censored--

GTX980 + Core i7 -6700K @ 4.00GHz + ubuntu 16.04 chainer

alexnet Average Forward: 51.7668122186 ms Average Backward: 122.44968462 ms Average Total: 174.216496838 ms

googlenet Average Forward: 234.798005846 ms

censored--

import theano.tensor as T
from theano import function
x = T.dscalar('x')
z = x**2
gz = T.grad(z, x)

f = function([x], gz)
print(f(12.2))

censored--

#!/bin/bash                                                                                                                          
python test.py -m "text message"

censored--

#!/bin/bash                                                                                                                          
python test.py -m "text message"

censored--

class SVM(object):
    def __init__(self,n_in,c0=1,c1=1,loss = RAMP_LOSS,gamma = 0.5):
        self.dim = n_in
        self.w = np.zeros(n_in)
        self.b = np.zeros(1)
        self.c0 = c0
        self.c1 = c1
        self.gamma = gamma
        self.x = None
        self.y = None

censored--

#include <Eigen/Core>
#include <Eigen/Sparse>
using namespace std;
using namespace Eigen;

void sinitialize(VectorXd &s,double mu,unsigned int sizex,VectorXd &x)
{
  for (unsigned int i=0;i<sizex;i++)
    if (x[i]!=0)s[i] = mu/x[i];
    else s[i]=0.1;

censored--

dot_globl	:min_caml_read_int
label	:min_caml_read_int
	read	at
	sll	at, at, 8
	read	at
	sll	at, at, 8
	read	at
	sll	at, at, 8
	read	at
	add	v0, at, zero

censored--

let rec create_2dmatrix a b c d =
  let matrix = Array.create 2 (Array.create 0 0.0) in
  matrix.(0)<-Array.create 2 0.0;
  matrix.(1)<-Array.create 2 0.0;
  let mx_0 = matrix.(0) in
  mx_0.(0)<- a;
  mx_0.(1)<- b;
  let mx_1 = matrix.(1) in
  mx_1.(0)<- c;
  mx_1.(1)<- d;