






"""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 OwlViTImageProcessor, OwlViTProcessor

@require_vision
class 						A_							(      unittest.TestCase  ):







				def     _snake_case					(							self							:						Union[str, Any]	)				->					Optional[int]:
										__magic_name__            =     tempfile.mkdtemp()

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

										__magic_name__            =     os.path.join(self.tmpdirname						,    VOCAB_FILES_NAMES["vocab_file"]	)
										__magic_name__            =     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	)	)

										__magic_name__            =     {
										    "do_resize": True,
										    "size": 2_0,
										    "do_center_crop": True,
										    "crop_size": 1_8,
										    "do_normalize": True,
										    "image_mean": [0.4814_5466, 0.457_8275, 0.4082_1073],
										    "image_std": [0.2686_2954, 0.2613_0258, 0.2757_7711],
										}
										__magic_name__            =     os.path.join(self.tmpdirname						,    __lowerCamelCase	)
										with open(self.image_processor_file						,    "w"						,    encoding="utf-8"	) as fp:
																json.dump(__lowerCamelCase						,    __lowerCamelCase	)







				def     _snake_case					(							self							:						Any						,    **__lowerCamelCase							:						Dict	)				->					int:
										return CLIPTokenizer.from_pretrained(self.tmpdirname						,    pad_token="!"						,    **__lowerCamelCase	)







				def     _snake_case					(							self							:						Union[str, Any]						,    **__lowerCamelCase							:						Optional[Any]	)				->					int:
										return CLIPTokenizerFast.from_pretrained(self.tmpdirname						,    pad_token="!"						,    **__lowerCamelCase	)







				def     _snake_case					(							self							:						Optional[Any]						,    **__lowerCamelCase							:						Optional[Any]	)				->					Optional[int]:
										return OwlViTImageProcessor.from_pretrained(self.tmpdirname						,    **__lowerCamelCase	)







				def     _snake_case					(							self							:						Dict	)				->					List[Any]:
										shutil.rmtree(self.tmpdirname	)







				def     _snake_case					(							self							:						Any	)				->					Any:
										__magic_name__            =     [np.random.randint(2_5_5						,    size=(3, 3_0, 4_0_0)						,    dtype=np.uinta	)]

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

										return image_inputs







				def     _snake_case					(							self							:						List[Any]	)				->					Union[str, Any]:
										__magic_name__            =     self.get_tokenizer()
										__magic_name__            =     self.get_rust_tokenizer()
										__magic_name__            =     self.get_image_processor()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)
										processor_slow.save_pretrained(self.tmpdirname	)
										__magic_name__            =     OwlViTProcessor.from_pretrained(self.tmpdirname						,    use_fast=__lowerCamelCase	)

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)
										processor_fast.save_pretrained(self.tmpdirname	)
										__magic_name__            =     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     _snake_case					(							self							:						Tuple	)				->					Union[str, Any]:
										__magic_name__            =     OwlViTProcessor(tokenizer=self.get_tokenizer()						,    image_processor=self.get_image_processor()	)
										processor.save_pretrained(self.tmpdirname	)

										__magic_name__            =     self.get_tokenizer(bos_token="(BOS)"						,    eos_token="(EOS)"	)
										__magic_name__            =     self.get_image_processor(do_normalize=__lowerCamelCase	)

										__magic_name__            =     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     _snake_case					(							self							:						Optional[Any]	)				->					Dict:
										__magic_name__            =     self.get_image_processor()
										__magic_name__            =     self.get_tokenizer()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)

										__magic_name__            =     self.prepare_image_inputs()

										__magic_name__            =     image_processor(__lowerCamelCase						,    return_tensors="np"	)
										__magic_name__            =     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     _snake_case					(							self							:						List[Any]	)				->					Tuple:
										__magic_name__            =     self.get_image_processor()
										__magic_name__            =     self.get_tokenizer()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)

										__magic_name__            =     "lower newer"

										__magic_name__            =     processor(text=__lowerCamelCase						,    return_tensors="np"	)

										__magic_name__            =     tokenizer(__lowerCamelCase						,    return_tensors="np"	)

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







				def     _snake_case					(							self							:						Any	)				->					int:
										__magic_name__            =     self.get_image_processor()
										__magic_name__            =     self.get_tokenizer()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)

										__magic_name__            =     "lower newer"
										__magic_name__            =     self.prepare_image_inputs()

										__magic_name__            =     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     _snake_case					(							self							:						Dict	)				->					Optional[int]:
										__magic_name__            =     "google/owlvit-base-patch32"
										__magic_name__            =     OwlViTProcessor.from_pretrained(__lowerCamelCase	)

										__magic_name__            =     ["cat", "nasa badge"]
										__magic_name__            =     processor(text=__lowerCamelCase	)

										__magic_name__            =     1_6
										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     _snake_case					(							self							:						str	)				->					Any:
										__magic_name__            =     "google/owlvit-base-patch32"
										__magic_name__            =     OwlViTProcessor.from_pretrained(__lowerCamelCase	)

										__magic_name__            =     [["cat", "nasa badge"], ["person"]]
										__magic_name__            =     processor(text=__lowerCamelCase	)

										__magic_name__            =     1_6
										__magic_name__            =     len(__lowerCamelCase	)
										__magic_name__            =     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     _snake_case					(							self							:						Union[str, Any]	)				->					int:
										__magic_name__            =     "google/owlvit-base-patch32"
										__magic_name__            =     OwlViTProcessor.from_pretrained(__lowerCamelCase	)

										__magic_name__            =     ["cat", "nasa badge"]
										__magic_name__            =     processor(text=__lowerCamelCase	)

										__magic_name__            =     1_6
										__magic_name__            =     inputs["input_ids"]
										__magic_name__            =     [
										    [4_9_4_0_6, 2_3_6_8, 4_9_4_0_7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
										    [4_9_4_0_6, 6_8_4_1, 1_1_3_0_1, 4_9_4_0_7, 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     _snake_case					(							self							:						List[Any]	)				->					Optional[int]:
										__magic_name__            =     self.get_image_processor()
										__magic_name__            =     self.get_tokenizer()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)

										__magic_name__            =     self.prepare_image_inputs()
										__magic_name__            =     self.prepare_image_inputs()

										__magic_name__            =     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     _snake_case					(							self							:						Dict	)				->					List[str]:
										__magic_name__            =     self.get_image_processor()
										__magic_name__            =     self.get_tokenizer()

										__magic_name__            =     OwlViTProcessor(tokenizer=__lowerCamelCase						,    image_processor=__lowerCamelCase	)

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

										__magic_name__            =     processor.batch_decode(__lowerCamelCase	)
										__magic_name__            =     tokenizer.batch_decode(__lowerCamelCase	)

										self.assertListEqual(__lowerCamelCase						,    __lowerCamelCase	)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:list   ):

						'''simple docstring'''






						__magic_name__            =     len(__lowerCamelCase   )
						for i in range(1 ,						__lowerCamelCase   ):
												__magic_name__            =     collection[i]
												__magic_name__            =     0
												__magic_name__            =     i - 1

												while low <= high:
																		__magic_name__            =     (low + high) // 2
																		if val < collection[mid]:
																								__magic_name__            =     mid - 1
																		else:
																								__magic_name__            =     mid + 1
												for j in range(__lowerCamelCase ,						__lowerCamelCase ,						-1   ):
																		__magic_name__            =     collection[j - 1]
												__magic_name__            =     val
						return collection


if __name__ == "__main__":
			lowercase    			=       input('''Enter numbers separated by a comma:\n''').strip()
			lowercase    			=       [int(item) for item in user_input.split(''',''')]
			print(binary_insertion_sort(unsorted))



