


'''simple docstring'''



import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 CLIPImageProcessor, CLIPProcessor





@require_vision
class    UpperCAmelCase_  (unittest.TestCase  ):





    """simple docstring"""






    def       lowercase_				(							self	)				->     Dict:
         __lowerCamelCase   :	Optional[int]								=		tempfile.mkdtemp()

         # fmt: off
         __lowerCamelCase   :	Dict								=		['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
         # fmt: on
         __lowerCamelCase   :	Any								=		dict(zip(SCREAMING_SNAKE_CASE_			,     range(len(SCREAMING_SNAKE_CASE_	)	)	)	)
         __lowerCamelCase   :	str								=		['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
         __lowerCamelCase   :	Optional[Any]								=		{'unk_token': '<unk>'}

         __lowerCamelCase   :	int								=		os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['vocab_file']	)
         __lowerCamelCase   :	List[str]								=		os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['merges_file']	)
         with open(self.vocab_file			,     'w'			,     encoding='utf-8'	) as fp:
              fp.write(json.dumps(SCREAMING_SNAKE_CASE_	) + '\n'	)
         with open(self.merges_file			,     'w'			,     encoding='utf-8'	) as fp:
              fp.write('\n'.join(SCREAMING_SNAKE_CASE_	)	)

         __lowerCamelCase   :	Optional[Any]								=		{
             'do_resize': True,
             'size': 20,
             'do_center_crop': True,
             'crop_size': 18,
             'do_normalize': True,
             'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
             'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
         }
         __lowerCamelCase   :	str								=		os.path.join(self.tmpdirname			,     SCREAMING_SNAKE_CASE_	)
         with open(self.image_processor_file			,     'w'			,     encoding='utf-8'	) as fp:
              json.dump(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)







    def       lowercase_				(							self			,     **SCREAMING_SNAKE_CASE_	)				->     Tuple:
         return CLIPTokenizer.from_pretrained(self.tmpdirname			,     **SCREAMING_SNAKE_CASE_	)







    def       lowercase_				(							self			,     **SCREAMING_SNAKE_CASE_	)				->     List[str]:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,     **SCREAMING_SNAKE_CASE_	)







    def       lowercase_				(							self			,     **SCREAMING_SNAKE_CASE_	)				->     List[Any]:
         return CLIPImageProcessor.from_pretrained(self.tmpdirname			,     **SCREAMING_SNAKE_CASE_	)







    def       lowercase_				(							self	)				->     List[str]:
         shutil.rmtree(self.tmpdirname	)







    def       lowercase_				(							self	)				->     Dict:
         __lowerCamelCase   :	List[str]								=		[np.random.randint(2_55			,     size=(3, 30, 4_00)			,     dtype=np.uinta	)]

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

         return image_inputs







    def       lowercase_				(							self	)				->     Tuple:
         __lowerCamelCase   :	int								=		self.get_tokenizer()
         __lowerCamelCase   :	Optional[Any]								=		self.get_rust_tokenizer()
         __lowerCamelCase   :	Dict								=		self.get_image_processor()

         __lowerCamelCase   :	int								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)
         processor_slow.save_pretrained(self.tmpdirname	)
         __lowerCamelCase   :	Optional[Any]								=		CLIPProcessor.from_pretrained(self.tmpdirname			,     use_fast=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	List[str]								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)
         processor_fast.save_pretrained(self.tmpdirname	)
         __lowerCamelCase   :	Optional[Any]								=		CLIPProcessor.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			,     SCREAMING_SNAKE_CASE_	)
         self.assertIsInstance(processor_fast.tokenizer			,     SCREAMING_SNAKE_CASE_	)

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







    def       lowercase_				(							self	)				->     Tuple:
         __lowerCamelCase   :	Union[str, Any]								=		CLIPProcessor(tokenizer=self.get_tokenizer()			,     image_processor=self.get_image_processor()	)
         processor.save_pretrained(self.tmpdirname	)

         __lowerCamelCase   :	List[Any]								=		self.get_tokenizer(bos_token='(BOS)'			,     eos_token='(EOS)'	)
         __lowerCamelCase   :	Union[str, Any]								=		self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_			,     padding_value=1.0	)

         __lowerCamelCase   :	Optional[Any]								=		CLIPProcessor.from_pretrained(
             self.tmpdirname			,     bos_token='(BOS)'			,     eos_token='(EOS)'			,     do_normalize=SCREAMING_SNAKE_CASE_			,     padding_value=1.0	)

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

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







    def       lowercase_				(							self	)				->     Tuple:
         __lowerCamelCase   :	Dict								=		self.get_image_processor()
         __lowerCamelCase   :	Union[str, Any]								=		self.get_tokenizer()

         __lowerCamelCase   :	Tuple								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	Any								=		self.prepare_image_inputs()

         __lowerCamelCase   :	Tuple								=		image_processor(SCREAMING_SNAKE_CASE_			,     return_tensors='np'	)
         __lowerCamelCase   :	Any								=		processor(images=SCREAMING_SNAKE_CASE_			,     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       lowercase_				(							self	)				->     str:
         __lowerCamelCase   :	Tuple								=		self.get_image_processor()
         __lowerCamelCase   :	str								=		self.get_tokenizer()

         __lowerCamelCase   :	Optional[Any]								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	Tuple								=		'lower newer'

         __lowerCamelCase   :	str								=		processor(text=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	Optional[Any]								=		tokenizer(SCREAMING_SNAKE_CASE_	)

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







    def       lowercase_				(							self	)				->     Dict:
         __lowerCamelCase   :	int								=		self.get_image_processor()
         __lowerCamelCase   :	str								=		self.get_tokenizer()

         __lowerCamelCase   :	Tuple								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)

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

         __lowerCamelCase   :	Any								=		processor(text=SCREAMING_SNAKE_CASE_			,     images=SCREAMING_SNAKE_CASE_	)

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

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







    def       lowercase_				(							self	)				->     Union[str, Any]:
         __lowerCamelCase   :	Any								=		self.get_image_processor()
         __lowerCamelCase   :	Optional[Any]								=		self.get_tokenizer()

         __lowerCamelCase   :	Dict								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)

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

         __lowerCamelCase   :	Optional[int]								=		processor.batch_decode(SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	int								=		tokenizer.batch_decode(SCREAMING_SNAKE_CASE_	)

         self.assertListEqual(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)







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

         __lowerCamelCase   :	int								=		CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_			,     image_processor=SCREAMING_SNAKE_CASE_	)

         __lowerCamelCase   :	Dict								=		'lower newer'
         __lowerCamelCase   :	Optional[Any]								=		self.prepare_image_inputs()

         __lowerCamelCase   :	Dict								=		processor(text=SCREAMING_SNAKE_CASE_			,     images=SCREAMING_SNAKE_CASE_	)

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










'''simple docstring'''



A__		:					Any												=  8.3_1_4_4_6_2  # Unit - J mol-1 K-1



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				float      ,    UpperCAmelCase_    :				float      ,    UpperCAmelCase_    :				float							)     ->		float:
     if moles < 0 or kelvin < 0 or volume < 0:
          raise ValueError('Invalid inputs. Enter positive value.'							)
     return moles * kelvin * UNIVERSAL_GAS_CONSTANT / volume



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				float      ,    UpperCAmelCase_    :				float      ,    UpperCAmelCase_    :				float							)     ->		float:
     if moles < 0 or kelvin < 0 or pressure < 0:
          raise ValueError('Invalid inputs. Enter positive value.'							)
     return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure


if __name__ == "__main__":
      from doctest import testmod

      testmod()






