anton/mlpractical
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge branch 'mlp2017-8/semester_2_materials' of https://github.com/CSTR-Edinburgh/mlpractical into mlp2017-8/semester_2_materials

Browse Source
This commit is contained in:
AntreasAntoniou 2018-02-05 13:46:21 +00:00
commit c3ff1774af
2 changed files with 7 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
gpu_cluster_tutorial_training_script.sh
View File

@ -30,4 +30,4 @@ export TMP=/disk/scratch/${STUDENT_ID}/
source /home/${STUDENT_ID}/miniconda3/bin/activate mlp
python network_trainer.py --batch_size 128 --epochs 200 --experiment_prefix vgg-net-emnist-sample-exp --dropout_rate 0.4 --batch_norm_use True --strided_dim_reduction True --seed 25012018
python emnist_network_trainer.py --batch_size 128 --epochs 200 --experiment_prefix vgg-net-emnist-sample-exp --dropout_rate 0.4 --batch_norm_use True --strided_dim_reduction True --seed 25012018

4
notes/gpu-cluster-quick-start.md
View File

@ -54,7 +54,7 @@ git config --global user.name "[your name]"
git config --global user.email "[matric-number]@sms.ed.ac.uk"
```
9. Now clone the mlpractical repo using ```git clone https://github.com/CSTR-Edinburgh/mlpractical.git```.
10. Checkout the mlp_tf_tutorial branch using ```git checkout mlp2017-8/mlp_tf_tutorial```.
10. Checkout the semester_2 branch using ```git checkout mlp2017-8/semester_2_materials```.
11. ```cd mlpractical``` and then install the required packages using ```pip install -r requirements_gpu.txt```.
12. Once this is done you will need to setup the MLP_DATA path using the following block of commands:
```bash
@ -86,7 +86,7 @@ To submit a job one needs to use ```sbatch script.sh``` which will automatically
#SBATCH --mem=16000 # memory in Mb
#SBATCH -o outfile # send stdout to outfile
#SBATCH -e errfile # send stderr to errfile
#SBATCH -t 0:01:00 # time requested in hour:minute:seconds
#SBATCH -t 1:00:00 # time requested in hour:minute:seconds
# Setup CUDA and CUDNN related paths
export CUDA_HOME=/opt/cuda-8.0.44