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For small files

wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rC6LWGNkHaZkuojCEWDqSKcDGwFMBTYZ' -O transformer_semeval.clf

For large files

wget --load-cookies cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rC6LWGNkHaZkuojCEWDqSKcDGwFMBTYZ' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rC6LWGNkHaZkuojCEWDqSKcDGwFMBTYZ" -O transformer_semeval.clf

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Learning Structured Representation for Text Classification
via Reinforcement Learning

https://github.com/keavil/AAAI18-code

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def reduce_mem_usage(df):
    """ iterate through all the columns of a dataframe and modify the data type
        to reduce memory usage.        
    """
    start_mem = df.memory_usage().sum() / 1024**2
    print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))
    
    for col in df.columns:
        col_type = df[col].dtype
        

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import tensorflow as tf
import tensorflow_hub as hub
module_url = "https://tfhub.dev/google/universal-sentence-encoder-large/3"
# Import the Universal Sentence Encoder's TF Hub module
embed = hub.Module(module_url)

# Compute a representation for each message, showing various lengths supported.
messages = ["That band rocks!", "That song is really cool."]

with tf.Session() as session:

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from IPython import display

for i in range(100):
    display.clear_output(wait=True)
    print(i)

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sudo add-apt-repository ppa:graphics-drivers -y
sudo apt-get update

sudo apt-get install nvidia-driver-418 nvidia-utils-418 nvidia-settings -y
wget -N https://developer.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.105_418.39_linux.run
wget -N http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/libcudnn7_7.5.0.56-1+cuda10.1_amd64.deb
sudo ./cuda_10.1.105_418.39_linux.run --override --silent --toolkit --no-opengl-libs
sudo dpkg -i libcudnn7_7.5.0.56-1+cuda10.1_amd64.deb
sudo apt-get install libcupti-dev -y

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# Setting default encoding python ENV - Ubuntu (Linux) - /bin/bash

export PYTHONIOENCODING=UTF-8

*****************************************************************************************


# Making python server on any directory

python3 -m http.server

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cd ~ && python3 -m http.server 8082

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ttyd -p 5055 -i 0.0.0.0 -R tmux a -r -t 1

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#CODE

#Generate root password
import random, string
password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

#Download ngrok
! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
! unzip -qq -n ngrok-stable-linux-amd64.zip
#Setup sshd