Currently torch initializes its random number generation by using the time in seconds. When running jobs in parallel this makes it easy to accidentally have jobs which have the same seed.

I'm opening this issue to propose:
attempting to fopen '/dev/urandom' in THRandom_seed and use that to initialize seed the seed. If this fails fall back to using time (i.e. on non-unix systems).

If this approach seems reasonable I'll work on a patch.

Hi,

What is roughly needed work to have torch working also on windows ?

If a tensor/table is serialized on x86 (ascii or binary) where nans are allowed to be saved and loaded,
and then serialized to ASCII, then loaded on an ARM machine, the loading fails with the error:
read error: read %d blocks instead of %d
where %d can be various numbers.

What do you guys think about adding support for broadcasting?

In terms of implementation, I believe it would be a simple matter of adding intelligent expandAs calls to the beginning of BLAS functions.

When parsing a command line, CmdLine interprets given boolean options as the negation of their default value. This is very annoying in the cases where one has fixed shell scripts controlling torch scripts and one fiddles around with default values in torch - the behaviour is then broken. I suggest that the special handling of boolean values in CmdLine:__readOption__() is dropped. In order to remain compatible with the current behaviour, there could be a "legacy" switch in CmdLine:__init() controlling this.

I found this problem when using torch/gnuplot, but it seems reasonable that torch.PipeFile would allow the caller to handle EPIPE instead of bailing out of luajit due to SIGPIPE.

Hi Soumith, I was wondering if you have any examples for running RNNs in Torch with LSTM?

I can't find trace of :squeeze() and :squeeze1d() in the doc, yet they're in the code.

Hope it could be fixed soon. Thanks!

I want to install Torch locally on REDHAT since I don't have sudo privilege:

cd torch7
mkdir build
cmake ..
make

I got the following errors:

/torch7/lib/luaT/luaT.c: In function ‘luaT_lua_newmetatable’:
/torch7/lib/luaT/luaT.c:454: error: ‘LUA_GLOBALSINDEX’ undeclared (first use in this function)
/torch7/lib/luaT/luaT.c:454: error: (Each undeclared identifier is reported only once
/torch7/lib/luaT/luaT.c:454: error: for each function it appears in.)
make[2]: *** [lib/luaT/CMakeFiles/luaT.dir/luaT.c.o] Error 1
make[1]: *** [lib/luaT/CMakeFiles/luaT.dir/all] Error 2
make: *** [all] Error 2

I thereby try:

ack LUA_GLOBALSINDEX

got:

init.c
59:  lua_setfield(L, LUA_GLOBALSINDEX, "torch");

lib/luaT/luaT.c
454:    lua_getfield(L, LUA_GLOBALSINDEX, module_name);
456:    lua_pushvalue(L, LUA_GLOBALSINDEX);

utils.c
116:  lua_getfield(L, LUA_GLOBALSINDEX, "torch");

I am just wondering where LUA_GLOBALSINDEX is declared... Any help is appreciated in advance!!

an nn model serialized and saved as littleendian binary (with torch.save on x86) fails to deserialize properly in bigendian machines (ARM), even after explicitly setting encoding with f:littleEndianEncoding()

Guys,

I am installing torch in my ubuntu 12.04, but failed to lzmq. Are you able to help on this issue? Thanks in advance.
Wenfeng
.....
gcc -shared -o lzmq/timer.so -L/home/wenfeng/torch-distro/install/lib src/ztimer.o src/lzutils.o -lrt
gcc -O2 -fPIC -I/home/wenfeng/torch-distro/install/include -c src/lzmq.c -o src/lzmq.o -DLUAZMQ_USE_SEND_AS_BUF -DLUAZMQ_USE_TEMP_BUFFERS -DLUAZMQ_USE_ERR_TYPE_OBJECT -I/usr/include
src/lzmq.c:482:1: error: ‘ZMQ_EVENT_CONNECTED’ undeclared here (not in a function)
src/lzmq.c:483:1: error: ‘ZMQ_EVENT_CONNECT_DELAYED’ undeclared here (not in a function)
src/lzmq.c:484:1: error: ‘ZMQ_EVENT_CONNECT_RETRIED’ undeclared here (not in a function)
src/lzmq.c:486:1: error: ‘ZMQ_EVENT_LISTENING’ undeclared here (not in a function)
src/lzmq.c:487:1: error: ‘ZMQ_EVENT_BIND_FAILED’ undeclared here (not in a function)
src/lzmq.c:489:1: error: ‘ZMQ_EVENT_ACCEPTED’ undeclared here (not in a function)
src/lzmq.c:490:1: error: ‘ZMQ_EVENT_ACCEPT_FAILED’ undeclared here (not in a function)
src/lzmq.c:492:1: error: ‘ZMQ_EVENT_CLOSED’ undeclared here (not in a function)
src/lzmq.c:493:1: error: ‘ZMQ_EVENT_CLOSE_FAILED’ undeclared here (not in a function)
src/lzmq.c:494:1: error: ‘ZMQ_EVENT_DISCONNECTED’ undeclared here (not in a function)
src/lzmq.c:499:1: error: ‘ZMQ_EVENT_ALL’ undeclared here (not in a function)

Error: Failed installing dependency: https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master/lzmq-0.4.2-1.src.rock - Build error: Failed compiling object src/lzmq.o
\nWriting new paths to shell config\n

i have to debug further, but torch.max(tensor, dim) is returning a nil value as output on arm. the same tensor is passed to the function on x86 and it works.

More concretely, I believe that the following is not correct:

The scalar might be on the right or left of the operator.

And then also the last example will fail:

> = 3-x

 1  1
 1  1
[torch.Tensor of dimension 2x2]

This commit introduces a bug on OSX: any call to the rand functions (randn, rand, ...) segfaults. Am I the only one to have this problem?

Basically, we could substitute a:copyAs(b) for a:resizeAs(b):copy(b).

I am aware (not yet sure why) that brew-doctor is expected to find

Warning: Unbrewed dylibs were found in /usr/local/lib.                                                                                                                                               [0/679]
If you didn't put them there on purpose they could cause problems when
building Homebrew formulae, and may need to be deleted.

Unexpected dylibs:
    /usr/local/lib/libluajit.dylib
    /usr/local/lib/libluaT.dylib
    /usr/local/lib/libqlua.dylib
    /usr/local/lib/libqtlua.dylib
    /usr/local/lib/libTH.dylib

But now we have a new comer

Warning: Unbrewed header files were found in /usr/local/include.
If you didn't put them there on purpose they could cause problems when
building Homebrew formulae, and may need to be deleted.

Unexpected header files:
    /usr/local/include/lauxlib.h
    /usr/local/include/lua.h
    /usr/local/include/luaconf.h
    /usr/local/include/luajit.h
    /usr/local/include/lualib.h
    /usr/local/include/luaT.h
    /usr/local/include/qtlua/qtluaconf.h
    /usr/local/include/qtlua/qtluaengine.h
    /usr/local/include/qtlua/qtluautils.h
    /usr/local/include/TH/generic/THBlas.h
    /usr/local/include/TH/generic/THLapack.h
    /usr/local/include/TH/generic/THStorage.h
    /usr/local/include/TH/generic/THStorageCopy.h
    /usr/local/include/TH/generic/THTensor.h
    /usr/local/include/TH/generic/THTensorConv.h
    /usr/local/include/TH/generic/THTensorCopy.h
    /usr/local/include/TH/generic/THTensorLapack.h
    /usr/local/include/TH/generic/THTensorMath.h
    /usr/local/include/TH/generic/THTensorRandom.h
    /usr/local/include/TH/TH.h
    /usr/local/include/TH/THAllocator.h
    /usr/local/include/TH/THBlas.h
    /usr/local/include/TH/THDiskFile.h
    /usr/local/include/TH/THFile.h
    /usr/local/include/TH/THFilePrivate.h
    /usr/local/include/TH/THGeneral.h
    /usr/local/include/TH/THGenerateAllTypes.h
    /usr/local/include/TH/THGenerateFloatTypes.h
    /usr/local/include/TH/THGenerateIntTypes.h
    /usr/local/include/TH/THLapack.h
    /usr/local/include/TH/THLogAdd.h
    /usr/local/include/TH/THMemoryFile.h
    /usr/local/include/TH/THRandom.h
    /usr/local/include/TH/THStorage.h
    /usr/local/include/TH/THTensor.h
    /usr/local/include/TH/THTensorApply.h
    /usr/local/include/TH/THTensorDimApply.h
    /usr/local/include/TH/THTensorMacros.h
    /usr/local/include/TH/THVector.h

What is happening?

The test starts from a random initial matrix. For some starting matrices, the test fails.

Reproducible within 10-20 repeats of torch.test()

Building with gcc-4.9 and g++-4.9 on MacOS 10.9.5

[ 44%] Building C object lib/luaT/CMakeFiles/luaT.dir/luaT.c.o                                                                          
/tmp/luarocks_torch-scm-1-5577/torch7/lib/luaT/luaT.c: In function 'luaT_lua_newmetatable':                                             
/tmp/luarocks_torch-scm-1-5577/torch7/lib/luaT/luaT.c:398:21: error: 'LUA_GLOBALSINDEX' undeclared (first use in this function)         
     lua_getfield(L, LUA_GLOBALSINDEX, module_name);                                                                                    
                     ^                                                                                                                  
/tmp/luarocks_torch-scm-1-5577/torch7/lib/luaT/luaT.c:398:21: note: each undeclared identifier is reported only once for each function i
t appears in                                                                                                                            
make[2]: *** [lib/luaT/CMakeFiles/luaT.dir/luaT.c.o] Error 1                                                                            
make[1]: *** [lib/luaT/CMakeFiles/luaT.dir/all] Error 2                                                                                 
make: *** [all] Error 2                                                                                                                 

Error: Build error: Failed building.                                                                                                    

Hi,

I was just wondering what the deal is with this issue:

When reading a c header with pre-compiler statements, torch ffi seems to not parse this properly nor ignores the pre-compiler statements.

Thanks.

Hello.
I am trying to simulate what clement farabet and others did in this paper : http://yann.lecun.com/exdb/publis/pdf/farabet-pami-13.pdf
(learning hierarchical features for scene labeling).

What I want is to train my system (consisting of copies of a single convnet) on a multi-scale pyramid version of an image. upscale the individual outputs and combine them to form one large set of feature maps, and forward it onto a 2 layer MLP.

Can anyone please point me towards the code that does this ? A short tutorial would be helpful also.

Hi,

I was wondering if we could build some kind of memory pool singleton which we could pass around torch and cutorch functions (or which they could access via a static variable). But this singleton approach would require that we make it thread-safe...

Another option would be to make a Storage-local memory pool (or Tensor-local?). We add an attribute to the Storage structure which C/Cuda functions can resize and use as an object-local memory pool. We could make its use optional by adding a global function torch.poolMemory().

This would allow us to make all the repeating cudaMalloc and malloc calls occur only once, thereby making the code faster (non-blocking in the case of cutorch), at the cost of a heavier memory footprint. The many THTensor_newContiguous() and THCudaTensor_computesz all require new memory allocations, which are slow and hidden. The THTensor_newContiguous() is a particular nuisance as it is located in so many BLAS wrappers and nn.Modules.

I believe this latter option, the storage-local memory pool, would be quite thread-safe as accessing a single Storage from different threads isn't currently thread-safe anyway (AFAIK).

I am replicating the install-luajit+torch script for my distro (Gentoo), but it seems to want to install in root regardless of using --local.

Not cmake literate so not sure if these lines mean it's an expected behaviour:

TorchConfig.cmake.in:

# This (ugly) setup assumes:
#  CMAKE_PREFIX_PATH = LUA_BINDIR
#  CMAKE_INSTALL_PREFIX = PREFIX

If not, sundown, cwrap and paths install fine, and here is my in/output:

export $(eval ``luarocks path``)
export CMAKE_LIBRARY_PATH=/usr/lib64/gcc/x86_64-pc-linux-gnu/4.7.3/

lua_modules=('sundown' 'cwrap' 'paths' 'torch')

for i in "${lua_modules[@]}"
do
   luarocks --local --server=https://raw.github.com/torch/rocks/master install $i || (echo "Error occurred"; break)
echo 
done

Install the project...
-- Install configuration: "Release"
-- Installing: /usr/share/cmake/torch/TorchExports.cmake
CMake Error at cmake_install.cmake:48 (FILE):
  file INSTALL cannot copy file
  "/tmp/luarocks_torch-scm-1-9869/torch7/build/CMakeFiles/Export/share/cmake/torch/TorchExports.cmake"
  to "/usr/share/cmake/torch/TorchExports.cmake".

-fopenmp flag does not propagate to utils.c in compile on Mac OS X.
utils.c contains wrapper functions of OpenMP (omp_get_max_threads, omp_set_num_threads) but -fopenmp flags does not propagate when building utils.c. This prevents users access from setting the number of threads. This problem is reported in https://groups.google.com/forum/#!topic/torch7/VxA13-MjkUo

Hi guys

I'm confused: why does torch.eig(A), where A is a d-by-d square matrix, returns a d-by-2 tensor of eigenvalues, instead of a vector? Is it for complex eigenvalues?
Example:

t7> = torch.eig(torch.eye(5), 'V')
 1  0
 1  0
 1  0
 1  0
 1  0
[torch.DoubleTensor of dimension 5x2]

 1  0  0  0  0
 0  1  0  0  0
 0  0  1  0  0
 0  0  0  1  0
 0  0  0  0  1
[torch.DoubleTensor of dimension 5x5]

t7>

Even after the successful installation of cwrap** and cleaning we cannot successfully manage to compile the project:

$ make
[ 3%] Built target TH
[ 44%] Built target luaT
[ 48%] Generating random.c
lua: random.lua:1: module 'cwrap' not found:
Failed loading module cwrap in LuaRocks rock cwrap scm-1

Any advice?

** cwrap installation successful:
$ luarocks --local --server=https://raw.github.com/torch/rocks/master install cwrap
Installing https://raw.github.com/torch/rocks/master/cwrap-scm-1.rockspec...
Using https://raw.github.com/torch/rocks/master/cwrap-scm-1.rockspec... switching to 'build' mode
Cloning into 'cwrap'...
remote: Counting objects: 8, done.
remote: Compressing objects: 100% (7/7), done.
remote: Total 8 (delta 0), reused 5 (delta 0)
Receiving objects: 100% (8/8), 9.80 KiB | 0 bytes/s, done.
Checking connectivity... done.
Updating manifest for $/.luarocks/lib/luarocks/rocks

cwrap scm-1 is now built and installed in $/.luarocks (license: BSD)

There are a few tests failing in torch.test(). We should probably not merge a commit if some of the tests fail.

I am following the Torch tutorial here: http://code.madbits.com/wiki/doku.php?id=tutorial_basics

When I try to use the help function in iTorch, I cannot get help on certain functions. For example:

In [17]:
help(itorch.image)

Out[17]:
undocumented symbol 

In [18]:
help(res:view)
[string "help(res:view)..."]:1: function arguments expected near ')'

These functions themselves work correctly (after adding the appropriate preceding code from the tutorial). Am I calling the help command incorrectly or is there just missing documentation?

when I run the code, require 'cunn' ,it appears,
no field package.preload['cunn']
no file './cunn.lua'
no file '/usr/local/share/luajit-2.0.2/cunn.lua'
no file '/usr/local/share/lua/5.1/cunn.lua'
no file '/usr/local/share/lua/5.1/cunn/init.lua'
no file './cunn.lua'
no file './cunn/init.lua'
no file './lua/cunn.lua'
no file './lua/cunn/init.lua'
no file '/opt/zbstudio/lualibs/cunn/cunn.lua'
no file '/opt/zbstudio/lualibs/cunn.lua'
no file '/opt/zbstudio/bin/linux/x64/libcunn.so'
no file '/opt/zbstudio/bin/linux/x64/clibs/cunn.so'
no file './cunn.so'
no file '/usr/local/lib/lua/5.1/cunn.so'
no file '/usr/local/lib/lua/5.1/loadall.so'
no file '/opt/zbstudio/bin/linux/x64/libcunn.so'
no file '/opt/zbstudio/bin/linux/x64/clibs/cunn.so'
stack traceback:
[C]: in function 'require'
I need your help,thanks

require 'cutorch'
require 'torch'

a = rand(3,20,20):type('torch.FloatTensor')

a = a:cuda()

=torch.isTensor(a)

Then I got

> = torch.isTensor(a)
[string " torch.isTensor(a)"]:1: attempt to call field 'isTensor' (a nil value)

isTensor has been out-dated?

The docs for Reshape say:

module = Reshape(dimension1, dimension2, ..)

Reshapes an nxpxqx.. Tensor into a dimension1xdimension2x... Tensor, taking the elements column-wise.

However it appears to leave initial dimensions of size 1 unchanged.

>>> nn.Reshape(6):forward(torch.Tensor(1, 2, 3)):size()
1
6
[torch.LongStorage of size 2]

Is this a bug or is this intended behavior?

Perhaps this is a minor issue, but whenever I attempt to get help for the specific function
?torch.Tensor.data
the repl dies and dumps core with no stacktrace
Same behavior with th and qlua -lqttorch -lenv

I tried reinstalling torch to make sure I didn't have a corrupt install, but get the same behavior.

The helptool works for everything else I have tried so far.

getRNGState / setRNGState in THRandom does not correctly serialise the state used to generate normally distributed numbers.

See timharley:getRNG_gaussian_bug for a patch to the tests which uncovers the bug.

I am working on a fix.

Below is a short program that seems to demonstrate a memory leak in torch.writeObject(). On my system (Mac OSX 10.6.8, 8 GB memory) torch halts after 4096 iterations with the message "luajit: not enough memory". Note that the code explicitly calls the garbage collector after every call to writeObject(), leading to the hypothesis of a memory leak.

 -- bug-writeobject-memoryleak.lua
 -- demonstrate memory leak in torch.writeObject

 require 'torch'

 local function append(outputFile, count)
    local tensor = torch.rand(100000)
    print('appending', count)
    outputFile:writeObject(tensor)
    collectgarbage()
 end

 local outputFile = torch.DiskFile('/tmp/bug-writeoject-memoryleak.serialized', 'w')
 assert(outputFile)

 for i = 1, 1e6 do
    append(outputFile, i)
 end

 print('done')

Currently, we can initialize a tensor using a lua table. However, when one wishes to copy from a lua table into a tensor A, one either has to initialize another tensor B using the table and then copy B into A. Or one can just manually copy each element of the table into A using lua code. What I would like to do is extend torch.copy to take lua tables as input. I could use the code at https://github.com/torch/torch7/blob/master/generic/Tensor.c#L80 to modify the code at https://github.com/torch/torch7/blob/master/lib/TH/generic/THTensorCopy.c .

If this sounds good to you, I will proceed to implement.

When I run the install scripts, I get the following error. How to fix it?

curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-deps | bash
curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-luajit+torch | bash

(...)

[100%] Built target cunn
Install the project...
-- Install configuration: "Release"
-- Installing: /usr/local/lib/luarocks/rocks/cunn/scm-1/lib/libcunn.so
-- Set runtime path of "/usr/local/lib/luarocks/rocks/cunn/scm-1/lib/libcunn.so" to "$ORIGIN/../lib:/opt/OpenBLAS/lib:/usr/local/lib:/usr/local/cuda/lib64"
-- Installing: /usr/local/lib/luarocks/rocks/cunn/scm-1/lua/cunn/init.lua
-- Installing: /usr/local/lib/luarocks/rocks/cunn/scm-1/lua/cunn/test.lua
Warning: Directory 'doc' not found
Updating manifest for /usr/local/lib/luarocks/rocks

cunn scm-1 is now built and installed in /usr/local/ (license: BSD)
Installing https://raw.githubusercontent.com/torch/rocks/master/qtlua-scm-1.rockspec...
Using https://raw.githubusercontent.com/torch/rocks/master/qtlua-scm-1.rockspec... switching to 'build' mode
Cloning into 'qtlua'...
remote: Counting objects: 171, done.
remote: Compressing objects: 100% (161/161), done.
remote: Total 171 (delta 9), reused 132 (delta 1)
Receiving objects: 100% (171/171), 357.84 KiB | 170.00 KiB/s, done.
Resolving deltas: 100% (9/9), done.
Checking connectivity... done.
cmake -E make_directory build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release -DLUA=/usr/local/bin/luajit -DLUA_BINDIR="/usr/local/bin" -DLUA_INCDIR="/usr/local/include" -DLUA_LIBDIR="/usr/local/lib" -DLUADIR="/usr/local/lib/luarocks/rocks/qtlua/scm-1/lua" -DLIBDIR="/usr/local/lib/luarocks/rocks/qtlua/scm-1/lib" -DCONFDIR="/usr/local/lib/luarocks/rocks/qtlua/scm-1/conf" && make

-- The C compiler identification is GNU 4.8.2
-- The CXX compiler identification is GNU 4.8.2
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Looking for Q_WS_X11
-- Looking for Q_WS_X11 - found
-- Looking for Q_WS_WIN
-- Looking for Q_WS_WIN - not found
-- Looking for Q_WS_QWS
-- Looking for Q_WS_QWS - not found
-- Looking for Q_WS_MAC
-- Looking for Q_WS_MAC - not found
CMake Error at /usr/share/cmake-2.8/Modules/FindPackageHandleStandardArgs.cmake:108 (message):
Could NOT find Qt4 (missing: QT_MOC_EXECUTABLE QT_RCC_EXECUTABLE
QT_UIC_EXECUTABLE) (found suitable version "4.8.5", minimum required is
"4.3.0")
Call Stack (most recent call first):
/usr/share/cmake-2.8/Modules/FindPackageHandleStandardArgs.cmake:315 (_FPHSA_FAILURE_MESSAGE)
/usr/share/cmake-2.8/Modules/FindQt4.cmake:1393 (FIND_PACKAGE_HANDLE_STANDARD_ARGS)
CMakeLists.txt:27 (FIND_PACKAGE)

-- Configuring incomplete, errors occurred!
See also "/tmp/luarocks_qtlua-scm-1-2097/qtlua/build/CMakeFiles/CMakeOutput.log".
See also "/tmp/luarocks_qtlua-scm-1-2097/qtlua/build/CMakeFiles/CMakeError.log".

Error: Build error: Failed building.

The example in the documentation doesn't work, because io.open won't create a folder. One would need to call os.execute('mkdir -p'..params.rundir) before cmd:log (which is quite dangerous), or CmdLine needs luafilesystem to create a folder if necessary.

Hi,

Fred (https://github.com/nouiz), from Theano, was asking if there was a common data format Torch and Theano could use to share its datasets?

I am aware of fb.thrift and fb.python, but they don't seem to provide a simple concise answer to this question, and I have never used them.

th> torch.randn(1,2) * torch.randn(2,1):expand(2,2)
 ** On entry to DGEMM  parameter number  8 had an illegal value
0 0
[torch.DoubleTensor of dimension 1x2]

thanks to tudor bosman for reporting this

When serializing an object using format == 'ascii', the values of number objects are truncated to 6 significant digits. Thus the loaded value can differ from the saved value.

Example program to illustrate this:

require 'torch'

local x = 913062344
local file = 'test_torch_save_load.data'
local format = 'ascii'

torch.save(file, x, format)
local y = torch.load(file, format)

print(x, y)
assert(x == y)
print('ok')

Let's sat I have a column from an image which I'd like to replicate horizontally. Only the first two row are computed correctly.

> = l
(1,.,.) = 
  0.6902
  0.6863
  0.6863
  0.6510
  0.6392

(2,.,.) = 
  0.6627
  0.6510
  0.6314
  0.5922
  0.5882

(3,.,.) = 
  0.6157
  0.5922
  0.5882
  0.5765
  0.5725
[torch.DoubleTensor of dimension 3x5x1]

> = l:repeatTensor(1,1,2)
(1,.,.) = 
  0.6902  0.6902
  0.6863  0.6863
  0.6627  0.6627
  0.6588  0.6588
  0.6471  0.6471

(2,.,.) = 
  0.6314  0.6314
  0.6157  0.6157
  0.6000  0.6000
  0.5765  0.5765
  0.5686  0.5686

(3,.,.) = 
  0.5569  0.5569
  0.5451  0.5451
  0.5176  0.5176
  0.5176  0.5176
  0.4980  0.4980
[torch.DoubleTensor of dimension 3x5x2]

I had to add

/usr/lib/gcc/x86_64-linux-gnu/4.8/ /opt/OpenBLAS/lib/

to FindBLAS.cmake, line 70, in order to compile correctly with Blas and Gfortran.

I'm on a Ubuntu 14.04.

I have a problem with parsing cmdine parameters staring with the letter l:

Heres a small script to demonstrate the problem

 print '==> processing options'
 cmd = torch.CmdLine()
 cmd:option('-learningrate', 0.05, 'lr')
 cmd:text()
 opts = cmd:parse(arg or {})

print(opts)

I savde the snippet in cmdline.lua and call:

   > th cmdtest.lua -learningrate 5
could not load earningrate, skipping
==> processing options  

invalid argument: 5 

Usage: [options] 
  -learningrate lr [0.05]

Apparently the learningrate parameters is passed in as earningrate? Changing the cmd parametername form learningrate to eta solves the problem:

th cmdtest.lua -eta 5
==> processing options
{
eta : 5
}
bn09574:Desktop sorensonderby$

I'm using OSX mavericks with a danish keyboard layout

I installed torch7 and other modules in mac by following the Cheatsheet. Somehow, the help function doesn't work. (help is nil)
Do you have any solution for this issue?

To be short, lua myscript.lua won't work as the doc shows.

1. torch is based on ``LuaJITandLuarocks`, which means that `lua` is not essential to this framework.
2. CmdLine is a torch utilities, as in torch tool collections, require torch`` is needed at the top of the code.
3. th myscript.lua gives what you want.

It's a pity. Well, this might be helpful to someone tried to read every torch docs.

using torc.max returns LongTensor for the idx

e.g

x = torch.rand(3,3)   -- Double
x_max,x_idx  = torch.max(x,2)  -- x_max = Double, x_idx = Long

Is it normal that the result of an expand() isn't contiguous (i.e. tensors having a stride of zero in one dim)?

Specifically, couldn't cublas deal with these directly without requiring a contiguous copy? Same goes for the cutorch copy kernels.

Because this is forcing me to use repeatTensor instead of expand.

Subtraction as described here: https://github.com/torch/torch7/blob/09eaf1ef629062ca69e4763d0fde26736340aa24/doc/maths.md#addition-and-substraction

(btw, it is spelled subtraction, not substraction)

Does not work as expected:

> x = torch.Tensor(2,2):fill(2)
                                                                      [0.0001s]
> = 3-x
[string "return  3-x..."]:1: internal error in __sub: no metatable
stack traceback:
    [C]: in function '__sub'
    [string "return  3-x..."]:1: in main chunk
    [C]: in function 'xpcall'
    /usr/local/share/lua/5.1/trepl/init.lua:519: in function </usr/local/share/lua/5.1/trepl/init.lua:426>
                                                                      [0.0002s]

i can install with the curl method that results this. i use the instalation instructions from http://torch.ch/

which: no nvcc in
....
sh: line 1: 41164 Trace/BPT trap: 5 'wget' --no-check-certificate --no-cache --user-agent='LuaRocks/2.2.0beta1 macosx-x86_64 via wget' --quiet --timeout=30 --tries=1 --timestamping 'https://raw.githubusercontent.com/torch/rocks/master/manifest' > /dev/null 2> /dev/null
Warning: Failed searching manifest: Failed fetching manifest for https://raw.githubusercontent.com/torch/rocks/master - Failed downloading https://raw.githubusercontent.com/torch/rocks/master/manifest

....
sh: line 1: 41185 Trace/BPT trap: 5 'wget' --no-check-certificate --no-cache --user-agent='LuaRocks/2.2.0beta1 macosx-x86_64 via wget' --quiet --timeout=30 --tries=1 --timestamping 'https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master/manifest' > /dev/null 2> /dev/null
Warning: Failed searching manifest: Failed fetching manifest for https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master - Failed downloading https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master/manifest

Error: No results matching query were found.
Password:

....
sh: line 1: 41657 Trace/BPT trap: 5 'wget' --no-check-certificate --no-cache --user-agent='LuaRocks/2.2.0beta1 macosx-x86_64 via wget' --quiet --timeout=30 --tries=1 --timestamping 'https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master/manifest' > /dev/null 2> /dev/null
Warning: Failed searching manifest: Failed fetching manifest for https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master - Failed downloading https://raw.githubusercontent.com/rocks-moonscript-org/moonrocks-mirror/master/manifest

Error: No results matching query were found.
Error. Exiting.