biggzlar

import numpy as np
from matplotlib import pyplot as plt

mean = [0, 0]
cov  = [[1., .5], [.5, 1.]]
m = 128

X = np.random.multivariate_normal(mean, cov, m)

cov = np.cov(X.T)

biggzlar

#!/bin/bash
## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.2 in ubuntu 18.04

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

biggzlar

import imageio
import numpy as np
from skimage.transform import resize
import tensorflow as tf

# obviously requires a session to run
outs = sess.run(conv0, feed_dict={input : img})
for i in range(32):
  # this will size up the filter output to (200, 200) and save it as .png
  imageio.imwrite(str(i) + '.png', resize((outs[0,:,:,i] * 200).astype(np.uint8), (200, 200)))

biggzlar

import numpy as np
import matplotlib.pyplot as plt


def softmax(x, beta=1.0):
    return np.exp(beta * x) / np.sum(np.exp(beta * x))


def softargmax(x, beta=1.0):
    return np.sum((np.exp(beta * x) / np.sum(np.exp(beta * x))) * np.arange(len(x)))