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
# 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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/****************************************************************************** | |
Online C++ Compiler. | |
Code, Compile, Run and Debug C++ program online. | |
Write your code in this editor and press "Run" button to compile and execute it. | |
*******************************************************************************/ | |
#include <iostream> |
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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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# 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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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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plt.figure(figsize=(15,8)) | |
plt.subplot(4, 1, 1) | |
plt.plot(OH.iloc[:,0],OH.iloc[:,1]) | |
plt.ylim(0, 3.5e-18) | |
plt.xlim(3580, 3900) | |
plt.title('R branch', fontsize=16, pad=-20) | |
plt.subplot(4, 1, 2) | |
plt.plot(OH.iloc[:,0],OH.iloc[:,1]) |
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class Progbar(object): | |
"""Displays a progress bar. | |
Arguments: | |
target: Total number of steps expected, None if unknown. | |
width: Progress bar width on screen. | |
verbose: Verbosity mode, 0 (silent), 1 (verbose), 2 (semi-verbose) | |
stateful_metrics: Iterable of string names of metrics that | |
should *not* be averaged over time. Metrics in this list | |
will be displayed as-is. All others will be averaged | |
by the progbar before display. |
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