
import json
import os
import re
import sys
import urllib.request

import requests
from bsa import BeautifulSoup

_lowerCamelCase	:    Optional[Any]          =      {
    '''User-Agent''': '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
    ''' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'''
}






def 	a_		(	__lowercase       :     str = "dhaka"	, __lowercase       :     Union[str, Any] = 5			)			->  int:
			_snake_case          =      min(__snake_case	, 50			)  # Prevent abuse!
			_snake_case          =      {
			    'q': query,
			    'tbm': 'isch',
			    'hl': 'en',
			    'ijn': '0',
			}

			_snake_case          =      requests.get('https://www.google.com/search'	, params=__snake_case	, headers=__snake_case			)
			_snake_case          =      BeautifulSoup(html.text	, 'html.parser'			)
			_snake_case          =      ''.join(
			    re.findall(r'AF_initDataCallback\(([^<]+)\);'	, str(soup.select('script'			)			)			)			)

			_snake_case          =      json.dumps(__snake_case			)
			_snake_case          =      json.loads(__snake_case			)

			_snake_case          =      re.findall(
			    r'\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\",'	, __snake_case	, )
			if not matched_google_image_data:
						return 0

			_snake_case          =      re.sub(
			    r'\[\"(https\:\/\/encrypted-tbn0\.gstatic\.com\/images\?.*?)\",\d+,\d+\]'	, ''	, str(__snake_case			)	, )

			_snake_case          =      re.findall(
			    r'(?:\'|,),\[\"(https:|http.*?)\",\d+,\d+\]'	, __snake_case	, )
			for index, fixed_full_res_image in enumerate(__snake_case			):
						if index >= max_images:
									return index
						_snake_case          =      bytes(__snake_case	, 'ascii'			).decode(
						    'unicode-escape'			)
						_snake_case          =      bytes(__snake_case	, 'ascii'			).decode(
						    'unicode-escape'			)
						_snake_case          =      urllib.request.build_opener()
						_snake_case          =      [
						    (
						        'User-Agent',
						        'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
						        ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582',
						    )
						]
						urllib.request.install_opener(__snake_case			)
						_snake_case          =      f'''query_{query.replace(' '	, '_'			)}'''
						if not os.path.exists(__snake_case			):
									os.makedirs(__snake_case			)
						urllib.request.urlretrieve(  # noqa: S310
						    __snake_case	, f'''{path_name}/original_size_img_{index}.jpg'''			)
			return index


if __name__ == "__main__":
					try:
										_lowerCamelCase	:    Union[str, Any]          =      download_images_from_google_query(sys.argv[1])
										print(F'{image_count} images were downloaded to disk.')
					except IndexError:
										print('''Please provide a search term.''')
										raise

import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_lowerCamelCase	:    Union[str, Any]          =      logging.getLogger()






def 	a_		(	__lowercase       :     Path	, __lowercase       :     list			)			->  Tuple:
			_snake_case          =      '\n'.join(__lowercase			)
			Path(__lowercase			).open('w'			).writelines(__lowercase			)


_lowerCamelCase	:    Any          =      '''patrickvonplaten/t5-tiny-random'''
_lowerCamelCase	:    List[Any]          =      '''sshleifer/bart-tiny-random'''
_lowerCamelCase	:    List[Any]          =      '''sshleifer/tiny-mbart'''

_lowerCamelCase	:    Union[str, Any]          =      logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks




class        SCREAMING_SNAKE_CASE__					(     UpperCAmelCase ):





	'''simple docstring'''



	def 			A							(  self     :   Optional[int]      ,  lowercase     :   int     ):


				'''simple docstring'''


				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     ) / 'utest_input.source'
				_snake_case          =      input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()
				_snake_case          =      [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
				_dump_articles(lowercase      ,  lowercase     )

				_snake_case          =      str(Path(self.get_auto_remove_tmp_dir()     ) / 'scores.json'     )
				_snake_case          =      'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case          =      f'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

				with patch.object(lowercase      ,  'argv'      ,  lowercase     ):
							run_generate()
							assert Path(lowercase     ).exists()
							# os.remove(Path(output_file_name))



	def 			A							(  self     :   List[Any]     ):


				'''simple docstring'''


				self.run_eval_tester(lowercase     )



	@parameterized.expand([BART_TINY, MBART_TINY]     )
	@slow
	def 			A							(  self     :   Any      ,  lowercase     :   int     ):


				'''simple docstring'''


				self.run_eval_tester(lowercase     )





	@parameterized.expand([T5_TINY, MBART_TINY]     )
	@slow
	def 			A							(  self     :   Any      ,  lowercase     :   str     ):


				'''simple docstring'''


				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     ) / 'utest_input.source'
				_snake_case          =      input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()

				_snake_case          =      {
				    'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
				    'de': [
				        'Maschinelles Lernen ist großartig, oder?',
				        'Ich esse gerne Bananen',
				        'Morgen ist wieder ein toller Tag!',
				    ],
				}

				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     )
				_snake_case          =      str(tmp_dir / 'scores.json'     )
				_snake_case          =      str(tmp_dir / 'val.target'     )
				_dump_articles(lowercase      ,  text['en']     )
				_dump_articles(lowercase      ,  text['de']     )
				_snake_case          =      'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case          =      f'''
            run_eval_search.py
            {model}
            {str(lowercase     )}
            {str(lowercase     )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
				testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']     )

				with patch.object(lowercase      ,  'argv'      ,  lowercase     ):
							with CaptureStdout() as cs:
										run_search()
							_snake_case          =      [' num_beams | length_penalty', model, 'Best score args']
							_snake_case          =      ['Info']
							if "translation" in task:
										expected_strings.append('bleu'     )
							else:
										expected_strings.extend(lowercase     )
							for w in expected_strings:
										assert w in cs.out
							for w in un_expected_strings:
										assert w not in cs.out
							assert Path(lowercase     ).exists()
							os.remove(Path(lowercase     )     )