.encode("question sequence"				,							add_special_tokens=a_     )
							lowerCamelCase_			:							List[str]      =       tokenizer.encode("title sequence"				,							add_special_tokens=a_     )
							lowerCamelCase_			:							Optional[Any]      =       tokenizer.encode("text sequence"				,							add_special_tokens=a_     )
							lowerCamelCase_			:							Union[str, Any]      =       [101] + text_a + [102] + text_a + [102] + text_a
							lowerCamelCase_			:							str      =       tokenizer(questions=["question sequence"]				,							titles=["title sequence"]				,							texts=["text sequence"]     )
							self.assertIn("input_ids"				,							a_     )
							self.assertIn("attention_mask"				,							a_     )
							self.assertListEqual(encoded_input["input_ids"][0]				,							a_     )





from __future__ import annotations





class    lowerCAmelCase__				:






						"""simple docstring"""




						def __init__(   self				,							a_     ):
							lowerCamelCase_			:							List[str]      =       value
							lowerCamelCase_			:							Node | None      =       None
							lowerCamelCase_			:							Node | None      =       None





class    lowerCAmelCase__				:






						"""simple docstring"""
						__UpperCAmelCase   :		int




						def __init__(   self     ):
							lowerCamelCase_			:							str      =       0




						def 					_UpperCamelCase			(   self				,							a_				,							a_     ):
							if node is None:
								return

							if path_sum == self.target:
								self.paths += 1

							if node.left:
								self.depth_first_search(node.left				,							path_sum + node.left.value     )
							if node.right:
								self.depth_first_search(node.right				,							path_sum + node.right.value     )




						def 					_UpperCamelCase			(   self				,							a_				,							a_ = None     ):
							if node is None:
								return 0
							if target is not None:
								lowerCamelCase_			:							List[str]      =       target

							self.depth_first_search(a_				,							node.value     )
							self.path_sum(node.left     )
							self.path_sum(node.right     )

							return self.paths


if __name__ == "__main__":
							import doctest

							doctest.testmod()

