


'''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    ):





    """simple docstring"""






    def  lowercase_							(				self      )							->	Optional[Any]:
         __lowerCamelCase  :      Tuple														=						tempfile.mkdtemp()

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

         __lowerCamelCase  :      int														=						os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['vocab_file']      )
         __lowerCamelCase  :      List[str]														=						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_      )      )

         __lowerCamelCase  :      Tuple														=						{
             'do_resize': True,
             'size': 20,
             'do_center_crop': True,
             'crop_size': 18,
             'do_normalize': True,
             'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
             'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
         }
         __lowerCamelCase  :      Optional[int]														=						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  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Any:
         return CLIPTokenizer.from_pretrained(self.tmpdirname     ,	pad_token='!'     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	int:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,	pad_token='!'     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Optional[Any]:
         return OwlViTImageProcessor.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	List[str]:
         shutil.rmtree(self.tmpdirname      )







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      List[Any]														=						[np.random.randint(2_55     ,	size=(3, 30, 4_00)     ,	dtype=np.uinta      )]

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

         return image_inputs







    def  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      Optional[Any]														=						self.get_tokenizer()
         __lowerCamelCase  :      int														=						self.get_rust_tokenizer()
         __lowerCamelCase  :      List[Any]														=						self.get_image_processor()

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

         __lowerCamelCase  :      Optional[Any]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )
         processor_fast.save_pretrained(self.tmpdirname      )
         __lowerCamelCase  :      Optional[Any]														=						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     ,	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  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Union[str, Any]														=						OwlViTProcessor(tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()      )
         processor.save_pretrained(self.tmpdirname      )

         __lowerCamelCase  :      Optional[int]														=						self.get_tokenizer(bos_token='(BOS)'     ,	eos_token='(EOS)'      )
         __lowerCamelCase  :      str														=						self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[str]														=						OwlViTProcessor.from_pretrained(
             self.tmpdirname     ,	bos_token='(BOS)'     ,	eos_token='(EOS)'     ,	do_normalize=SCREAMING_SNAKE_CASE_      )

         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  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      str														=						self.get_image_processor()
         __lowerCamelCase  :      str														=						self.get_tokenizer()

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

         __lowerCamelCase  :      Union[str, Any]														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Dict														=						image_processor(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )
         __lowerCamelCase  :      Union[str, Any]														=						processor(images=SCREAMING_SNAKE_CASE_     ,	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  lowercase_							(				self      )							->	int:
         __lowerCamelCase  :      Tuple														=						self.get_image_processor()
         __lowerCamelCase  :      Tuple														=						self.get_tokenizer()

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

         __lowerCamelCase  :      List[Any]														=						'lower newer'

         __lowerCamelCase  :      Optional[int]														=						processor(text=SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )

         __lowerCamelCase  :      Optional[Any]														=						tokenizer(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )

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







    def  lowercase_							(				self      )							->	List[Any]:
         __lowerCamelCase  :      Optional[int]														=						self.get_image_processor()
         __lowerCamelCase  :      List[Any]														=						self.get_tokenizer()

         __lowerCamelCase  :      int														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Dict														=						'lower newer'
         __lowerCamelCase  :      Dict														=						self.prepare_image_inputs()

         __lowerCamelCase  :      int														=						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  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      int														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      Any														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Tuple														=						['cat', 'nasa badge']
         __lowerCamelCase  :      Optional[Any]														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Dict														=						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(SCREAMING_SNAKE_CASE_      ):
              processor()







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Tuple														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      List[str]														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						[['cat', 'nasa badge'], ['person']]
         __lowerCamelCase  :      int														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						16
         __lowerCamelCase  :      Optional[int]														=						len(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						max([len(SCREAMING_SNAKE_CASE_      ) 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(SCREAMING_SNAKE_CASE_      ):
              processor()







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      List[Any]														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      Optional[Any]														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Tuple														=						['cat', 'nasa badge']
         __lowerCamelCase  :      int														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						16
         __lowerCamelCase  :      Union[str, Any]														=						inputs['input_ids']
         __lowerCamelCase  :      Any														=						[
             [4_94_06, 23_68, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [4_94_06, 68_41, 1_13_01, 4_94_07, 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  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      int														=						self.get_image_processor()
         __lowerCamelCase  :      List[str]														=						self.get_tokenizer()

         __lowerCamelCase  :      Union[str, Any]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						self.prepare_image_inputs()
         __lowerCamelCase  :      Tuple														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Optional[Any]														=						processor(images=SCREAMING_SNAKE_CASE_     ,	query_images=SCREAMING_SNAKE_CASE_      )

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

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







    def  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      Union[str, Any]														=						self.get_image_processor()
         __lowerCamelCase  :      Any														=						self.get_tokenizer()

         __lowerCamelCase  :      Dict														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[Any]														=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         __lowerCamelCase  :      List[str]														=						processor.batch_decode(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Optional[Any]														=						tokenizer.batch_decode(SCREAMING_SNAKE_CASE_      )

         self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )














"""simple docstring"""







from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame


def      UpperCamelCase       ( _A = "laptop" )     ->       DataFrame:
				lowercase    :      List[str]       = F"""https://www.amazon.in/laptop/s?k={product}"""
				lowercase    :      str       = {
				    """User-Agent""": """Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36
        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36""",
				    """Accept-Language""": """en-US, en;q=0.5""",
				}
				lowercase    :      str       = BeautifulSoup(requests.get(_A  ,				headers=_A ).text )
				# Initialize a Pandas dataframe with the column titles
				lowercase    :      Optional[Any]       = DataFrame(
				    columns=[
				        """Product Title""",
				        """Product Link""",
				        """Current Price of the product""",
				        """Product Rating""",
				        """MRP of the product""",
				        """Discount""",
				    ] )
				# Loop through each entry and store them in the dataframe
				for item, _ in zip_longest(
				    soup.find_all(
				        """div"""  ,				attrs={"""class""": """s-result-item""", """data-component-type""": """s-search-result"""}  ,				)  ,				soup.find_all("""div"""  ,				attrs={"""class""": """a-row a-size-base a-color-base"""} )  ,				):
								try:
												lowercase    :      str       = item.ha.text
												lowercase    :      Tuple       = """https://www.amazon.in/""" + item.ha.a["""href"""]
												lowercase    :      Tuple       = item.find("""span"""  ,				attrs={"""class""": """a-offscreen"""} ).text
												try:
																lowercase    :      Any       = item.find("""span"""  ,				attrs={"""class""": """a-icon-alt"""} ).text
												except AttributeError:
																lowercase    :      Tuple       = """Not available"""
												try:
																lowercase    :      Any       = (
																    """₹"""
																    + item.find(
																        """span"""  ,				attrs={"""class""": """a-price a-text-price"""} ).text.split("""₹""" )[1]
																)
												except AttributeError:
																lowercase    :      Any       = """"""
												try:
																lowercase    :      List[str]       = float(
																    (
																        (
																            float(product_mrp.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																            - float(product_price.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																        )
																        / float(product_mrp.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																    )
																    * 100 )
												except ValueError:
																lowercase    :      Tuple       = float("""nan""" )
								except AttributeError:
												pass
								lowercase    :      Union[str, Any]       = [
								    product_title,
								    product_link,
								    product_price,
								    product_rating,
								    product_mrp,
								    discount,
								]
				lowercase    :      Tuple       = """ """
				lowercase    :      List[str]       = """ """
				data_frame.index += 1
				return data_frame


if __name__ == "__main__":
				_lowerCAmelCase            =	'headphones'
				get_amazon_product_data(product).to_csv(F'Amazon Product Data for {product}.csv')
