






'''simple docstring'''







import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 	SCREAMING_SNAKE_CASE					(					_A	,   unittest.TestCase       ):
			snake_case__  =				CodeGenTokenizer
			snake_case__  =				CodeGenTokenizerFast
			snake_case__  =				True
			snake_case__  =				{"add_prefix_space": True}
			snake_case__  =				False






			def 			SCREAMING_SNAKE_CASE      ( self      :			List[str]					)			->			List[Any]:
							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							a_		:  Tuple											=      [
							    "l",
							    "o",
							    "w",
							    "e",
							    "r",
							    "s",
							    "t",
							    "i",
							    "d",
							    "n",
							    "\u0120",
							    "\u0120l",
							    "\u0120n",
							    "\u0120lo",
							    "\u0120low",
							    "er",
							    "\u0120lowest",
							    "\u0120newer",
							    "\u0120wider",
							    "<unk>",
							    "<|endoftext|>",
							]
							a_		:  List[str]											=      dict(zip(__SCREAMING_SNAKE_CASE  ,						range(len(__SCREAMING_SNAKE_CASE					)					)					)					)
							a_		:  Optional[int]											=      ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
							a_		:  str											=      {"unk_token": "<unk>"}

							a_		:  Optional[int]											=      os.path.join(self.tmpdirname  ,						VOCAB_FILES_NAMES['''vocab_file''']					)
							a_		:  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					)					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			List[str]  ,						**__SCREAMING_SNAKE_CASE      :			Union[str, Any]					)			->			Any:
							kwargs.update(self.special_tokens_map					)
							return CodeGenTokenizer.from_pretrained(self.tmpdirname  ,						**__SCREAMING_SNAKE_CASE					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			int  ,						**__SCREAMING_SNAKE_CASE      :			List[Any]					)			->			List[Any]:
							kwargs.update(self.special_tokens_map					)
							return CodeGenTokenizerFast.from_pretrained(self.tmpdirname  ,						**__SCREAMING_SNAKE_CASE					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			Any  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]					)			->			Tuple:
							a_		:  Any											=      "lower newer"
							a_		:  Dict											=      "lower newer"
							return input_text, output_text






			def 			SCREAMING_SNAKE_CASE      ( self      :			List[str]					)			->			Optional[int]:
							a_		:  Optional[Any]											=      CodeGenTokenizer(self.vocab_file  ,						self.merges_file  ,						**self.special_tokens_map					)
							a_		:  Optional[Any]											=      "lower newer"
							a_		:  Optional[int]											=      ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
							a_		:  List[str]											=      tokenizer.tokenize(__SCREAMING_SNAKE_CASE  ,						add_prefix_space=__SCREAMING_SNAKE_CASE					)
							self.assertListEqual(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					)

							a_		:  List[str]											=      tokens + [tokenizer.unk_token]
							a_		:  List[Any]											=      [14, 15, 10, 9, 3, 2, 15, 19]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE					)  ,						__SCREAMING_SNAKE_CASE					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			List[Any]					)			->			Any:
							if not self.test_rust_tokenizer:
											return

							a_		:  str											=      self.get_tokenizer()
							a_		:  List[Any]											=      self.get_rust_tokenizer(add_prefix_space=__SCREAMING_SNAKE_CASE					)

							a_		:  Tuple											=      "lower newer"

							# Testing tokenization
							a_		:  Optional[Any]											=      tokenizer.tokenize(__SCREAMING_SNAKE_CASE  ,						add_prefix_space=__SCREAMING_SNAKE_CASE					)
							a_		:  Optional[int]											=      rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
							self.assertListEqual(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					)

							# Testing conversion to ids without special tokens
							a_		:  Dict											=      tokenizer.encode(__SCREAMING_SNAKE_CASE  ,						add_special_tokens=__SCREAMING_SNAKE_CASE  ,						add_prefix_space=__SCREAMING_SNAKE_CASE					)
							a_		:  List[Any]											=      rust_tokenizer.encode(__SCREAMING_SNAKE_CASE  ,						add_special_tokens=__SCREAMING_SNAKE_CASE					)
							self.assertListEqual(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					)

							# Testing conversion to ids with special tokens
							a_		:  Any											=      self.get_rust_tokenizer(add_prefix_space=__SCREAMING_SNAKE_CASE					)
							a_		:  str											=      tokenizer.encode(__SCREAMING_SNAKE_CASE  ,						add_prefix_space=__SCREAMING_SNAKE_CASE					)
							a_		:  int											=      rust_tokenizer.encode(__SCREAMING_SNAKE_CASE					)
							self.assertListEqual(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					)

							# Testing the unknown token
							a_		:  Tuple											=      tokens + [rust_tokenizer.unk_token]
							a_		:  int											=      [14, 15, 10, 9, 3, 2, 15, 19]
							self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE					)  ,						__SCREAMING_SNAKE_CASE					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			str  ,						*__SCREAMING_SNAKE_CASE      :			Dict  ,						**__SCREAMING_SNAKE_CASE      :			int					)			->			Union[str, Any]:
							# It's very difficult to mix/test pretokenization with byte-level
							# And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
							pass






			def 			SCREAMING_SNAKE_CASE      ( self      :			Optional[Any]  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=15					)			->			List[str]:
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'					):
															a_		:  Dict											=      self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE  ,						**__SCREAMING_SNAKE_CASE					)

															# Simple input
															a_		:  List[str]											=      "This is a simple input"
															a_		:  int											=      ["This is a simple input 1", "This is a simple input 2"]
															a_		:  Dict											=      ("This is a simple input", "This is a pair")
															a_		:  Dict											=      [
															    ("This is a simple input 1", "This is a simple input 2"),
															    ("This is a simple pair 1", "This is a simple pair 2"),
															]

															# Simple input tests
															self.assertRaises(__SCREAMING_SNAKE_CASE  ,						tokenizer_r.encode  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''					)

															# Simple input
															self.assertRaises(__SCREAMING_SNAKE_CASE  ,						tokenizer_r.encode_plus  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''					)

															# Simple input
															self.assertRaises(
															    __SCREAMING_SNAKE_CASE  ,						tokenizer_r.batch_encode_plus  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''  ,						)

															# Pair input
															self.assertRaises(__SCREAMING_SNAKE_CASE  ,						tokenizer_r.encode  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''					)

															# Pair input
															self.assertRaises(__SCREAMING_SNAKE_CASE  ,						tokenizer_r.encode_plus  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''					)

															# Pair input
															self.assertRaises(
															    __SCREAMING_SNAKE_CASE  ,						tokenizer_r.batch_encode_plus  ,						__SCREAMING_SNAKE_CASE  ,						max_length=__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''  ,						)






			def 			SCREAMING_SNAKE_CASE      ( self      :			Union[str, Any]					)			->			int:
							a_		:  Tuple											=      CodeGenTokenizer.from_pretrained(self.tmpdirname  ,						pad_token='''<pad>'''					)

							# Simple input
							a_		:  List[Any]											=      "This is a simple input"
							a_		:  Union[str, Any]											=      ["This is a simple input looooooooong", "This is a simple input"]
							a_		:  int											=      ("This is a simple input", "This is a pair")
							a_		:  Union[str, Any]											=      [
							    ("This is a simple input loooooong", "This is a simple input"),
							    ("This is a simple pair loooooong", "This is a simple pair"),
							]

							a_		:  Tuple											=      tokenizer.pad_token_id

							a_		:  Optional[Any]											=      tokenizer(__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''  ,						max_length=30  ,						return_tensors='''np'''					)
							a_		:  List[Any]											=      tokenizer(__SCREAMING_SNAKE_CASE  ,						padding=__SCREAMING_SNAKE_CASE  ,						truncate=__SCREAMING_SNAKE_CASE  ,						return_tensors='''np'''					)
							a_		:  Any											=      tokenizer(*__SCREAMING_SNAKE_CASE  ,						padding='''max_length'''  ,						max_length=60  ,						return_tensors='''np'''					)
							a_		:  List[str]											=      tokenizer(__SCREAMING_SNAKE_CASE  ,						padding=__SCREAMING_SNAKE_CASE  ,						truncate=__SCREAMING_SNAKE_CASE  ,						return_tensors='''np'''					)

							# s
							# test single string max_length padding
							self.assertEqual(out_s['''input_ids'''].shape[-1]  ,						30					)
							self.assertTrue(pad_token_id in out_s['''input_ids''']					)
							self.assertTrue(0 in out_s['''attention_mask''']					)

							# s2
							# test automatic padding
							self.assertEqual(out_sa['''input_ids'''].shape[-1]  ,						33					)
							# long slice doesn't have padding
							self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]					)
							self.assertFalse(0 in out_sa['''attention_mask'''][0]					)
							# short slice does have padding
							self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]					)
							self.assertTrue(0 in out_sa['''attention_mask'''][1]					)

							# p
							# test single pair max_length padding
							self.assertEqual(out_p['''input_ids'''].shape[-1]  ,						60					)
							self.assertTrue(pad_token_id in out_p['''input_ids''']					)
							self.assertTrue(0 in out_p['''attention_mask''']					)

							# p2
							# test automatic padding pair
							self.assertEqual(out_pa['''input_ids'''].shape[-1]  ,						52					)
							# long slice pair doesn't have padding
							self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]					)
							self.assertFalse(0 in out_pa['''attention_mask'''][0]					)
							# short slice pair does have padding
							self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]					)
							self.assertTrue(0 in out_pa['''attention_mask'''][1]					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			List[str]					)			->			str:
							a_		:  List[str]											=      "$$$"
							a_		:  Dict											=      CodeGenTokenizer.from_pretrained(self.tmpdirname  ,						bos_token=__SCREAMING_SNAKE_CASE  ,						add_bos_token=__SCREAMING_SNAKE_CASE					)

							a_		:  int											=      "This is a simple input"
							a_		:  Optional[Any]											=      ["This is a simple input 1", "This is a simple input 2"]

							a_		:  Any											=      tokenizer.bos_token_id

							a_		:  Optional[Any]											=      tokenizer(__SCREAMING_SNAKE_CASE					)
							a_		:  int											=      tokenizer(__SCREAMING_SNAKE_CASE					)

							self.assertEqual(out_s.input_ids[0]  ,						__SCREAMING_SNAKE_CASE					)
							self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids					)					)

							a_		:  int											=      tokenizer.decode(out_s.input_ids					)
							a_		:  Tuple											=      tokenizer.batch_decode(out_sa.input_ids					)

							self.assertEqual(decode_s.split()[0]  ,						__SCREAMING_SNAKE_CASE					)
							self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa					)					)






			@slow
			def 			SCREAMING_SNAKE_CASE      ( self      :			Tuple					)			->			Dict:
							a_		:  List[Any]											=      CodeGenTokenizer.from_pretrained('''Salesforce/codegen-350M-mono'''					)

							a_		:  List[str]											=      "\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"
							a_		:  str											=      "\nif len_a > len_b:      result = a\nelse:      result = b"

							a_		:  str											=      tokenizer.encode(__SCREAMING_SNAKE_CASE					)
							a_		:  Dict											=      ["^#", re.escape('''<|endoftext|>'''					), "^'''", "^\"\"\"", "\n\n\n"]
							a_		:  str											=      tokenizer.decode(__SCREAMING_SNAKE_CASE  ,						truncate_before_pattern=__SCREAMING_SNAKE_CASE					)
							self.assertEqual(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					)







			def 			SCREAMING_SNAKE_CASE      ( self      :			Dict					)			->			str:
							pass












'''simple docstring'''







import requests
from bsa import BeautifulSoup





def 		_UpperCAmelCase   (							__A							:   str						,		__A							:   dict      ):
				a_		:  Tuple											=      BeautifulSoup(requests.get(__A						,		params=__A      ).content						,		'''html.parser'''      )
				a_		:  List[str]											=      soup.find('''div'''						,		attrs={'''class''': '''gs_ri'''}      )
				a_		:  List[str]											=      div.find('''div'''						,		attrs={'''class''': '''gs_fl'''}      ).find_all('''a'''      )
				return anchors[2].get_text()


if __name__ == "__main__":
		__lowerCAmelCase       		=      {
		    'title': (
		        'Precisely geometry controlled microsupercapacitors for ultrahigh areal '
		        'capacitance, volumetric capacitance, and energy density'
		    ),
		    'journal': 'Chem. Mater.',
		    'volume': 30,
		    'pages': '3979-3990',
		    'year': 2_018,
		    'hl': 'en',
		}
		print(get_citation('https://scholar.google.com/scholar_lookup', params=params))




