jcjohnson

require 'torch'
require 'cutorch'
require 'nn'
require 'cunn'
require 'cudnn'

local N = 32
local cin = 64
local cout = 64
local height = 256

jcjohnson

cunn forward took 0.048157 +- 0.016924 [0.000000, 0.053959]	
cunn backward took 0.197217 += 0.069304 [0.000000, 0.220502]	
MM forward took 0.048390 +- 0.017005 [0.000000, 0.054137]	
MM backward took 0.198168 += 0.069635 [0.000000, 0.221254]	
cudnn forward took 0.063036 +- 0.022154 [0.000000, 0.070827]	
cudnn backward took 0.240987 += 0.084703 [0.000000, 0.272077]	

jcjohnson

require 'torch'
require 'cutorch'
require 'nn'
require 'cunn'
require 'cudnn'
require 'loadcaffe'

local cmd = torch.CmdLine()
cmd:option('-model', 'alexnet')
cmd:option('-backend', 'nn')

jcjohnson

require 'nn'

local times_two, parent = torch.class('nn.TimesTwo', 'nn.Module')


function times_two:__init()
  parent.__init(self)
end

jcjohnson

$(function() {

  var SERVER_URL = null;
  var video_active = false;
  var demo_running = false;

  var NUM_TO_SHOW = 20;

  var IMAGE_DISPLAY_WIDTH = 800;
  var BOX_LINE_WIDTH = 6;

jcjohnson

import argparse, random, os, time, json

from PIL import Image
from io import BytesIO
import base64

from flask import Flask, request
from flask.ext.cors import CORS
from flask_restful import Resource, Api

jcjohnson

require 'nn'
require 'cutorch'
require 'cunn'

--[[
-- A simple benchmark comparing fully-connected net times on CPU and GPU.
--
-- Note that we don't count time it takes to transfer data to the GPU.
--]]

jcjohnson

1 0.00348258706468
2 0.00497760079642
3 0.00846613545817
4 0.028898854011
5 0.0827517447657
6 0.17506234414
7 0.318862275449
8 0.478781827259
9 0.627372627373
10 0.752123938031

jcjohnson

require 'torch'
require 'nn'
require 'cutorch'
require 'cunn'
require 'cudnn'
require 'optim'
require 'hdf5'
require 'image'

jcjohnson

import argparse, os, glob, tempfile

import h5py
import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import imread, imresize

# Stupid workaround for some messed up images
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True