




"""simple docstring"""





import json
import os
import random
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 IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
							from PIL import Image

							from transformers import FlavaImageProcessor, FlavaProcessor
							from transformers.models.flava.image_processing_flava import (
							    FLAVA_CODEBOOK_MEAN,
							    FLAVA_CODEBOOK_STD,
							    FLAVA_IMAGE_MEAN,
							    FLAVA_IMAGE_STD,
							)

@require_vision
class    __lowercase							(      unittest.TestCase						):


				'''simple docstring'''


				def    _lowerCamelCase       ( self :  str   ):
										snake_case__							:       Dict				      =       tempfile.mkdtemp()

										# fmt: off
										snake_case__							:       Any				      =       ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
										# fmt: on
										snake_case__							:       Any				      =       os.path.join(self.tmpdirname   ,VOCAB_FILES_NAMES['''vocab_file''']   )

										with open(self.vocab_file   ,'''w'''   ,encoding='''utf-8'''   ) as fp:
																fp.write(''''''.join([x + '''\n''' for x in vocab_tokens]   )   )

										snake_case__							:       List[str]				      =       {
										    '''image_mean''': FLAVA_IMAGE_MEAN,
										    '''image_std''': FLAVA_IMAGE_STD,
										    '''do_normalize''': True,
										    '''do_resize''': True,
										    '''size''': 2_2_4,
										    '''do_center_crop''': True,
										    '''crop_size''': 2_2_4,
										    '''input_size_patches''': 1_4,
										    '''total_mask_patches''': 7_5,
										    '''mask_group_max_patches''': None,
										    '''mask_group_min_patches''': 1_6,
										    '''mask_group_min_aspect_ratio''': 0.3,
										    '''mask_group_max_aspect_ratio''': None,
										    '''codebook_do_resize''': True,
										    '''codebook_size''': 1_1_2,
										    '''codebook_do_center_crop''': True,
										    '''codebook_crop_size''': 1_1_2,
										    '''codebook_do_map_pixels''': True,
										    '''codebook_do_normalize''': True,
										    '''codebook_image_mean''': FLAVA_CODEBOOK_MEAN,
										    '''codebook_image_std''': FLAVA_CODEBOOK_STD,
										}

										snake_case__							:       Optional[int]				      =       os.path.join(self.tmpdirname   ,A_   )
										with open(self.image_processor_file   ,'''w'''   ,encoding='''utf-8'''   ) as fp:
																json.dump(A_   ,A_   )

				def    _lowerCamelCase       ( self :  List[str]   ,**SCREAMING_SNAKE_CASE_ :  int   ):
										return BertTokenizer.from_pretrained(self.tmpdirname   ,**A_   )

				def    _lowerCamelCase       ( self :  Tuple   ,**SCREAMING_SNAKE_CASE_ :  Optional[Any]   ):
										return BertTokenizerFast.from_pretrained(self.tmpdirname   ,**A_   )

				def    _lowerCamelCase       ( self :  List[Any]   ,**SCREAMING_SNAKE_CASE_ :  Dict   ):
										return FlavaImageProcessor.from_pretrained(self.tmpdirname   ,**A_   )

				def    _lowerCamelCase       ( self :  str   ):
										shutil.rmtree(self.tmpdirname   )

				def    _lowerCamelCase       ( self :  int   ):
										snake_case__							:       Optional[Any]				      =       [np.random.randint(2_5_5   ,size=(3, 3_0, 4_0_0)   ,dtype=np.uinta   )]

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

										return image_inputs

				def    _lowerCamelCase       ( self :  Optional[int]   ):
										snake_case__							:       Tuple				      =       self.get_tokenizer()
										snake_case__							:       Union[str, Any]				      =       self.get_rust_tokenizer()
										snake_case__							:       Union[str, Any]				      =       self.get_image_processor()

										snake_case__							:       Optional[int]				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )
										processor_slow.save_pretrained(self.tmpdirname   )
										snake_case__							:       Any				      =       FlavaProcessor.from_pretrained(self.tmpdirname   ,use_fast=A_   )

										snake_case__							:       List[Any]				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )
										processor_fast.save_pretrained(self.tmpdirname   )
										snake_case__							:       str				      =       FlavaProcessor.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   ,A_   )
										self.assertIsInstance(processor_fast.tokenizer   ,A_   )

										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   ,A_   )
										self.assertIsInstance(processor_fast.image_processor   ,A_   )

				def    _lowerCamelCase       ( self :  Optional[int]   ):
										snake_case__							:       Dict				      =       FlavaProcessor(tokenizer=self.get_tokenizer()   ,image_processor=self.get_image_processor()   )
										processor.save_pretrained(self.tmpdirname   )

										snake_case__							:       Union[str, Any]				      =       self.get_tokenizer(bos_token='''(BOS)'''   ,eos_token='''(EOS)'''   )
										snake_case__							:       int				      =       self.get_image_processor(do_normalize=A_   ,padding_value=1.0   )

										snake_case__							:       Union[str, Any]				      =       FlavaProcessor.from_pretrained(
										    self.tmpdirname   ,bos_token='''(BOS)'''   ,eos_token='''(EOS)'''   ,do_normalize=A_   ,padding_value=1.0   )

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

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

				def    _lowerCamelCase       ( self :  int   ):
										snake_case__							:       Optional[Any]				      =       self.get_image_processor()
										snake_case__							:       Union[str, Any]				      =       self.get_tokenizer()

										snake_case__							:       int				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )

										snake_case__							:       Union[str, Any]				      =       self.prepare_image_inputs()

										snake_case__							:       List[Any]				      =       image_processor(A_   ,return_tensors='''np'''   )
										snake_case__							:       List[str]				      =       processor(images=A_   ,return_tensors='''np'''   )

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

										# With rest of the args
										random.seed(1_2_3_4   )
										snake_case__							:       Any				      =       image_processor(
										    A_   ,return_image_mask=A_   ,return_codebook_pixels=A_   ,return_tensors='''np'''   )
										random.seed(1_2_3_4   )
										snake_case__							:       Dict				      =       processor(
										    images=A_   ,return_image_mask=A_   ,return_codebook_pixels=A_   ,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    _lowerCamelCase       ( self :  List[str]   ):
										snake_case__							:       Dict				      =       self.get_image_processor()
										snake_case__							:       Any				      =       self.get_tokenizer()

										snake_case__							:       str				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )

										snake_case__							:       List[Any]				      =       '''lower newer'''

										snake_case__							:       str				      =       processor(text=A_   )

										snake_case__							:       int				      =       tokenizer(A_   )

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

				def    _lowerCamelCase       ( self :  Tuple   ):
										snake_case__							:       List[str]				      =       self.get_image_processor()
										snake_case__							:       List[str]				      =       self.get_tokenizer()

										snake_case__							:       List[Any]				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )

										snake_case__							:       List[Any]				      =       '''lower newer'''
										snake_case__							:       List[Any]				      =       self.prepare_image_inputs()

										snake_case__							:       List[str]				      =       processor(text=A_   ,images=A_   )

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

										# add extra args
										snake_case__							:       Tuple				      =       processor(text=A_   ,images=A_   ,return_codebook_pixels=A_   ,return_image_mask=A_   )

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

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

				def    _lowerCamelCase       ( self :  Union[str, Any]   ):
										snake_case__							:       Dict				      =       self.get_image_processor()
										snake_case__							:       Dict				      =       self.get_tokenizer()

										snake_case__							:       Optional[int]				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )

										snake_case__							:       int				      =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										snake_case__							:       Any				      =       processor.batch_decode(A_   )
										snake_case__							:       Any				      =       tokenizer.batch_decode(A_   )

										self.assertListEqual(A_   ,A_   )





				def    _lowerCamelCase       ( self :  Optional[Any]   ):
										snake_case__							:       str				      =       self.get_image_processor()
										snake_case__							:       Dict				      =       self.get_tokenizer()

										snake_case__							:       Optional[int]				      =       FlavaProcessor(tokenizer=A_   ,image_processor=A_   )

										snake_case__							:       Any				      =       '''lower newer'''
										snake_case__							:       Dict				      =       self.prepare_image_inputs()

										snake_case__							:       Any				      =       processor(text=A_   ,images=A_   )

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






_A									=		{
    0: 'underwear',
    1: 'pants',
    2: 'belt',
    3: 'suit',
    4: 'shoe',
    5: 'socks',
    6: 'shirt',
    7: 'tie',
    8: 'watch',
}

_A									=		[[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

_A									=		[0 for x in range(len(graph))]
_A									=		[]

def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   Optional[Any]     ,	SCREAMING_SNAKE_CASE__     :   Tuple							):
     __UpperCamelCase       				=1
     while stack:
          __UpperCamelCase       				=stack.pop()
          print(SCREAMING_SNAKE_CASE__     ,	clothes[current_clothing]							)
          order += 1

def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   Any     ,	SCREAMING_SNAKE_CASE__     :   int     ,	SCREAMING_SNAKE_CASE__     :   Tuple							):
     __UpperCamelCase       				=1
     for v in graph[u]:
          if not visited[v]:
               depth_first_search(SCREAMING_SNAKE_CASE__     ,	SCREAMING_SNAKE_CASE__     ,	SCREAMING_SNAKE_CASE__							)

     stack.append(SCREAMING_SNAKE_CASE__							)

def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   int     ,	SCREAMING_SNAKE_CASE__     :   List[str]							):
     for v in range(len(SCREAMING_SNAKE_CASE__							)							):
          if not visited[v]:
               depth_first_search(SCREAMING_SNAKE_CASE__     ,	SCREAMING_SNAKE_CASE__     ,	SCREAMING_SNAKE_CASE__							)


if __name__ == "__main__":
   topological_sort(graph, visited)
   print(stack)
   print_stack(stack, clothes)





