Soumith Chintala soumith

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soumith / torchmemtest.lua

Last active December 14, 2015 00:39

torch seems to have a memleak in this case, even though you'd expect it to not, with the collectgarbage()

	require 'image'
	local memTestClass = torch.class('image.memTestClass')
	function memTestClass:__newindex__(key, value)
	if type(key) == 'number' then
	return 1 -- do this so that rawset isn't called anyways, stupid of me to miss this
	else rawset(self, key, value) end
	end

	function testMemory()
	n = 50000

soumith / gist:6011923

Last active December 19, 2015 20:09 — forked from culurciello/gist:5189137

	#!/usr/bin/env torch
	require 'nn'
	require 'image'
	require 'xlua'
	require 'pl'


	opt = lapp[[
	-t,--threads (default 8) number of threads
	-p,--type (default float) float or cuda

soumith / async-http-leak.lua

Last active January 1, 2016 13:19

testing async http mem leak

	local async = require 'async'
	local http = require 'socket.http'
	local ltn12 = require 'ltn12'

	function start()
	local url = 'tcp://localhost:8082/'
	while true do
	print(os.date())

	local response = {}

soumith / tcp-memleaks.lua

Last active January 1, 2016 15:19

tcp-memleaks.lua

	local tcp = require 'socket'
	require 'sys'

	function start()
	while true do
	print(os.date())
	local conn = tcp.connect('localhost',8483)
	conn:send('ealasjdiasldjeladj')
	conn:close()
	sys.sleep(0.01)

soumith / gist:c5a7ac73e06aee39e48d

Created May 1, 2014 01:36

gist of using the *CUDA modules

	features = nn.Sequential()
	features:add(nn.Transpose({1,4},{1,3},{1,2}))
	features:add(nn.SpatialConvolutionCUDA(fSize[1], fSize[2], 9, 9, 2, 2)) -- (111 - 9 + 2)/2 = 52
	features:add(nn.Threshold(0,1e-6))
	features:add(nn.SpatialMaxPoolingCUDA(2,2,2,2)) -- 26
	features:add(nn.SpatialConvolutionCUDA(fSize[2], fSize[3], 5, 5)) -- 22
	features:add(nn.Threshold(0,1e-6))
	features:add(nn.SpatialMaxPoolingCUDA(2,2,2,2)) -- 11
	features:add(nn.SpatialConvolutionCUDA(fSize[3], fSize[4], 4, 4)) -- 8
	features:add(nn.Threshold(0,1e-6))

soumith / criterion.lua

Last active August 29, 2015 14:01

	require 'torch'
	require 'nn'


	local mytester = torch.Tester()
	local precision = 1e-5

	local critest = {}

	function critest.MSECriterion()

soumith / shared-brad

Created May 14, 2014 17:48

	require 'torch'
	require 'nn'

	torch.setdefaulttensortype('torch.FloatTensor')
	-------------- Model -------------------------
	branch = nn.Sequential()
	branch:add(nn.Linear(4,5))
	branch:add(nn.Linear(5,1))

	parallel=nn.Parallel(1,1);

soumith / conv-brad

Created May 14, 2014 18:05

	require 'torch'
	require 'nn'

	torch.setdefaulttensortype('torch.FloatTensor')

	frameSize = 4 -- each input frame has 4 numbers
	hiddenSize = 5 -- each hidden layer has 5 units
	outputSize = 1 -- each output layer has 1 output
	-------------- Model -------------------------
	mlp = nn.Sequential()

soumith / batch-brad

Last active August 29, 2015 14:01

	require 'torch'
	require 'nn'
	require 'sys'

	torch.setdefaulttensortype('torch.FloatTensor')
	numInputNodes=30
	numBatches=64
	numHidden1=64
	numHidden2=128
	numOutputNodes=1

soumith / bug1.lua

Created July 3, 2014 15:22