






"""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      UpperCamelCase		(unittest.TestCase     ):






						def      __snake_case      (		self  :str				)      ->Optional[int]:
										lowercase    :      Optional[int]       = tempfile.mkdtemp()

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

										lowercase    :      List[str]       = os.path.join(self.tmpdirname			, VOCAB_FILES_NAMES["""vocab_file"""]				)
										lowercase    :      Optional[int]       = 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(__magic_name__				) + """\n"""				)
										with open(self.merges_file			, """w"""			, encoding="""utf-8"""				) as fp:
														fp.write("""\n""".join(__magic_name__				)				)

										lowercase    :      Optional[int]       = {
										    """do_resize""": True,
										    """size""": 20,
										    """do_center_crop""": True,
										    """crop_size""": 18,
										    """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],
										}
										lowercase    :      int       = os.path.join(self.tmpdirname			, __magic_name__				)
										with open(self.image_processor_file			, """w"""			, encoding="""utf-8"""				) as fp:
														json.dump(__magic_name__			, __magic_name__				)






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






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






						def      __snake_case      (		self  :Optional[int]			, **__magic_name__  :List[Any]				)      ->Optional[Any]:
										return OwlViTImageProcessor.from_pretrained(self.tmpdirname			, **__magic_name__				)






						def      __snake_case      (		self  :Any				)      ->Optional[Any]:
										shutil.rmtree(self.tmpdirname				)






						def      __snake_case      (		self  :List[str]				)      ->Tuple:
										lowercase    :      Any       = [np.random.randint(255			, size=(3, 30, 400)			, dtype=np.uinta				)]

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

										return image_inputs






						def      __snake_case      (		self  :List[str]				)      ->Optional[Any]:
										lowercase    :      Tuple       = self.get_tokenizer()
										lowercase    :      Optional[int]       = self.get_rust_tokenizer()
										lowercase    :      Optional[Any]       = self.get_image_processor()

										lowercase    :      Any       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)
										processor_slow.save_pretrained(self.tmpdirname				)
										lowercase    :      str       = OwlViTProcessor.from_pretrained(self.tmpdirname			, use_fast=__magic_name__				)

										lowercase    :      int       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)
										processor_fast.save_pretrained(self.tmpdirname				)
										lowercase    :      int       = 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			, __magic_name__				)
										self.assertIsInstance(processor_fast.tokenizer			, __magic_name__				)

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






						def      __snake_case      (		self  :Any				)      ->List[str]:
										lowercase    :      str       = OwlViTProcessor(tokenizer=self.get_tokenizer()			, image_processor=self.get_image_processor()				)
										processor.save_pretrained(self.tmpdirname				)

										lowercase    :      Any       = self.get_tokenizer(bos_token="""(BOS)"""			, eos_token="""(EOS)"""				)
										lowercase    :      List[Any]       = self.get_image_processor(do_normalize=__magic_name__				)

										lowercase    :      Optional[int]       = OwlViTProcessor.from_pretrained(
										    self.tmpdirname			, bos_token="""(BOS)"""			, eos_token="""(EOS)"""			, do_normalize=__magic_name__				)

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

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






						def      __snake_case      (		self  :List[Any]				)      ->Union[str, Any]:
										lowercase    :      Tuple       = self.get_image_processor()
										lowercase    :      Dict       = self.get_tokenizer()

										lowercase    :      Any       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)

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

										lowercase    :      Union[str, Any]       = image_processor(__magic_name__			, return_tensors="""np"""				)
										lowercase    :      Any       = processor(images=__magic_name__			, 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  :Optional[int]				)      ->Optional[int]:
										lowercase    :      Optional[int]       = self.get_image_processor()
										lowercase    :      Optional[int]       = self.get_tokenizer()

										lowercase    :      Tuple       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)

										lowercase    :      Any       = """lower newer"""

										lowercase    :      int       = processor(text=__magic_name__			, return_tensors="""np"""				)

										lowercase    :      Union[str, Any]       = tokenizer(__magic_name__			, 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  :List[Any]				)      ->Union[str, Any]:
										lowercase    :      Union[str, Any]       = self.get_image_processor()
										lowercase    :      str       = self.get_tokenizer()

										lowercase    :      Union[str, Any]       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)

										lowercase    :      Tuple       = """lower newer"""
										lowercase    :      str       = self.prepare_image_inputs()

										lowercase    :      int       = processor(text=__magic_name__			, images=__magic_name__				)

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

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






						def      __snake_case      (		self  :Optional[int]				)      ->str:
										lowercase    :      Union[str, Any]       = """google/owlvit-base-patch32"""
										lowercase    :      Union[str, Any]       = OwlViTProcessor.from_pretrained(__magic_name__				)

										lowercase    :      List[Any]       = ["""cat""", """nasa badge"""]
										lowercase    :      Union[str, Any]       = processor(text=__magic_name__				)

										lowercase    :      List[str]       = 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(__magic_name__				):
														processor()






						def      __snake_case      (		self  :Optional[Any]				)      ->str:
										lowercase    :      List[str]       = """google/owlvit-base-patch32"""
										lowercase    :      Tuple       = OwlViTProcessor.from_pretrained(__magic_name__				)

										lowercase    :      Union[str, Any]       = [["""cat""", """nasa badge"""], ["""person"""]]
										lowercase    :      Optional[Any]       = processor(text=__magic_name__				)

										lowercase    :      Optional[Any]       = 16
										lowercase    :      Tuple       = len(__magic_name__				)
										lowercase    :      List[Any]       = max([len(__magic_name__				) 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(__magic_name__				):
														processor()






						def      __snake_case      (		self  :Tuple				)      ->Any:
										lowercase    :      int       = """google/owlvit-base-patch32"""
										lowercase    :      str       = OwlViTProcessor.from_pretrained(__magic_name__				)

										lowercase    :      Optional[Any]       = ["""cat""", """nasa badge"""]
										lowercase    :      Optional[Any]       = processor(text=__magic_name__				)

										lowercase    :      Optional[Any]       = 16
										lowercase    :      Optional[Any]       = inputs["""input_ids"""]
										lowercase    :      List[Any]       = [
										    [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      __snake_case      (		self  :Any				)      ->List[Any]:
										lowercase    :      Any       = self.get_image_processor()
										lowercase    :      Dict       = self.get_tokenizer()

										lowercase    :      str       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)

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

										lowercase    :      Dict       = processor(images=__magic_name__			, query_images=__magic_name__				)

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

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






						def      __snake_case      (		self  :Any				)      ->Optional[Any]:
										lowercase    :      int       = self.get_image_processor()
										lowercase    :      Optional[int]       = self.get_tokenizer()

										lowercase    :      int       = OwlViTProcessor(tokenizer=__magic_name__			, image_processor=__magic_name__				)

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

										lowercase    :      Tuple       = processor.batch_decode(__magic_name__				)
										lowercase    :      int       = tokenizer.batch_decode(__magic_name__				)

										self.assertListEqual(__magic_name__			, __magic_name__				)








"""simple docstring"""







import math
import random


def      UpperCamelCase       ( _A  ,				_A = False )     ->       float:
				if deriv:
								return value * (1 - value)
				return 1 / (1 + math.exp(-value ))


# Initial Value
_lowerCAmelCase            =	0.02


def      UpperCamelCase       ( _A  ,				_A )     ->       float:
				lowercase    :      Any       = float(2 * (random.randint(1  ,				100 )) - 1 )

				for _ in range(_A ):
								# Forward propagation
								lowercase    :      Dict       = sigmoid_function(INITIAL_VALUE * weight )
								# How much did we miss?
								lowercase    :      Any       = (expected / 100) - layer_a
								# Error delta
								lowercase    :      Dict       = layer_1_error * sigmoid_function(_A  ,				_A )
								# Update weight
								weight += INITIAL_VALUE * layer_1_delta

				return layer_a * 100


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				_lowerCAmelCase            =	int(input('Expected value: '))
				_lowerCAmelCase            =	int(input('Number of propagations: '))
				print(forward_propagation(expected, number_propagations))
