






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 OwlViTImageProcessor, OwlViTProcessor

@require_vision
class     _SCREAMING_SNAKE_CASE       (			unittest.TestCase      ):





	def 						_A (		self				:					List[str]	):
		UpperCamelCase     :int          =	tempfile.mkdtemp()

		# fmt: off
		UpperCamelCase     :str          =	["""""", """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
		UpperCamelCase     :Optional[int]          =	dict(zip(__lowerCamelCase ,  range(len(__lowerCamelCase	)	)	)	)
		UpperCamelCase     :List[str]          =	["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
		UpperCamelCase     :List[str]          =	{"""unk_token""": """<unk>"""}

		UpperCamelCase     :List[Any]          =	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["""vocab_file"""]	)
		UpperCamelCase     :Tuple          =	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(__lowerCamelCase	) + """\n"""	)
		with open(self.merges_file ,  """w""" ,  encoding="""utf-8"""	) as fp:
			fp.write("""\n""".join(__lowerCamelCase	)	)

		UpperCamelCase     :List[Any]          =	{
		    """do_resize""": True,
		    """size""": 20,
		    """do_center_crop""": True,
		    """crop_size""": 18,
		    """do_normalize""": True,
		    """image_mean""": [0.48145466, 0.4578275, 0.40821073],
		    """image_std""": [0.26862954, 0.26130258, 0.27577711],
		}
		UpperCamelCase     :Optional[Any]          =	os.path.join(self.tmpdirname ,  __lowerCamelCase	)
		with open(self.image_processor_file ,  """w""" ,  encoding="""utf-8"""	) as fp:
			json.dump(__lowerCamelCase ,  __lowerCamelCase	)





	def 						_A (		self				:					Dict ,  **__lowerCamelCase				:					Dict	):
		return CLIPTokenizer.from_pretrained(self.tmpdirname ,  pad_token="""!""" ,  **__lowerCamelCase	)





	def 						_A (		self				:					str ,  **__lowerCamelCase				:					Any	):
		return CLIPTokenizerFast.from_pretrained(self.tmpdirname ,  pad_token="""!""" ,  **__lowerCamelCase	)





	def 						_A (		self				:					Tuple ,  **__lowerCamelCase				:					List[Any]	):
		return OwlViTImageProcessor.from_pretrained(self.tmpdirname ,  **__lowerCamelCase	)





	def 						_A (		self				:					str	):
		shutil.rmtree(self.tmpdirname	)





	def 						_A (		self				:					str	):
		UpperCamelCase     :Any          =	[np.random.randint(255 ,  size=(3, 30, 400) ,  dtype=np.uinta	)]

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

		return image_inputs





	def 						_A (		self				:					str	):
		UpperCamelCase     :List[Any]          =	self.get_tokenizer()
		UpperCamelCase     :List[Any]          =	self.get_rust_tokenizer()
		UpperCamelCase     :Tuple          =	self.get_image_processor()

		UpperCamelCase     :Any          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)
		processor_slow.save_pretrained(self.tmpdirname	)
		UpperCamelCase     :int          =	OwlViTProcessor.from_pretrained(self.tmpdirname ,  use_fast=__lowerCamelCase	)

		UpperCamelCase     :Union[str, Any]          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)
		processor_fast.save_pretrained(self.tmpdirname	)
		UpperCamelCase     :str          =	OwlViTProcessor.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 ,  __lowerCamelCase	)
		self.assertIsInstance(processor_fast.tokenizer ,  __lowerCamelCase	)

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





	def 						_A (		self				:					List[str]	):
		UpperCamelCase     :Optional[int]          =	OwlViTProcessor(tokenizer=self.get_tokenizer() ,  image_processor=self.get_image_processor()	)
		processor.save_pretrained(self.tmpdirname	)

		UpperCamelCase     :Any          =	self.get_tokenizer(bos_token="""(BOS)""" ,  eos_token="""(EOS)"""	)
		UpperCamelCase     :str          =	self.get_image_processor(do_normalize=__lowerCamelCase	)

		UpperCamelCase     :str          =	OwlViTProcessor.from_pretrained(
		    self.tmpdirname ,  bos_token="""(BOS)""" ,  eos_token="""(EOS)""" ,  do_normalize=__lowerCamelCase	)

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

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





	def 						_A (		self				:					Union[str, Any]	):
		UpperCamelCase     :Union[str, Any]          =	self.get_image_processor()
		UpperCamelCase     :Dict          =	self.get_tokenizer()

		UpperCamelCase     :Optional[int]          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)

		UpperCamelCase     :Dict          =	self.prepare_image_inputs()

		UpperCamelCase     :List[Any]          =	image_processor(__lowerCamelCase ,  return_tensors="""np"""	)
		UpperCamelCase     :Dict          =	processor(images=__lowerCamelCase ,  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 						_A (		self				:					Dict	):
		UpperCamelCase     :List[Any]          =	self.get_image_processor()
		UpperCamelCase     :str          =	self.get_tokenizer()

		UpperCamelCase     :List[Any]          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)

		UpperCamelCase     :Optional[Any]          =	"""lower newer"""

		UpperCamelCase     :List[str]          =	processor(text=__lowerCamelCase ,  return_tensors="""np"""	)

		UpperCamelCase     :List[str]          =	tokenizer(__lowerCamelCase ,  return_tensors="""np"""	)

		for key in encoded_tok.keys():
			self.assertListEqual(encoded_tok[key][0].tolist() ,  encoded_processor[key][0].tolist()	)





	def 						_A (		self				:					Optional[int]	):
		UpperCamelCase     :List[str]          =	self.get_image_processor()
		UpperCamelCase     :Union[str, Any]          =	self.get_tokenizer()

		UpperCamelCase     :Any          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)

		UpperCamelCase     :Optional[int]          =	"""lower newer"""
		UpperCamelCase     :Tuple          =	self.prepare_image_inputs()

		UpperCamelCase     :int          =	processor(text=__lowerCamelCase ,  images=__lowerCamelCase	)

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

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





	def 						_A (		self				:					Any	):
		UpperCamelCase     :Optional[Any]          =	"""google/owlvit-base-patch32"""
		UpperCamelCase     :List[Any]          =	OwlViTProcessor.from_pretrained(__lowerCamelCase	)

		UpperCamelCase     :Union[str, Any]          =	["""cat""", """nasa badge"""]
		UpperCamelCase     :str          =	processor(text=__lowerCamelCase	)

		UpperCamelCase     :Optional[Any]          =	16
		self.assertListEqual(list(inputs.keys()	) ,  ["""input_ids""", """attention_mask"""]	)
		self.assertEqual(inputs["""input_ids"""].shape ,  (2, seq_length)	)

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





	def 						_A (		self				:					List[str]	):
		UpperCamelCase     :Dict          =	"""google/owlvit-base-patch32"""
		UpperCamelCase     :Dict          =	OwlViTProcessor.from_pretrained(__lowerCamelCase	)

		UpperCamelCase     :Tuple          =	[["""cat""", """nasa badge"""], ["""person"""]]
		UpperCamelCase     :Union[str, Any]          =	processor(text=__lowerCamelCase	)

		UpperCamelCase     :int          =	16
		UpperCamelCase     :int          =	len(__lowerCamelCase	)
		UpperCamelCase     :Dict          =	max([len(__lowerCamelCase	) for texts in input_texts]	)

		self.assertListEqual(list(inputs.keys()	) ,  ["""input_ids""", """attention_mask"""]	)
		self.assertEqual(inputs["""input_ids"""].shape ,  (batch_size * num_max_text_queries, seq_length)	)

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





	def 						_A (		self				:					Any	):
		UpperCamelCase     :Optional[Any]          =	"""google/owlvit-base-patch32"""
		UpperCamelCase     :List[Any]          =	OwlViTProcessor.from_pretrained(__lowerCamelCase	)

		UpperCamelCase     :Optional[int]          =	["""cat""", """nasa badge"""]
		UpperCamelCase     :Union[str, Any]          =	processor(text=__lowerCamelCase	)

		UpperCamelCase     :str          =	16
		UpperCamelCase     :Optional[int]          =	inputs["""input_ids"""]
		UpperCamelCase     :str          =	[
		    [49_406, 2_368, 49_407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
		    [49_406, 6_841, 11_301, 49_407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
		]

		self.assertListEqual(list(inputs.keys()	) ,  ["""input_ids""", """attention_mask"""]	)
		self.assertEqual(inputs["""input_ids"""].shape ,  (2, seq_length)	)
		self.assertListEqual(list(input_ids[0]	) ,  predicted_ids[0]	)
		self.assertListEqual(list(input_ids[1]	) ,  predicted_ids[1]	)





	def 						_A (		self				:					str	):
		UpperCamelCase     :Union[str, Any]          =	self.get_image_processor()
		UpperCamelCase     :str          =	self.get_tokenizer()

		UpperCamelCase     :Optional[int]          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)

		UpperCamelCase     :List[Any]          =	self.prepare_image_inputs()
		UpperCamelCase     :List[str]          =	self.prepare_image_inputs()

		UpperCamelCase     :Union[str, Any]          =	processor(images=__lowerCamelCase ,  query_images=__lowerCamelCase	)

		self.assertListEqual(list(inputs.keys()	) ,  ["""query_pixel_values""", """pixel_values"""]	)

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





	def 						_A (		self				:					Dict	):
		UpperCamelCase     :Dict          =	self.get_image_processor()
		UpperCamelCase     :str          =	self.get_tokenizer()

		UpperCamelCase     :str          =	OwlViTProcessor(tokenizer=__lowerCamelCase ,  image_processor=__lowerCamelCase	)

		UpperCamelCase     :str          =	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

		UpperCamelCase     :Any          =	processor.batch_decode(__lowerCamelCase	)
		UpperCamelCase     :Optional[Any]          =	tokenizer.batch_decode(__lowerCamelCase	)

		self.assertListEqual(__lowerCamelCase ,  __lowerCamelCase	)


"""simple docstring"""




def   __magic_name__	(      __snake_case				:       int     , __snake_case				:       int     , __snake_case				:       int  ) ->				float:
       lowercase    :				List[Any]       		=							(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
       # formula for sum of series
       return total


def   __magic_name__	(      ) ->				int:
       print(sum_of_series(1     , 1     , 10  )  )


if __name__ == "__main__":
   import doctest

   doctest.testmod()


