


"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor



@require_vision
class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						str						=				tempfile.mkdtemp()

			__snake_case	:						List[Any]						=				[
			    '[UNK]',
			    '[CLS]',
			    '[SEP]',
			    '[PAD]',
			    '[MASK]',
			    '的',
			    '价',
			    '格',
			    '是',
			    '15',
			    '便',
			    'alex',
			    '##andra',
			    '，',
			    '。',
			    '-',
			    't',
			    'shirt',
			]
			__snake_case	:						Optional[Any]						=				os.path.join(self.tmpdirname				,       VOCAB_FILES_NAMES['''vocab_file''']					)
			with open(self.vocab_file				,       '''w'''				,       encoding='''utf-8'''					) as vocab_writer:
				vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]					)					)

			__snake_case	:						Any						=				{
			    'do_resize': True,
			    'size': {'height': 2_24, 'width': 2_24},
			    'do_center_crop': True,
			    'crop_size': {'height': 18, 'width': 18},
			    'do_normalize': True,
			    'image_mean': [0.4814_5466, 0.457_8275, 0.4082_1073],
			    'image_std': [0.2686_2954, 0.2613_0258, 0.2757_7711],
			    'do_convert_rgb': True,
			}
			__snake_case	:						List[str]						=				os.path.join(self.tmpdirname				,       lowercase_					)
			with open(self.image_processor_file				,       '''w'''				,       encoding='''utf-8'''					) as fp:
				json.dump(lowercase_				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self				,       **a_					):





			'''simple docstring'''

			return BertTokenizer.from_pretrained(self.tmpdirname				,       **lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self				,       **a_					):





			'''simple docstring'''

			return BertTokenizerFast.from_pretrained(self.tmpdirname				,       **lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self				,       **a_					):





			'''simple docstring'''

			return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname				,       **lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			shutil.rmtree(self.tmpdirname					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Optional[Any]						=				[np.random.randint(2_55				,       size=(3, 30, 4_00)				,       dtype=np.uinta					)]

			__snake_case	:						List[Any]						=				[Image.fromarray(np.moveaxis(lowercase_				,       0				,       -1					)					) for x in image_inputs]

			return image_inputs



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Optional[Any]						=				self.get_tokenizer()
			__snake_case	:						Dict						=				self.get_rust_tokenizer()
			__snake_case	:						List[str]						=				self.get_image_processor()

			__snake_case	:						Optional[int]						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)
			processor_slow.save_pretrained(self.tmpdirname					)
			__snake_case	:						Union[str, Any]						=				ChineseCLIPProcessor.from_pretrained(self.tmpdirname				,       use_fast=lowercase_					)

			__snake_case	:						List[str]						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)
			processor_fast.save_pretrained(self.tmpdirname					)
			__snake_case	:						Optional[Any]						=				ChineseCLIPProcessor.from_pretrained(self.tmpdirname					)

			self.assertEqual(processor_slow.tokenizer.get_vocab()				,       tokenizer_slow.get_vocab()					)
			self.assertEqual(processor_fast.tokenizer.get_vocab()				,       tokenizer_fast.get_vocab()					)
			self.assertEqual(tokenizer_slow.get_vocab()				,       tokenizer_fast.get_vocab()					)
			self.assertIsInstance(processor_slow.tokenizer				,       lowercase_					)
			self.assertIsInstance(processor_fast.tokenizer				,       lowercase_					)

			self.assertEqual(processor_slow.image_processor.to_json_string()				,       image_processor.to_json_string()					)
			self.assertEqual(processor_fast.image_processor.to_json_string()				,       image_processor.to_json_string()					)
			self.assertIsInstance(processor_slow.image_processor				,       lowercase_					)
			self.assertIsInstance(processor_fast.image_processor				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Tuple						=				ChineseCLIPProcessor(tokenizer=self.get_tokenizer()				,       image_processor=self.get_image_processor()					)
			processor.save_pretrained(self.tmpdirname					)

			__snake_case	:						Union[str, Any]						=				self.get_tokenizer(cls_token='''(CLS)'''				,       sep_token='''(SEP)'''					)
			__snake_case	:						Optional[int]						=				self.get_image_processor(do_normalize=lowercase_					)

			__snake_case	:						Optional[Any]						=				ChineseCLIPProcessor.from_pretrained(
			    self.tmpdirname				,       cls_token='''(CLS)'''				,       sep_token='''(SEP)'''				,       do_normalize=lowercase_					)

			self.assertEqual(processor.tokenizer.get_vocab()				,       tokenizer_add_kwargs.get_vocab()					)
			self.assertIsInstance(processor.tokenizer				,       lowercase_					)

			self.assertEqual(processor.image_processor.to_json_string()				,       image_processor_add_kwargs.to_json_string()					)
			self.assertIsInstance(processor.image_processor				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Union[str, Any]						=				self.get_image_processor()
			__snake_case	:						List[str]						=				self.get_tokenizer()

			__snake_case	:						Any						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)

			__snake_case	:						List[str]						=				self.prepare_image_inputs()

			__snake_case	:						List[str]						=				image_processor(lowercase_				,       return_tensors='''np'''					)
			__snake_case	:						List[str]						=				processor(images=lowercase_				,       return_tensors='''np'''					)

			for key in input_feat_extract.keys():
				self.assertAlmostEqual(input_feat_extract[key].sum()				,       input_processor[key].sum()				,       delta=1E-2					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[Any]						=				self.get_image_processor()
			__snake_case	:						Optional[int]						=				self.get_tokenizer()

			__snake_case	:						int						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)

			__snake_case	:						List[str]						=				'Alexandra，T-shirt的价格是15便士。'

			__snake_case	:						List[str]						=				processor(text=lowercase_					)

			__snake_case	:						List[Any]						=				tokenizer(lowercase_					)

			for key in encoded_tok.keys():
				self.assertListEqual(encoded_tok[key]				,       encoded_processor[key]					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Optional[Any]						=				self.get_image_processor()
			__snake_case	:						Any						=				self.get_tokenizer()

			__snake_case	:						Dict						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)

			__snake_case	:						Optional[Any]						=				'Alexandra，T-shirt的价格是15便士。'
			__snake_case	:						Optional[Any]						=				self.prepare_image_inputs()

			__snake_case	:						List[str]						=				processor(text=lowercase_				,       images=lowercase_					)

			self.assertListEqual(list(inputs.keys()					)				,       ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']					)

			# test if it raises when no input is passed
			with pytest.raises(lowercase_					):
				processor()



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Tuple						=				self.get_image_processor()
			__snake_case	:						Dict						=				self.get_tokenizer()

			__snake_case	:						Optional[Any]						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)

			__snake_case	:						Optional[Any]						=				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

			__snake_case	:						Tuple						=				processor.batch_decode(lowercase_					)
			__snake_case	:						Union[str, Any]						=				tokenizer.batch_decode(lowercase_					)

			self.assertListEqual(lowercase_				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Dict						=				self.get_image_processor()
			__snake_case	:						str						=				self.get_tokenizer()

			__snake_case	:						Optional[Any]						=				ChineseCLIPProcessor(tokenizer=lowercase_				,       image_processor=lowercase_					)

			__snake_case	:						Optional[int]						=				'Alexandra，T-shirt的价格是15便士。'
			__snake_case	:						Optional[int]						=				self.prepare_image_inputs()

			__snake_case	:						int						=				processor(text=lowercase_				,       images=lowercase_					)

			self.assertListEqual(list(inputs.keys()					)				,       processor.model_input_names					)









# using dfs for finding eulerian path traversal




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Any		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[int]=None     ):
       '''simple docstring'''





       _lowerCamelCase       :		Optional[Any]		=(path or []) + [u]
       for v in graph[u]:
              if visited_edge[u][v] is False:
                     _lowerCamelCase	,     _lowerCamelCase       :		Dict		=True, True
                     _lowerCamelCase       :		Optional[Any]		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       return path




def 	a_      (    SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[Any]     ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		=0
       _lowerCamelCase       :		Union[str, Any]		=-1
       for i in range(SCREAMING_SNAKE_CASE__     ):
              if i not in graph.keys():
                     continue
              if len(graph[i]     ) % 2 == 1:
                     odd_degree_nodes += 1
                     _lowerCamelCase       :		Tuple		=i
       if odd_degree_nodes == 0:
              return 1, odd_node
       if odd_degree_nodes == 2:
              return 2, odd_node
       return 3, odd_node




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]		,			SCREAMING_SNAKE_CASE__					:      Any     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=[[False for _ in range(max_node + 1     )] for _ in range(max_node + 1     )]
       _lowerCamelCase	,     _lowerCamelCase       :		Optional[int]		=check_circuit_or_path(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       if check == 3:
              print('graph is not Eulerian'     )
              print('no path'     )
              return
       _lowerCamelCase       :		Any		=1
       if check == 2:
              _lowerCamelCase       :		Tuple		=odd_node
              print('graph has a Euler path'     )
       if check == 1:
              print('graph has a Euler cycle'     )
       _lowerCamelCase       :		int		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       print(SCREAMING_SNAKE_CASE__     )




def 	a_      (    ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		={1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
       _lowerCamelCase       :		str		={1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
       _lowerCamelCase       :		List[Any]		={1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
       _lowerCamelCase       :		Any		={1: [2, 3], 2: [1, 3], 3: [1, 2]}
       _lowerCamelCase       :		Dict		={
           1: [],
           2: []
           # all degree is zero
       }
       _lowerCamelCase       :		str		=10
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 main()


