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function product() { | |
var args = Array.prototype.slice.call(arguments); // makes array from arguments | |
return args.reduce(function tl (accumulator, value) { | |
var tmp = []; | |
accumulator.forEach(function (a0) { | |
value.forEach(function (a1) { | |
tmp.push(a0.concat(a1)); | |
}); | |
}); | |
return tmp; |
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from keras import backend as K | |
import tensorflow as tf | |
from tensorflow.contrib.session_bundle import exporter | |
sess = K.get_session() | |
export_path ="." | |
export_version = 1 | |
saver = tf.train.Saver(sharded=True) | |
### Code if you want to only export .meta files |
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import numpy as np | |
from PIL import Image, ImageDraw | |
import colorsys, random | |
from pylab import plot,show | |
from numpy import vstack,array | |
from numpy.random import rand | |
from scipy.cluster.vq import kmeans,vq | |
from mpl_toolkits.mplot3d import Axes3D | |
import matplotlib.pyplot as plt | |
import matplotlib.image as mpimg |
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