


'''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 IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
       from PIL import Image

       from transformers import AlignProcessor, EfficientNetImageProcessor

@require_vision
class 		UpperCAmelCase_      (  unittest.TestCase		):





     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  Optional[int]:
        lowerCAmelCase     =			tempfile.mkdtemp()

        lowerCAmelCase     =			[
            '[UNK]',
            '[CLS]',
            '[SEP]',
            '[PAD]',
            '[MASK]',
            'want',
            '##want',
            '##ed',
            'wa',
            'un',
            'runn',
            '##ing',
            ',',
            'low',
            'lowest',
        ]
        lowerCAmelCase     =			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]    )    )

        lowerCAmelCase     =			{
            'do_resize': True,
            'size': 2_0,
            'do_center_crop': True,
            'crop_size': 1_8,
            'do_normalize': True,
            'image_mean': [0.48_145_466, 0.4_578_275, 0.40_821_073],
            'image_std': [0.26_862_954, 0.26_130_258, 0.27_577_711],
        }
        lowerCAmelCase     =			os.path.join(self.tmpdirname    ,      UpperCAmelCase__    )
        with open(self.image_processor_file    ,      'w'    ,      encoding='utf-8'    ) as fp:
           json.dump(UpperCAmelCase__    ,      UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Tuple    ,      **UpperCAmelCase__       :      Optional[int]    )				->  Tuple:
        return BertTokenizer.from_pretrained(self.tmpdirname    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    ,      **UpperCAmelCase__       :      Optional[int]    )				->  Any:
        return BertTokenizerFast.from_pretrained(self.tmpdirname    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    ,      **UpperCAmelCase__       :      int    )				->  Union[str, Any]:
        return EfficientNetImageProcessor.from_pretrained(self.tmpdirname    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    )				->  Tuple:
        shutil.rmtree(self.tmpdirname    )





     def 							__UpperCAmelCase      ( self       :      Any    )				->  Optional[Any]:
        lowerCAmelCase     =			[np.random.randint(2_5_5    ,      size=(3, 3_0, 4_0_0)    ,      dtype=np.uinta    )]
        lowerCAmelCase     =			[Image.fromarray(np.moveaxis(UpperCAmelCase__    ,      0    ,      -1    )    ) for x in image_inputs]
        return image_inputs





     def 							__UpperCAmelCase      ( self       :      Dict    )				->  List[str]:
        lowerCAmelCase     =			self.get_tokenizer()
        lowerCAmelCase     =			self.get_rust_tokenizer()
        lowerCAmelCase     =			self.get_image_processor()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )
        processor_slow.save_pretrained(self.tmpdirname    )
        lowerCAmelCase     =			AlignProcessor.from_pretrained(self.tmpdirname    ,      use_fast=UpperCAmelCase__    )

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )
        processor_fast.save_pretrained(self.tmpdirname    )
        lowerCAmelCase     =			AlignProcessor.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    ,      UpperCAmelCase__    )
        self.assertIsInstance(processor_fast.tokenizer    ,      UpperCAmelCase__    )

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





     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  str:
        lowerCAmelCase     =			AlignProcessor(tokenizer=self.get_tokenizer()    ,      image_processor=self.get_image_processor()    )
        processor.save_pretrained(self.tmpdirname    )

        lowerCAmelCase     =			self.get_tokenizer(bos_token='(BOS)'    ,      eos_token='(EOS)'    )
        lowerCAmelCase     =			self.get_image_processor(do_normalize=UpperCAmelCase__    ,      padding_value=1.0    )

        lowerCAmelCase     =			AlignProcessor.from_pretrained(
            self.tmpdirname    ,      bos_token='(BOS)'    ,      eos_token='(EOS)'    ,      do_normalize=UpperCAmelCase__    ,      padding_value=1.0    )

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

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





     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    )				->  Any:
        lowerCAmelCase     =			self.get_image_processor()
        lowerCAmelCase     =			self.get_tokenizer()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )

        lowerCAmelCase     =			self.prepare_image_inputs()

        lowerCAmelCase     =			image_processor(UpperCAmelCase__    ,      return_tensors='np'    )
        lowerCAmelCase     =			processor(images=UpperCAmelCase__    ,      return_tensors='np'    )

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





     def 							__UpperCAmelCase      ( self       :      Dict    )				->  Union[str, Any]:
        lowerCAmelCase     =			self.get_image_processor()
        lowerCAmelCase     =			self.get_tokenizer()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )

        lowerCAmelCase     =			'lower newer'

        lowerCAmelCase     =			processor(text=UpperCAmelCase__    )

        lowerCAmelCase     =			tokenizer(UpperCAmelCase__    ,      padding='max_length'    ,      max_length=6_4    )

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





     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  Any:
        lowerCAmelCase     =			self.get_image_processor()
        lowerCAmelCase     =			self.get_tokenizer()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )

        lowerCAmelCase     =			'lower newer'
        lowerCAmelCase     =			self.prepare_image_inputs()

        lowerCAmelCase     =			processor(text=UpperCAmelCase__    ,      images=UpperCAmelCase__    )

        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(UpperCAmelCase__    ):
           processor()





     def 							__UpperCAmelCase      ( self       :      List[str]    )				->  Dict:
        lowerCAmelCase     =			self.get_image_processor()
        lowerCAmelCase     =			self.get_tokenizer()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )

        lowerCAmelCase     =			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        lowerCAmelCase     =			processor.batch_decode(UpperCAmelCase__    )
        lowerCAmelCase     =			tokenizer.batch_decode(UpperCAmelCase__    )

        self.assertListEqual(UpperCAmelCase__    ,      UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      str    )				->  Tuple:
        lowerCAmelCase     =			self.get_image_processor()
        lowerCAmelCase     =			self.get_tokenizer()

        lowerCAmelCase     =			AlignProcessor(tokenizer=UpperCAmelCase__    ,      image_processor=UpperCAmelCase__    )

        lowerCAmelCase     =			'lower newer'
        lowerCAmelCase     =			self.prepare_image_inputs()

        lowerCAmelCase     =			processor(text=UpperCAmelCase__    ,      images=UpperCAmelCase__    )

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









'''simple docstring'''




def 	a_					( lowerCamelCase	:     Optional[Any]				):
   return [
       {
           0: [1, 2],
           1: [0, 2],
           2: [0, 1, 3, 5],
           3: [2, 4],
           4: [3],
           5: [2, 6, 8],
           6: [5, 7],
           7: [6, 8],
           8: [5, 7],
       },
       {
           0: [6],
           1: [9],
           2: [4, 5],
           3: [4],
           4: [2, 3],
           5: [2],
           6: [0, 7],
           7: [6],
           8: [],
           9: [1],
       },
       {
           0: [4],
           1: [6],
           2: [],
           3: [5, 6, 7],
           4: [0, 6],
           5: [3, 8, 9],
           6: [1, 3, 4, 7],
           7: [3, 6, 8, 9],
           8: [5, 7],
           9: [5, 7],
       },
       {
           0: [1, 3],
           1: [0, 2, 4],
           2: [1, 3, 4],
           3: [0, 2, 4],
           4: [1, 2, 3],
       },
   ][index]





def 	a_					( lowerCamelCase	:     dict[int, list[int]]				):
   lowerCAmelCase     =			0
   lowerCAmelCase     =			len(lowerCamelCase				)  # No of vertices in graph
   lowerCAmelCase     =			[0] * n
   lowerCAmelCase     =			[False] * n

   def dfs(lowerCamelCase	:     Tuple	, lowerCamelCase	:     str	, lowerCamelCase	:     Dict	, lowerCamelCase	:     str				):
      lowerCAmelCase     =			True
      lowerCAmelCase     =			id_
      id_ += 1
      for to in graph[at]:
         if to == parent:
            pass
         elif not visited[to]:
            dfs(lowerCamelCase	, lowerCamelCase	, lowerCamelCase	, id_				)
            lowerCAmelCase     =			min(low[at]	, low[to]				)
            if id_ <= low[to]:
               bridges.append((at, to) if at < to else (to, at)				)
         else:
            # This edge is a back edge and cannot be a bridge
            lowerCAmelCase     =			min(low[at]	, low[to]				)

   lowerCAmelCase     =			[]
   for i in range(lowerCamelCase				):
      if not visited[i]:
         dfs(lowerCamelCase	, -1	, lowerCamelCase	, id_				)
   return bridges


if __name__ == "__main__":
       import doctest

       doctest.testmod()





