
'''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 CLIPSegProcessor, ViTImageProcessor






@require_vision
class  lowerCAmelCase__   (  unittest.TestCase     ):






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Optional[int]													=       tempfile.mkdtemp()

											# fmt: off
											lowercase_	:     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
											lowercase_	:     Dict													=       dict(zip(SCREAMING_SNAKE_CASE_				,							range(len(SCREAMING_SNAKE_CASE_		)		)		)		)
											lowercase_	:     List[Any]													=       ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
											lowercase_	:     Tuple													=       {'unk_token': '<unk>'}

											lowercase_	:     Tuple													=       os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES['''vocab_file''']		)
											lowercase_	:     Optional[Any]													=       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_		)		)

											lowercase_	:     str													=       {
											    'do_resize': True,
											    'size': 20,
											    'do_center_crop': True,
											    'crop_size': 18,
											    '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],
											}
											lowercase_	:     Optional[Any]													=       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 	_snake_case    (   self				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return CLIPTokenizer.from_pretrained(self.tmpdirname				,							**SCREAMING_SNAKE_CASE_		)






					def 	_snake_case    (   self				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,							**SCREAMING_SNAKE_CASE_		)






					def 	_snake_case    (   self				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





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






					def 	_snake_case    (   self		):


											"""simple docstring"""





											shutil.rmtree(self.tmpdirname		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     int													=       [np.random.randint(2_55				,							size=(3, 30, 4_00)				,							dtype=np.uinta		)]

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

											return image_inputs






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     str													=       self.get_tokenizer()
											lowercase_	:     str													=       self.get_rust_tokenizer()
											lowercase_	:     Any													=       self.get_image_processor()

											lowercase_	:     Optional[Any]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)
											processor_slow.save_pretrained(self.tmpdirname		)
											lowercase_	:     str													=       CLIPSegProcessor.from_pretrained(self.tmpdirname				,							use_fast=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     Optional[int]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)
											processor_fast.save_pretrained(self.tmpdirname		)
											lowercase_	:     List[Any]													=       CLIPSegProcessor.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 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Optional[Any]													=       CLIPSegProcessor(tokenizer=self.get_tokenizer()				,							image_processor=self.get_image_processor()		)
											processor.save_pretrained(self.tmpdirname		)

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

											lowercase_	:     Optional[int]													=       CLIPSegProcessor.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 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Dict													=       self.get_image_processor()
											lowercase_	:     Optional[int]													=       self.get_tokenizer()

											lowercase_	:     Optional[int]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     Optional[Any]													=       self.prepare_image_inputs()

											lowercase_	:     Any													=       image_processor(SCREAMING_SNAKE_CASE_				,							return_tensors='''np'''		)
											lowercase_	:     int													=       processor(images=SCREAMING_SNAKE_CASE_				,							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		):


											"""simple docstring"""





											lowercase_	:     Optional[Any]													=       self.get_image_processor()
											lowercase_	:     Any													=       self.get_tokenizer()

											lowercase_	:     Tuple													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     str													=       'lower newer'

											lowercase_	:     Tuple													=       processor(text=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     List[Any]													=       tokenizer(SCREAMING_SNAKE_CASE_		)

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






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Tuple													=       self.get_image_processor()
											lowercase_	:     Optional[Any]													=       self.get_tokenizer()

											lowercase_	:     List[str]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)

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

											lowercase_	:     Tuple													=       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 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     List[Any]													=       self.get_image_processor()
											lowercase_	:     Optional[int]													=       self.get_tokenizer()

											lowercase_	:     Optional[int]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     List[Any]													=       self.prepare_image_inputs()
											lowercase_	:     Any													=       self.prepare_image_inputs()

											lowercase_	:     Tuple													=       processor(images=SCREAMING_SNAKE_CASE_				,							visual_prompt=SCREAMING_SNAKE_CASE_		)

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

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






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     int													=       self.get_image_processor()
											lowercase_	:     List[Any]													=       self.get_tokenizer()

											lowercase_	:     List[str]													=       CLIPSegProcessor(tokenizer=SCREAMING_SNAKE_CASE_				,							image_processor=SCREAMING_SNAKE_CASE_		)

											lowercase_	:     Union[str, Any]													=       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

											lowercase_	:     List[str]													=       processor.batch_decode(SCREAMING_SNAKE_CASE_		)
											lowercase_	:     Union[str, Any]													=       tokenizer.batch_decode(SCREAMING_SNAKE_CASE_		)

											self.assertListEqual(SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_		)







'''simple docstring'''



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				List[Any]							)     ->		str:
     __lowerCamelCase   :	Tuple								=		0
     __lowerCamelCase   :	Optional[int]								=		len(UpperCAmelCase_							)

     for i in range(n - 1							):
          for j in range(i + 1      ,    UpperCAmelCase_							):
               if arr[i] > arr[j]:
                    num_inversions += 1

     return num_inversions



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				str							)     ->		Optional[int]:
     if len(UpperCAmelCase_							) <= 1:
          return arr, 0
     __lowerCamelCase   :	str								=		len(UpperCAmelCase_							) // 2
     __lowerCamelCase   :	List[Any]								=		arr[0:mid]
     __lowerCamelCase   :	List[str]								=		arr[mid:]

     __lowerCamelCase				,       __lowerCamelCase   :	int								=		count_inversions_recursive(UpperCAmelCase_							)
     __lowerCamelCase				,       __lowerCamelCase   :	Optional[Any]								=		count_inversions_recursive(UpperCAmelCase_							)
     __lowerCamelCase				,       __lowerCamelCase   :	Any								=		_count_cross_inversions(UpperCAmelCase_      ,    UpperCAmelCase_							)

     __lowerCamelCase   :	Optional[int]								=		inversion_p + inversions_q + cross_inversions
     return c, num_inversions



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				List[Any]      ,    UpperCAmelCase_    :				List[str]							)     ->		Optional[Any]:
     __lowerCamelCase   :	List[str]								=		[]
     __lowerCamelCase   :	Optional[int]								=		0
     while i < len(UpperCAmelCase_							) and j < len(UpperCAmelCase_							):
          if p[i] > q[j]:
               # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
               # These are all inversions. The claim emerges from the
               # property that P is sorted.
               num_inversion += len(UpperCAmelCase_							) - i
               r.append(q[j]							)
               j += 1
          else:
               r.append(p[i]							)
               i += 1

     if i < len(UpperCAmelCase_							):
          r.extend(p[i:]							)
     else:
          r.extend(q[j:]							)

     return r, num_inversion



def 			UpperCAmelCase__					(	)     ->		List[str]:
     __lowerCamelCase   :	Any								=		[10, 2, 1, 5, 5, 2, 11]

     # this arr has 8 inversions:
     # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

     __lowerCamelCase   :	Optional[Any]								=		count_inversions_bf(UpperCAmelCase_							)
     __lowerCamelCase				,       __lowerCamelCase   :	Dict								=		count_inversions_recursive(UpperCAmelCase_							)

     assert num_inversions_bf == num_inversions_recursive == 8

     print('number of inversions = '      ,    UpperCAmelCase_							)

     # testing an array with zero inversion (a sorted arr_1)

     arr_a.sort()
     __lowerCamelCase   :	Optional[Any]								=		count_inversions_bf(UpperCAmelCase_							)
     __lowerCamelCase				,       __lowerCamelCase   :	int								=		count_inversions_recursive(UpperCAmelCase_							)

     assert num_inversions_bf == num_inversions_recursive == 0
     print('number of inversions = '      ,    UpperCAmelCase_							)

     # an empty list should also have zero inversions
     __lowerCamelCase   :	Dict								=		[]
     __lowerCamelCase   :	Optional[Any]								=		count_inversions_bf(UpperCAmelCase_							)
     __lowerCamelCase				,       __lowerCamelCase   :	Union[str, Any]								=		count_inversions_recursive(UpperCAmelCase_							)

     assert num_inversions_bf == num_inversions_recursive == 0
     print('number of inversions = '      ,    UpperCAmelCase_							)


if __name__ == "__main__":
      main()






