




import requests
from bsa import BeautifulSoup




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				__magic_name__	:	Any								=BeautifulSoup(requests.get(lowerCamelCase	,     params=lowerCamelCase   ).content	,     """html.parser"""   )
				__magic_name__	:	List[Any]								=soup.find("""div"""	,     attrs={"""class""": """gs_ri"""}   )
				__magic_name__	:	Tuple								=div.find("""div"""	,     attrs={"""class""": """gs_fl"""}   ).find_all("""a"""   )
				return anchors[2].get_text()


if __name__ == "__main__":
							UpperCAmelCase_		:				Any									=     {
							    "title": (
							        "Precisely geometry controlled microsupercapacitors for ultrahigh areal "
							        "capacitance, volumetric capacitance, and energy density"
							    ),
							    "journal": "Chem. Mater.",
							    "volume": 30,
							    "pages": "3979-3990",
							    "year": 2018,
							    "hl": "en",
							}
							print(get_citation("https://scholar.google.com/scholar_lookup", params=params))










# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import sys

import transformers


UpperCAmelCase_		:				str									=     "3"

print("Python version:", sys.version)
print("transformers version:", transformers.__version__)

try:
							import torch

							print("Torch version:", torch.__version__)
							print("Cuda available:", torch.cuda.is_available())
							print("Cuda version:", torch.version.cuda)
							print("CuDNN version:", torch.backends.cudnn.version())
							print("Number of GPUs available:", torch.cuda.device_count())
							print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
							print("Torch version:", None)

try:
							import deepspeed

							print("DeepSpeed version:", deepspeed.__version__)
except ImportError:
							print("DeepSpeed version:", None)

try:
							import tensorflow as tf

							print("TensorFlow version:", tf.__version__)
							print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
							print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
							print("TensorFlow version:", None)




