
import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard





class 						lowerCamelCase			(					unittest.TestCase				):







	def    snake_case__    (    self			:Optional[Any] )		->			Optional[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   {
				    '''model_details''': {
				        '''Organization''': '''testing''',
				        '''Model date''': '''today''',
				        '''Model version''': '''v2.1, Developed by Test Corp in 2019.''',
				        '''Architecture''': '''Convolutional Neural Network.''',
				    },
				    '''metrics''': '''BLEU and ROUGE-1''',
				    '''evaluation_data''': {
				        '''Datasets''': {'''BLEU''': '''My-great-dataset-v1''', '''ROUGE-1''': '''My-short-dataset-v2.1'''},
				        '''Preprocessing''': '''See details on https://arxiv.org/pdf/1810.03993.pdf''',
				    },
				    '''training_data''': {
				        '''Dataset''': '''English Wikipedia dump dated 2018-12-01''',
				        '''Preprocessing''': (
				            '''Using SentencePiece vocabulary of size 52k tokens. See details on'''
				            ''' https://arxiv.org/pdf/1810.03993.pdf'''
				        ),
				    },
				    '''quantitative_analyses''': {'''BLEU''': 55.1, '''ROUGE-1''': 7_6},
				}







	def    snake_case__    (    self			:Any )		->			List[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   ModelCard.from_dict(self.inputs_dict )
				self.assertTrue(hasattr(lowercase      ,    '''model_details''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''intended_use''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''factors''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''metrics''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''evaluation_data''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''training_data''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''quantitative_analyses''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''ethical_considerations''' ) )
				self.assertTrue(hasattr(lowercase      ,    '''caveats_and_recommendations''' ) )







	def    snake_case__    (    self			:Tuple )		->			List[str]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   ModelCard.from_dict(self.inputs_dict )
				SCREAMING_SNAKE_CASE    	=   json.loads(modelcard.to_json_string() )
				for key, value in self.inputs_dict.items():
							self.assertEqual(obj[key]      ,    lowercase )







	def    snake_case__    (    self			:List[str] )		->			int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   ModelCard.from_dict(self.inputs_dict )

				with tempfile.TemporaryDirectory() as tmpdirname:
							SCREAMING_SNAKE_CASE    	=   os.path.join(lowercase      ,    '''modelcard.json''' )
							model_card_first.to_json_file(lowercase )
							SCREAMING_SNAKE_CASE    	=   ModelCard.from_json_file(lowercase )

				self.assertEqual(model_card_second.to_dict()      ,    model_card_first.to_dict() )







	def    snake_case__    (    self			:List[Any] )		->			Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   ModelCard.from_dict(self.inputs_dict )

				with tempfile.TemporaryDirectory() as tmpdirname:
							model_card_first.save_pretrained(lowercase )
							SCREAMING_SNAKE_CASE    	=   ModelCard.from_pretrained(lowercase )

				self.assertEqual(model_card_second.to_dict()      ,    model_card_first.to_dict() )

from __future__ import annotations

__lowerCAmelCase				      =					[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]





class 						lowerCamelCase			:







	def __init__(    self			:List[str]      ,    lowercase			:int )		->			None:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   -1
				SCREAMING_SNAKE_CASE    	=   -1
				SCREAMING_SNAKE_CASE    	=   [-1] * length
				SCREAMING_SNAKE_CASE    	=   None
				SCREAMING_SNAKE_CASE    	=   None







	def __repr__(    self			:List[Any] )		->			str:







				"""simple docstring"""






				return f"""Node(min_value={self.minn} max_value={self.maxx})"""



def       a			(   a  )    ->Node | None:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE    	=   Node(len(a  )  )
			SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   min(a  ), max(a  )
			# Leaf node case where the node contains only one unique value
			if root.minn == root.maxx:
						return root
			SCREAMING_SNAKE_CASE    	=   (root.minn + root.maxx) // 2

			SCREAMING_SNAKE_CASE    	=   []
			SCREAMING_SNAKE_CASE    	=   []

			for index, num in enumerate(a  ):
						if num <= pivot:
									left_arr.append(a  )
						else:
									right_arr.append(a  )
						SCREAMING_SNAKE_CASE    	=   len(a  )
			SCREAMING_SNAKE_CASE    	=   build_tree(a  )
			SCREAMING_SNAKE_CASE    	=   build_tree(a  )
			return root


def       a			(   a		,	a		,	a  )    ->int:




			'''simple docstring'''


			if index < 0 or node is None:
						return 0
			# Leaf node cases
			if node.minn == node.maxx:
						return index + 1 if node.minn == num else 0
			SCREAMING_SNAKE_CASE    	=   (node.minn + node.maxx) // 2
			if num <= pivot:
						# go the left subtree and map index to the left subtree
						return rank_till_index(node.left		,	a		,	node.map_left[index] - 1  )
			else:
						# go to the right subtree and map index to the right subtree
						return rank_till_index(node.right		,	a		,	index - node.map_left[index]  )


def       a			(   a		,	a		,	a		,	a  )    ->int:




			'''simple docstring'''


			if start > end:
						return 0
			SCREAMING_SNAKE_CASE    	=   rank_till_index(a		,	a		,	a  )
			SCREAMING_SNAKE_CASE    	=   rank_till_index(a		,	a		,	start - 1  )
			return rank_till_end - rank_before_start


def       a			(   a		,	a		,	a		,	a  )    ->int:




			'''simple docstring'''


			if index > (end - start) or start > end or node is None:
						return -1
			# Leaf node case
			if node.minn == node.maxx:
						return node.minn
			# Number of elements in the left subtree in interval [start, end]
			SCREAMING_SNAKE_CASE    	=   node.map_left[end] - (
			    node.map_left[start - 1] if start else 0
			)
			if num_elements_in_left_tree > index:
						return quantile(
						    node.left		,	a		,	(node.map_left[start - 1] if start else 0)		,	node.map_left[end] - 1		,	)
			else:
						return quantile(
						    node.right		,	index - num_elements_in_left_tree		,	start - (node.map_left[start - 1] if start else 0)		,	end - node.map_left[end]		,	)


def       a			(   a		,	a		,	a		,	a		,	a  )    ->int:




			'''simple docstring'''


			if (
			    start > end
			    or node is None
			    or start_num > end_num
			    or node.minn > end_num
			    or node.maxx < start_num
			):
						return 0
			if start_num <= node.minn and node.maxx <= end_num:
						return end - start + 1
			SCREAMING_SNAKE_CASE    	=   range_counting(
			    node.left		,	(node.map_left[start - 1] if start else 0)		,	node.map_left[end] - 1		,	a		,	a		,	)
			SCREAMING_SNAKE_CASE    	=   range_counting(
			    node.right		,	start - (node.map_left[start - 1] if start else 0)		,	end - node.map_left[end]		,	a		,	a		,	)
			return left + right


if __name__ == "__main__":
							import doctest

							doctest.testmod()