Torch: Difference between revisions
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You can compile [http://torch.ch/ Torch] on our | You can compile [http://torch.ch/ Torch] on our [[RHEL | Red Hat Enterprise Linux (RHEL)]] machines. Please make sure to [[HelpDesk | contact staff]] if you have issues, as there are some local packages that are required and could cause the install to fail. | ||
'''Note you have to use Cuda 8 or Cuda 7.5 when compiling Torch | '''Note you have to use Cuda 8 or Cuda 7.5 when compiling Torch. Certain newer GPU cards are not supported under Cuda 7.5. We will use Cuda 8 in this example.''' | ||
First load the following software into your environment with GNU [[Modules]]. | First load the following software into your environment with GNU [[Modules]]. |
Latest revision as of 13:56, 23 October 2024
You can compile Torch on our Red Hat Enterprise Linux (RHEL) machines. Please make sure to contact staff if you have issues, as there are some local packages that are required and could cause the install to fail.
Note you have to use Cuda 8 or Cuda 7.5 when compiling Torch. Certain newer GPU cards are not supported under Cuda 7.5. We will use Cuda 8 in this example.
First load the following software into your environment with GNU Modules.
module add cuda/8.0.61 cudnn zeromq nodejs sox GraphicsMagick
Next we are going to create a python environment and active it (this assumes you are using the bash shell)
virtualenv env source env/bin/activate
Then we are going to upgrade the python pip package manager and install two more dependencies
pip install --upgrade pip pip install pyzmq ipython
Next clone the repository from Torch ensuring you do it with the recursive option to get all its sub dependencies.
git clone https://github.com/torch/distro.git torch --recursive
Finally build Torch, this will take awhile.
cd torch && ./install.sh
At the end it will give you example of how to activate your Torch environment here is an example.
source install/bin/torch-activate
Now you can test you your install with the command th torch_test.th
where the contents of the file torch_test.th
are the following.
a = torch.Tensor(5,3) a = torch.rand(5,3) b = torch.rand(3,4) c = torch.Tensor(5,4) c:mm(a,b) print(c) require 'cutorch'; a = a:cuda() b = b:cuda() c = c:cuda() c:mm(a,b) print(c)