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import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
import numpy as np
import matplotlib
from matplotlib import pyplot as plt
%matplotlib inline

class linear_reg(tf.keras.Model):
    def __init__(self):

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# 1. openmpi-2.1.5 /home/qasdfgtyuiop/program/openmpi/
cd ~
mkdir program
cd program/
wget https://download.open-mpi.org/release/open-mpi/v2.1/openmpi-2.1.5.tar.gz
tar -zxvf openmpi-2.1.5.tar.gz
rm openmpi-2.1.5.tar.gz
cd openmpi-2.1.5/
./configure --prefix="/home/qasdfgtyuiop/program/openmpi"
make # take a while

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def loadmodel():
    H_model = tf.keras.models.load_model('./models/H_tf.model', custom_objects={'AniCELU':AniCELU})
    C_model = tf.keras.models.load_model('./models/C_tf.model', custom_objects={'AniCELU':AniCELU})
    N_model = tf.keras.models.load_model('./models/N_tf.model', custom_objects={'AniCELU':AniCELU})
    O_model = tf.keras.models.load_model('./models/O_tf.model', custom_objects={'AniCELU':AniCELU})

    modelist = [H_model, C_model, N_model, O_model]
    return modelist

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#include <iostream>

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# tensorflow
conda create -n tf python=3.5 tensorflow-gpu

# pytorch
conda install pytorch torchvision -c pytorch

# .bashrc
source activate tf

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on run {input, parameters}
	
	tell application "System Events" to set all_apps to the name of every process whose visible is true
	
	repeat with a in all_apps
		tell application "System Events" to try
			keystroke "h" using command down
			delay 0.1
 on error