


import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowercase     :						Any	=     '▁'

__lowercase     :						Union[str, Any]	=     get_tests_dir('fixtures/test_sentencepiece.model')





@require_sentencepiece
class 							__UpperCamelCase    (		lowerCAmelCase__		,				unittest.TestCase ):
	A_           =   BertGenerationTokenizer
	A_           =   False
	A_           =   True




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						super().setUp()

						__a      :	List[str]    =  BertGenerationTokenizer(_SCREAMING_SNAKE_CASE						,    keep_accents=_SCREAMING_SNAKE_CASE							)
						tokenizer.save_pretrained(self.tmpdirname							)




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Dict    =  '<s>'
						__a      :	Any    =  1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(_SCREAMING_SNAKE_CASE							)						,    _SCREAMING_SNAKE_CASE							)
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(_SCREAMING_SNAKE_CASE							)						,    _SCREAMING_SNAKE_CASE							)




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Tuple    =  list(self.get_tokenizer().get_vocab().keys()							)

						self.assertEqual(vocab_keys[0]						,    '<unk>'							)
						self.assertEqual(vocab_keys[1]						,    '<s>'							)
						self.assertEqual(vocab_keys[-1]						,    '<pad>'							)
						self.assertEqual(len(_SCREAMING_SNAKE_CASE							)						,    1002							)




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						self.assertEqual(self.get_tokenizer().vocab_size						,    1000							)




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Union[str, Any]    =  BertGenerationTokenizer(_SCREAMING_SNAKE_CASE						,    keep_accents=_SCREAMING_SNAKE_CASE							)

						__a      :	Any    =  tokenizer.tokenize('This is a test'							)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,    ['▁This', '▁is', '▁a', '▁t', 'est']							)

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE							)						,    [285, 46, 10, 170, 382]						,    )

						__a      :	List[str]    =  tokenizer.tokenize('I was born in 92000, and this is falsé.'							)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,    [
						        SPIECE_UNDERLINE + 'I',
						        SPIECE_UNDERLINE + 'was',
						        SPIECE_UNDERLINE + 'b',
						        'or',
						        'n',
						        SPIECE_UNDERLINE + 'in',
						        SPIECE_UNDERLINE + '',
						        '9',
						        '2',
						        '0',
						        '0',
						        '0',
						        ',',
						        SPIECE_UNDERLINE + 'and',
						        SPIECE_UNDERLINE + 'this',
						        SPIECE_UNDERLINE + 'is',
						        SPIECE_UNDERLINE + 'f',
						        'al',
						        's',
						        'é',
						        '.',
						    ]						,    )
						__a      :	Optional[Any]    =  tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE							)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,    [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]						,    )

						__a      :	List[Any]    =  tokenizer.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE							)
						self.assertListEqual(
						    _SCREAMING_SNAKE_CASE						,    [
						        SPIECE_UNDERLINE + 'I',
						        SPIECE_UNDERLINE + 'was',
						        SPIECE_UNDERLINE + 'b',
						        'or',
						        'n',
						        SPIECE_UNDERLINE + 'in',
						        SPIECE_UNDERLINE + '',
						        '<unk>',
						        '2',
						        '0',
						        '0',
						        '0',
						        ',',
						        SPIECE_UNDERLINE + 'and',
						        SPIECE_UNDERLINE + 'this',
						        SPIECE_UNDERLINE + 'is',
						        SPIECE_UNDERLINE + 'f',
						        'al',
						        's',
						        '<unk>',
						        '.',
						    ]						,    )




	@cached_property
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'							)




	@slow
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Tuple    =  'Hello World!'
						__a      :	List[str]    =  [1_8536, 2260, 101]

						self.assertListEqual(_SCREAMING_SNAKE_CASE						,    self.big_tokenizer.encode(_SCREAMING_SNAKE_CASE							)							)




	@slow
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	List[str]    =  (
						    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will'
						    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
						)
						__a      :	Optional[Any]    =  [
						    871,
						    419,
						    358,
						    946,
						    991,
						    2521,
						    452,
						    358,
						    1357,
						    387,
						    7751,
						    3536,
						    112,
						    985,
						    456,
						    126,
						    865,
						    938,
						    5400,
						    5734,
						    458,
						    1368,
						    467,
						    786,
						    2462,
						    5246,
						    1159,
						    633,
						    865,
						    4519,
						    457,
						    582,
						    852,
						    2557,
						    427,
						    916,
						    508,
						    405,
						    3_4324,
						    497,
						    391,
						    408,
						    1_1342,
						    1244,
						    385,
						    100,
						    938,
						    985,
						    456,
						    574,
						    362,
						    1_2597,
						    3200,
						    3129,
						    1172,
						]

						self.assertListEqual(_SCREAMING_SNAKE_CASE						,    self.big_tokenizer.encode(_SCREAMING_SNAKE_CASE							)							)




	@require_torch
	@slow
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						import torch

						from transformers import BertGenerationConfig, BertGenerationEncoder

						# Build sequence
						__a      :	int    =  list(self.big_tokenizer.get_vocab().keys()							)[:10]
						__a      :	Union[str, Any]    =  ' '.join(_SCREAMING_SNAKE_CASE							)
						__a      :	Optional[Any]    =  self.big_tokenizer.encode_plus(_SCREAMING_SNAKE_CASE						,    return_tensors='pt'						,    return_token_type_ids=_SCREAMING_SNAKE_CASE							)
						__a      :	Tuple    =  self.big_tokenizer.batch_encode_plus(
						    [sequence + ' ' + sequence]						,    return_tensors='pt'						,    return_token_type_ids=_SCREAMING_SNAKE_CASE							)

						__a      :	int    =  BertGenerationConfig()
						__a      :	Dict    =  BertGenerationEncoder(_SCREAMING_SNAKE_CASE							)

						assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

						with torch.no_grad():
											model(**_SCREAMING_SNAKE_CASE							)
											model(**_SCREAMING_SNAKE_CASE							)





	@slow
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	List[Any]    =  {'input_ids': [[3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114], [448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=_SCREAMING_SNAKE_CASE						,    model_name='google/bert_for_seq_generation_L-24_bbc_encoder'						,    revision='c817d1fd1be2ffa69431227a1fe320544943d4db'						,    )







'''simple docstring'''



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

import requests
from bsa import BeautifulSoup

__lowercase     :						str	=     {
    '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   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       str = "dhaka"						,				_SCREAMING_SNAKE_CASE				:       int = 5       ):
					__a      :	Optional[Any]    =  min(_SCREAMING_SNAKE_CASE						,				50       )  # Prevent abuse!
					__a      :	Optional[Any]    =  {
					    'q': query,
					    'tbm': 'isch',
					    'hl': 'en',
					    'ijn': '0',
					}

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

					__a      :	Optional[Any]    =  json.dumps(_SCREAMING_SNAKE_CASE       )
					__a      :	List[str]    =  json.loads(_SCREAMING_SNAKE_CASE       )

					__a      :	List[Any]    =  re.findall(
					    r'\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\",'						,				_SCREAMING_SNAKE_CASE						,				)
					if not matched_google_image_data:
										return 0

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

					__a      :	Optional[Any]    =  re.findall(
					    r'(?:\'|,),\[\"(https:|http.*?)\",\d+,\d+\]'						,				_SCREAMING_SNAKE_CASE						,				)
					for index, fixed_full_res_image in enumerate(_SCREAMING_SNAKE_CASE       ):
										if index >= max_images:
															return index
										__a      :	List[str]    =  bytes(_SCREAMING_SNAKE_CASE						,				'ascii'       ).decode(
										    'unicode-escape'       )
										__a      :	Tuple    =  bytes(_SCREAMING_SNAKE_CASE						,				'ascii'       ).decode(
										    'unicode-escape'       )
										__a      :	Dict    =  urllib.request.build_opener()
										__a      :	Union[str, 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',
										    )
										]
										urllib.request.install_opener(_SCREAMING_SNAKE_CASE       )
										__a      :	List[Any]    =  F"""query_{query.replace(" "						,				"_"       )}"""
										if not os.path.exists(_SCREAMING_SNAKE_CASE       ):
															os.makedirs(_SCREAMING_SNAKE_CASE       )
										urllib.request.urlretrieve(  # noqa: S310
										    _SCREAMING_SNAKE_CASE						,				F"""{path_name}/original_size_img_{index}.jpg"""       )
					return index


if __name__ == "__main__":
	try:
		__lowercase     :						Optional[int]	=     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



