Phriction Projects Wikis Bioimaging And Optics Platform Image Processing Machine Learning Deep Learning SCITAS GPU Clusters Protocols History Version 4 vs 5
Version 4 vs 5
Version 4 vs 5
Content Changes
Content Changes
= First Time Setup =
Create environment
`virtualenv --system-site-packages -p python3 env-biop-tf2`
== Activate environment ==
source env-biop-tf2/bin/activate
== Install TF ==
```
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
pip install ipython tensorboard
```
== Test ==
ipython
import tensorflow as tf
= Run on the Cluster =
Request time as ptbiop user
```
salloc -t 2:0:0 -A ptbiop --exclusive
squeue -u $USER
ssh NAME OF ALLOCATED NODE
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
source env-biop-tf2/bin/activate
```
Now you can run stuff
NOTE: Nicola will update on the Jupyter Notebook setup
= First Time Setup =
Create environment
`virtualenv --system-site-packages -p python3 env-biop-tf2`
== Activate environment ==
source env-biop-tf2/bin/activate
== Install TF ==
```
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
pip install ipython tensorboard
```
== Test ==
ipython
import tensorflow as tf
= Run on the Cluster =
Request time as ptbiop user
```
salloc -t 2:0:0 -A ptbiop --exclusive
squeue -u $USER
ssh NAME OF ALLOCATED NODE
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
source env-biop-tf2/bin/activate
```
Now you can run stuff
NOTE: Nicola will update on the Jupyter Notebook setup
= YAPIC Setup =
NOTE: We need to work with TF 1.15 in YAPIC in order to be able to export YAPIC models to the ModelZoo structure for reuse in Fiji.
== First time setup ==
module load gcc/8.4.0-cuda cuda/10.2.89 cudnn/7.6.5.32-10.2-linux-x64
virtualenv -p python3 --system-site-packages yapic-tf-1.15
source yapic-tf-1.15/bin/activate
pip install tensorflow-gpu==1.15
cd yapic-tf-1.15/lib64
ln -s $CUDA_ROOT/lib64/libcudart.so libcudart.so.10.0
ln -s $CUDA_ROOT/lib64/libcublas.so libcublas.so.10.0
ln -s $CUDA_ROOT/lib64/libcufft.so libcufft.so.10.0
ln -s $CUDA_ROOT/lib64/libcurand.so libcurand.so.10.0
ln -s $CUDA_ROOT/lib64/libcusolver.so libcusolver.so.10.0
ln -s $CUDA_ROOT/lib64/libcusparse.so libcusparse.so.10.0
export LD_LIBRARY_PATH=$PWD:$LD_LIBRARY_PATH
Then we can start using YAPIC
Instructions to follow
= First Time Setup =
Create environment
`virtualenv --system-site-packages -p python3 env-biop-tf2`
== Activate environment ==
source env-biop-tf2/bin/activate
== Install TF ==
```
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
pip install ipython tensorboard
```
== Test ==
ipython
import tensorflow as tf
= Run on the Cluster =
Request time as ptbiop user
```
salloc -t 2:0:0 -A ptbiop --exclusive
squeue -u $USER
ssh NAME OF ALLOCATED NODE
module load python gcc/8.4.0-cuda mvapich2/2.3.4-cuda py-tensorflow
source env-biop-tf2/bin/activate
```
Now you can run stuff
NOTE: Nicola will update on the Jupyter Notebook setup
= YAPIC Setup =
NOTE: We need to work with TF 1.15 in YAPIC in order to be able to export YAPIC models to the ModelZoo structure for reuse in Fiji.
== First time setup ==
module load gcc/8.4.0-cuda cuda/10.2.89 cudnn/7.6.5.32-10.2-linux-x64
virtualenv -p python3 --system-site-packages yapic-tf-1.15
source yapic-tf-1.15/bin/activate
pip install tensorflow-gpu==1.15
cd yapic-tf-1.15/lib64
ln -s $CUDA_ROOT/lib64/libcudart.so libcudart.so.10.0
ln -s $CUDA_ROOT/lib64/libcublas.so libcublas.so.10.0
ln -s $CUDA_ROOT/lib64/libcufft.so libcufft.so.10.0
ln -s $CUDA_ROOT/lib64/libcurand.so libcurand.so.10.0
ln -s $CUDA_ROOT/lib64/libcusolver.so libcusolver.so.10.0
ln -s $CUDA_ROOT/lib64/libcusparse.so libcusparse.so.10.0
export LD_LIBRARY_PATH=$PWD:$LD_LIBRARY_PATH
Then we can start using YAPIC
Instructions to follow
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