

'''simple docstring'''

import json
import os
import shutil
import tempfile
import unittest

import numpy as np

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


if is_vision_available():
       from PIL import Image

       from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor


@require_tokenizers
@require_vision
class 	lowerCAmelCase  (   unittest.TestCase ):







       def       snake_case (				self      :			Tuple   ):







            """simple docstring"""







            __lowercase      		=tempfile.mkdtemp()

            # fmt: off
            __lowercase      		=['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
            # fmt: on
            __lowercase      		=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]   )   )

            __lowercase      		={
                'do_resize': True,
                'size': {'height': 18, 'width': 18},
                'do_normalize': True,
                'image_mean': [0.5, 0.5, 0.5],
                'image_std': [0.5, 0.5, 0.5],
            }
            __lowercase      		=os.path.join(self.tmpdirname    ,   __lowercase   )
            with open(self.image_processor_file    ,   'w'    ,   encoding='utf-8'   ) as fp:
                 json.dump(__lowercase    ,   __lowercase   )







       def       snake_case (				self      :			List[str]    ,   **__lowercase      :			int   ):







            """simple docstring"""







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







       def       snake_case (				self      :			Union[str, Any]    ,   **__lowercase      :			Any   ):







            """simple docstring"""







            return ViTImageProcessor.from_pretrained(self.tmpdirname    ,   **__lowercase   )







       def       snake_case (				self      :			List[Any]   ):







            """simple docstring"""







            shutil.rmtree(self.tmpdirname   )







       def       snake_case (				self      :			Dict   ):







            """simple docstring"""







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

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

            return image_inputs







       def       snake_case (				self      :			Optional[int]   ):







            """simple docstring"""







            __lowercase      		=self.get_tokenizer()
            __lowercase      		=self.get_image_processor()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

            processor.save_pretrained(self.tmpdirname   )
            __lowercase      		=VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname   )

            self.assertEqual(processor.tokenizer.get_vocab()    ,   tokenizer.get_vocab()   )
            self.assertIsInstance(processor.tokenizer    ,   (BertTokenizer, BertTokenizerFast)   )

            self.assertEqual(processor.image_processor.to_json_string()    ,   image_processor.to_json_string()   )
            self.assertIsInstance(processor.image_processor    ,   __lowercase   )







       def       snake_case (				self      :			int   ):







            """simple docstring"""







            __lowercase      		=VisionTextDualEncoderProcessor(
                tokenizer=self.get_tokenizer()    ,   image_processor=self.get_image_processor()   )
            processor.save_pretrained(self.tmpdirname   )

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

            __lowercase      		=VisionTextDualEncoderProcessor.from_pretrained(
                self.tmpdirname    ,   bos_token='(BOS)'    ,   eos_token='(EOS)'    ,   do_normalize=__lowercase    ,   padding_value=1.0   )

            self.assertEqual(processor.tokenizer.get_vocab()    ,   tokenizer_add_kwargs.get_vocab()   )
            self.assertIsInstance(processor.tokenizer    ,   (BertTokenizer, BertTokenizerFast)   )

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







       def       snake_case (				self      :			Dict   ):







            """simple docstring"""







            __lowercase      		=self.get_image_processor()
            __lowercase      		=self.get_tokenizer()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

            __lowercase      		=self.prepare_image_inputs()

            __lowercase      		=image_processor(__lowercase    ,   return_tensors='np'   )
            __lowercase      		=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       snake_case (				self      :			Dict   ):







            """simple docstring"""







            __lowercase      		=self.get_image_processor()
            __lowercase      		=self.get_tokenizer()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

            __lowercase      		='lower newer'

            __lowercase      		=processor(text=__lowercase   )

            __lowercase      		=tokenizer(__lowercase   )

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







       def       snake_case (				self      :			Any   ):







            """simple docstring"""







            __lowercase      		=self.get_image_processor()
            __lowercase      		=self.get_tokenizer()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

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

            __lowercase      		=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 self.assertRaises(__lowercase   ):
                 processor()







       def       snake_case (				self      :			Union[str, Any]   ):







            """simple docstring"""







            __lowercase      		=self.get_image_processor()
            __lowercase      		=self.get_tokenizer()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

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

            __lowercase      		=processor.batch_decode(__lowercase   )
            __lowercase      		=tokenizer.batch_decode(__lowercase   )

            self.assertListEqual(__lowercase    ,   __lowercase   )







       def       snake_case (				self      :			Dict   ):







            """simple docstring"""







            __lowercase      		=self.get_image_processor()
            __lowercase      		=self.get_tokenizer()

            __lowercase      		=VisionTextDualEncoderProcessor(tokenizer=__lowercase    ,   image_processor=__lowercase   )

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

            __lowercase      		=processor(text=__lowercase    ,   images=__lowercase   )

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





'''simple docstring'''

from __future__ import annotations

def 					__UpperCamelCase				(						lowercase__    :	float,       lowercase__    :	float,       lowercase__    :	float			):






     '''simple docstring'''





     if (voltage, current, resistance).count(0			) != 1:
          raise ValueError('One and only one argument must be 0'			)
     if resistance < 0:
          raise ValueError('Resistance cannot be negative'			)
     if voltage == 0:
          return {"voltage": float(current * resistance			)}
     elif current == 0:
          return {"current": voltage / resistance}
     elif resistance == 0:
          return {"resistance": voltage / current}
     else:
          raise ValueError('Exactly one argument must be 0'			)


if __name__ == "__main__":
       import doctest

       doctest.testmod()


