



"""simple docstring"""





import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import (
      AutoProcessor,
      BertTokenizerFast,
      BlipImageProcessor,
      GPTaTokenizer,
      InstructBlipProcessor,
      PreTrainedTokenizerFast,
  )
@require_vision
class 				lowercase__       (   unittest.TestCase				):







       '''simple docstring'''


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


             '''simple docstring'''




             UpperCAmelCase_      			=							tempfile.mkdtemp()

             UpperCAmelCase_      			=							BlipImageProcessor()
             UpperCAmelCase_      			=							GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model"   )
             UpperCAmelCase_      			=							BertTokenizerFast.from_pretrained("hf-internal-testing/tiny-random-bert"   )

             UpperCAmelCase_      			=							InstructBlipProcessor(_UpperCAmelCase		,    _UpperCAmelCase		,    _UpperCAmelCase   )

             processor.save_pretrained(self.tmpdirname   )



       def 					lowercase__    (							self      :  Any		,    **_UpperCAmelCase      :  Optional[int]   )			->						Optional[Any]:


             '''simple docstring'''




             return AutoProcessor.from_pretrained(self.tmpdirname		,    **_UpperCAmelCase   ).tokenizer



       def 					lowercase__    (							self      :  Any		,    **_UpperCAmelCase      :  Union[str, Any]   )			->						Union[str, Any]:


             '''simple docstring'''




             return AutoProcessor.from_pretrained(self.tmpdirname		,    **_UpperCAmelCase   ).image_processor



       def 					lowercase__    (							self      :  Tuple		,    **_UpperCAmelCase      :  List[Any]   )			->						Union[str, Any]:


             '''simple docstring'''




             return AutoProcessor.from_pretrained(self.tmpdirname		,    **_UpperCAmelCase   ).qformer_tokenizer



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


             '''simple docstring'''




             shutil.rmtree(self.tmpdirname   )



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


             '''simple docstring'''




             UpperCAmelCase_      			=							[np.random.randint(255		,    size=(3, 30, 400)		,    dtype=np.uinta   )]

             UpperCAmelCase_      			=							[Image.fromarray(np.moveaxis(_UpperCAmelCase		,    0		,    -1   )   ) for x in image_inputs]

             return image_inputs



       def 					lowercase__    (							self      :  List[Any]   )			->						Union[str, Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=self.get_tokenizer()		,    image_processor=self.get_image_processor()		,    qformer_tokenizer=self.get_qformer_tokenizer()		,    )
             processor.save_pretrained(self.tmpdirname   )

             UpperCAmelCase_      			=							self.get_tokenizer(bos_token="(BOS)"		,    eos_token="(EOS)"   )
             UpperCAmelCase_      			=							self.get_image_processor(do_normalize=_UpperCAmelCase		,    padding_value=1.0   )

             UpperCAmelCase_      			=							InstructBlipProcessor.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   )
             self.assertIsInstance(processor.qformer_tokenizer		,    _UpperCAmelCase   )



       def 					lowercase__    (							self      :  Optional[int]   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_image_processor()
             UpperCAmelCase_      			=							self.get_tokenizer()
             UpperCAmelCase_      			=							self.get_qformer_tokenizer()

             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=_UpperCAmelCase		,    image_processor=_UpperCAmelCase		,    qformer_tokenizer=_UpperCAmelCase   )

             UpperCAmelCase_      			=							self.prepare_image_inputs()

             UpperCAmelCase_      			=							image_processor(_UpperCAmelCase		,    return_tensors="np"   )
             UpperCAmelCase_      			=							processor(images=_UpperCAmelCase		,    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 					lowercase__    (							self      :  int   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_image_processor()
             UpperCAmelCase_      			=							self.get_tokenizer()
             UpperCAmelCase_      			=							self.get_qformer_tokenizer()

             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=_UpperCAmelCase		,    image_processor=_UpperCAmelCase		,    qformer_tokenizer=_UpperCAmelCase   )

             UpperCAmelCase_      			=							"lower newer"

             UpperCAmelCase_      			=							processor(text=_UpperCAmelCase   )

             UpperCAmelCase_      			=							tokenizer(_UpperCAmelCase		,    return_token_type_ids=_UpperCAmelCase   )
             UpperCAmelCase_      			=							qformer_tokenizer(_UpperCAmelCase		,    return_token_type_ids=_UpperCAmelCase   )

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

             for key in encoded_tokens_qformer.keys():
                   self.assertListEqual(encoded_tokens_qformer[key]		,    encoded_processor["qformer_" + key]   )



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


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_image_processor()
             UpperCAmelCase_      			=							self.get_tokenizer()
             UpperCAmelCase_      			=							self.get_qformer_tokenizer()

             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=_UpperCAmelCase		,    image_processor=_UpperCAmelCase		,    qformer_tokenizer=_UpperCAmelCase   )

             UpperCAmelCase_      			=							"lower newer"
             UpperCAmelCase_      			=							self.prepare_image_inputs()

             UpperCAmelCase_      			=							processor(text=_UpperCAmelCase		,    images=_UpperCAmelCase   )

             self.assertListEqual(
                 list(inputs.keys()   )		,    ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]		,    )

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



       def 					lowercase__    (							self      :  int   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_image_processor()
             UpperCAmelCase_      			=							self.get_tokenizer()
             UpperCAmelCase_      			=							self.get_qformer_tokenizer()

             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=_UpperCAmelCase		,    image_processor=_UpperCAmelCase		,    qformer_tokenizer=_UpperCAmelCase   )

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

             UpperCAmelCase_      			=							processor.batch_decode(_UpperCAmelCase   )
             UpperCAmelCase_      			=							tokenizer.batch_decode(_UpperCAmelCase   )

             self.assertListEqual(_UpperCAmelCase		,    _UpperCAmelCase   )







       def 					lowercase__    (							self      :  Dict   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_image_processor()
             UpperCAmelCase_      			=							self.get_tokenizer()
             UpperCAmelCase_      			=							self.get_qformer_tokenizer()

             UpperCAmelCase_      			=							InstructBlipProcessor(
                 tokenizer=_UpperCAmelCase		,    image_processor=_UpperCAmelCase		,    qformer_tokenizer=_UpperCAmelCase   )

             UpperCAmelCase_      			=							"lower newer"
             UpperCAmelCase_      			=							self.prepare_image_inputs()

             UpperCAmelCase_      			=							processor(text=_UpperCAmelCase		,    images=_UpperCAmelCase   )

             self.assertListEqual(
                 list(inputs.keys()   )		,    ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]		,    )









"""simple docstring"""





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					42
       UpperCamelCase						=					None
       UpperCamelCase						=					None



lowerCamelCase       	=						namedtuple("""CoinsDistribResult""", """moves excess""")
def        a__     (				lowerCAmelCase__				):

      if root is None:
            return 0

      # Validation
      def count_nodes(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left				) + count_nodes(node.right				) + 1

      def count_coins(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_coins(node.left				) + count_coins(node.right				) + node.data

      if count_nodes(lowerCAmelCase__				) != count_coins(lowerCAmelCase__				):
            raise ValueError("The nodes number should be same as the number of coins"				)

      # Main calculation
      def get_distrib(lowerCAmelCase__				) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0     ,      1				)

            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.left				)
            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.right				)

            UpperCAmelCase_      			=							1 - left_distrib_excess
            UpperCAmelCase_      			=							1 - right_distrib_excess

            UpperCAmelCase_      			=							(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowerCAmelCase__				)
                + abs(lowerCAmelCase__				)
            )
            UpperCAmelCase_      			=							node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowerCAmelCase__     ,      lowerCAmelCase__				)

      return get_distrib(lowerCAmelCase__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




