
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch


if is_vision_available():
					from transformers import TvltImageProcessor

if is_speech_available():
					from transformers import TvltFeatureExtractor

from transformers import TvltProcessor







@require_torch
class      A__							(     unittest.TestCase	):






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






							'''simple docstring'''







							lowerCAmelCase__      :      int         =		'ZinengTang/tvlt-base'
							lowerCAmelCase__      :      List[Any]         =		tempfile.mkdtemp()






				def 							_lowerCamelCase		(						self					:      Any    ,     **a					:      Tuple   ):






							'''simple docstring'''







							return TvltImageProcessor.from_pretrained(self.checkpoint    ,     **_lowerCamelCase   )






				def 							_lowerCamelCase		(						self					:      List[Any]    ,     **a					:      Tuple   ):






							'''simple docstring'''







							return TvltFeatureExtractor.from_pretrained(self.checkpoint    ,     **_lowerCamelCase   )






				def 							_lowerCamelCase		(						self					:      List[Any]   ):






							'''simple docstring'''







							shutil.rmtree(self.tmpdirname   )






				def 							_lowerCamelCase		(						self					:      List[Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Any         =		self.get_image_processor()
							lowerCAmelCase__      :      Any         =		self.get_feature_extractor()

							lowerCAmelCase__      :      Any         =		TvltProcessor(image_processor=_lowerCamelCase    ,     feature_extractor=_lowerCamelCase   )
							processor.save_pretrained(self.tmpdirname   )
							lowerCAmelCase__      :      int         =		TvltProcessor.from_pretrained(self.tmpdirname   )

							self.assertIsInstance(processor.feature_extractor    ,     _lowerCamelCase   )
							self.assertIsInstance(processor.image_processor    ,     _lowerCamelCase   )






				def 							_lowerCamelCase		(						self					:      List[str]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Union[str, Any]         =		self.get_image_processor()
							lowerCAmelCase__      :      List[Any]         =		self.get_feature_extractor()

							lowerCAmelCase__      :      Optional[Any]         =		TvltProcessor(image_processor=_lowerCamelCase    ,     feature_extractor=_lowerCamelCase   )

							lowerCAmelCase__      :      Any         =		np.ones([12_000]   )

							lowerCAmelCase__      :      Union[str, Any]         =		feature_extractor(_lowerCamelCase    ,     return_tensors='np'   )
							lowerCAmelCase__      :      Union[str, Any]         =		processor(audio=_lowerCamelCase    ,     return_tensors='np'   )

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






				def 							_lowerCamelCase		(						self					:      Any   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[str]         =		self.get_image_processor()
							lowerCAmelCase__      :      Optional[int]         =		self.get_feature_extractor()

							lowerCAmelCase__      :      str         =		TvltProcessor(image_processor=_lowerCamelCase    ,     feature_extractor=_lowerCamelCase   )

							lowerCAmelCase__      :      int         =		np.ones([3, 224, 224]   )

							lowerCAmelCase__      :      Tuple         =		image_processor(_lowerCamelCase    ,     return_tensors='np'   )
							lowerCAmelCase__      :      Optional[int]         =		processor(images=_lowerCamelCase    ,     return_tensors='np'   )

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






				def 							_lowerCamelCase		(						self					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[str]         =		self.get_image_processor()
							lowerCAmelCase__      :      Optional[Any]         =		self.get_feature_extractor()

							lowerCAmelCase__      :      int         =		TvltProcessor(image_processor=_lowerCamelCase    ,     feature_extractor=_lowerCamelCase   )

							lowerCAmelCase__      :      str         =		np.ones([12_000]   )
							lowerCAmelCase__      :      Any         =		np.ones([3, 224, 224]   )

							lowerCAmelCase__      :      Tuple         =		processor(audio=_lowerCamelCase    ,     images=_lowerCamelCase   )

							self.assertListEqual(list(inputs.keys()   )    ,     ['audio_values', 'audio_mask', 'pixel_values', 'pixel_mask']   )

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






				def 							_lowerCamelCase		(						self					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[str]         =		self.get_image_processor()
							lowerCAmelCase__      :      int         =		self.get_feature_extractor()

							lowerCAmelCase__      :      List[Any]         =		TvltProcessor(image_processor=_lowerCamelCase    ,     feature_extractor=_lowerCamelCase   )

							self.assertListEqual(
							    processor.model_input_names    ,     image_processor.model_input_names + feature_extractor.model_input_names    ,     msg='`processor` and `image_processor`+`feature_extractor` model input names do not match'    ,     )

"""simple docstring"""



def 					_UpperCAmelCase      ( __lowerCamelCase   :       list ,					__lowerCamelCase   :       int = 0		)     ->					list:
  _snake_case					     =       length or len(__lowerCamelCase		)
  _snake_case					     =       False
  for i in range(length - 1		):
    if list_data[i] > list_data[i + 1]:
      _snake_case     ,					_snake_case					     =       list_data[i + 1], list_data[i]
      _snake_case					     =       True

  return list_data if not swapped else bubble_sort(__lowerCamelCase ,					length - 1		)


if __name__ == "__main__":
 import doctest

 doctest.testmod()



