From fbb82856c4d58ab629ffc1f546380b6f75b16d4b Mon Sep 17 00:00:00 2001 From: Andrei Politov <andrei.politov@tu-dresden.de> Date: Wed, 16 Jun 2021 11:55:44 +0000 Subject: [PATCH] Update PyTorch.md --- doc.zih.tu-dresden.de/docs/software/PyTorch.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/doc.zih.tu-dresden.de/docs/software/PyTorch.md b/doc.zih.tu-dresden.de/docs/software/PyTorch.md index 0a215967d..f3ca6f9bc 100644 --- a/doc.zih.tu-dresden.de/docs/software/PyTorch.md +++ b/doc.zih.tu-dresden.de/docs/software/PyTorch.md @@ -96,7 +96,7 @@ Examples: 1\. Simple MNIST model. The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. PyTorch allows us to import and download the MNIST dataset directly from the Torchvision - package consists of datasets, model architectures and transformations. The model contains a neural network with sequential architecture and typical modules for this kind of models. Recommended parameters for running this model are 1 GPU and 7 cores (28 thread) -[https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/PyTorch/example_MNIST_Pytorch.zip](%ATTACHURL%/example_MNIST_Pytorch.zip) +[example_MNIST_Pytorch.zip]() #### Running the model @@ -120,7 +120,7 @@ Examples: 1. Image recognition example. This PyTorch script is using Resnet to single image classification. Recommended parameters for running this model are 1 GPU and 7 cores (28 thread). -[https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/PyTorch/example_Pytorch_image_recognition.zip](%ATTACHURL%/example_Pytorch_image_recognition.zip) +[example_Pytorch_image_recognition.zip]() Remember that for using [JupyterHub service]() for PyTorch you need to create and activate a virtual environment (kernel) with loaded essential modules (see "envtest" environment form the virtual environment example. @@ -151,9 +151,9 @@ includes a comparison of different kinds of models and tips to improve the performance of your model. **Necessary** parameters for running this model are **2 GPU** and 14 cores (56 thread). -[https://doc.zih.tu-dresden.de/hpc-wiki/pub/Compendium/PyTorch/example_PyTorch_parallel.zip](%ATTACHURL%/example_PyTorch_parallel.zip?t=1572619180) +[example_PyTorch_parallel.zip]() -Remember that for using [JupyterHub service](JupyterHub) for PyTorch you need to create and activate a virtual environment (kernel) with loaded essential modules. +Remember that for using [JupyterHub service]() for PyTorch you need to create and activate a virtual environment (kernel) with loaded essential modules. Run the example in the same way as the previous examples. @@ -179,6 +179,6 @@ Keep in mind that only one memory parameter (`--mem-per-cpu` = <MB> or `--mem`=< -- [example_MNIST_Pytorch.zip](%ATTACHURL%/example_MNIST_Pytorch.zip) -- [example_Pytorch_image_recognition.zip](%ATTACHURL%/example_Pytorch_image_recognition.zip) -- [example_PyTorch_parallel.zip](%ATTACHURL%/example_PyTorch_parallel.zip) \ No newline at end of file +- [example_MNIST_Pytorch.zip]() +- [example_Pytorch_image_recognition.zip]() +- [example_PyTorch_parallel.zip]() -- GitLab