

from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers

class   __UpperCamelCase      :




	def __init__(						self		:  Dict						,		lowerCAmelCase		:  Tuple							):


		'''simple docstring'''







		UpperCAmelCase_    			=     vocab
		UpperCAmelCase_    			=     normalizers.BertNormalizer(
		    clean_text=__SCREAMING_SNAKE_CASE						,		handle_chinese_chars=__SCREAMING_SNAKE_CASE						,		strip_accents=__SCREAMING_SNAKE_CASE						,		lowercase=__SCREAMING_SNAKE_CASE						,		)
		try:
			import rjieba
		except ImportError:
			raise ImportError(
			    "You need to install rjieba to use RoFormerTokenizer. "
			    "See https://pypi.org/project/rjieba/ for installation."							)
		UpperCAmelCase_    			=     rjieba




	def  __A   (						self		:  str						,		lowerCAmelCase		:  List[str]						,		lowerCAmelCase		:  Union[str, Any]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     []

		# this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
		for token, start, end in self.jieba.tokenize(str(__SCREAMING_SNAKE_CASE							)						,		hmm=__SCREAMING_SNAKE_CASE							):
			if token in self.vocab:
				splits.append(normalized_string[start:end]							)
			else:
				UpperCAmelCase_    			=     self.normalizers.normalize_str(__SCREAMING_SNAKE_CASE							).split()
				for token in token_list:
					if token:
						UpperCAmelCase_    			=     start + len(__SCREAMING_SNAKE_CASE							)
						splits.append(normalized_string[start:end]							)
						UpperCAmelCase_    			=     end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

		return splits




	def  __A   (						self		:  List[str]						,		lowerCAmelCase		:  Optional[int]							):


		'''simple docstring'''







		pretok.split(self.jieba_split							)


import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin

class   __UpperCamelCase      (   unittest.TestCase       ,       lowercase  ):




	def  __A   (						self		:  str							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_tool("document-question-answering"							)
		self.tool.setup()
		UpperCAmelCase_    			=     load_tool("document-question-answering"						,		remote=lowerCAmelCase							)




	def  __A   (						self		:  Optional[Any]							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_dataset("hf-internal-testing/example-documents"						,		split="test"							)
		UpperCAmelCase_    			=     dataset[0]["image"]

		UpperCAmelCase_    			=     self.tool(lowerCAmelCase						,		"When is the coffee break?"							)
		self.assertEqual(lowerCAmelCase						,		"11-14 to 11:39 a.m."							)




	def  __A   (						self		:  Any							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_dataset("hf-internal-testing/example-documents"						,		split="test"							)
		UpperCAmelCase_    			=     dataset[0]["image"]

		UpperCAmelCase_    			=     self.remote_tool(lowerCAmelCase						,		"When is the coffee break?"							)
		self.assertEqual(lowerCAmelCase						,		"11-14 to 11:39 a.m."							)




	def  __A   (						self		:  int							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_dataset("hf-internal-testing/example-documents"						,		split="test"							)
		UpperCAmelCase_    			=     dataset[0]["image"]

		self.tool(document=lowerCAmelCase						,		question="When is the coffee break?"							)




	def  __A   (						self		:  Any							):


		'''simple docstring'''







		UpperCAmelCase_    			=     load_dataset("hf-internal-testing/example-documents"						,		split="test"							)
		UpperCAmelCase_    			=     dataset[0]["image"]

		UpperCAmelCase_    			=     self.remote_tool(document=lowerCAmelCase						,		question="When is the coffee break?"							)
		self.assertEqual(lowerCAmelCase						,		"11-14 to 11:39 a.m."							)