Setup env

jobs/log/MyLeNetMatNormalNoceil-44492595.out

@@ -0,0 +1,17 @@
+Namespace(batch=128, dataset='CIFAR10', epochs=10, lr=0.05, net='MyLeNetMatNormalNoceil', postfix='_noCrop', res_folder='res/', resume=False, scheduler='cosine', stoch=False, warmup_ep=5, warmup_mul=0)
+==> Preparing data..
+==> Building model..
+==> Training model..
+---------
+
+Epoch: 0
+Acc : 36.21 / 49.24
+Loss : 1.72 / 1.42
+Time: 247.9577119993046
+---------
+
+Epoch: 1
+Acc : 52.45 / 53.66
+Loss : 1.32 / 1.29
+Time: 496.28596297279
+slurmstepd: error: *** JOB 44492595 ON cdr294 CANCELLED AT 2020-06-23T01:58:42 ***

jobs/setup_env.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+#SBATCH --gres=gpu:1       # Request GPU "generic resources"
+#SBATCH --cpus-per-task=6  # Cores proportional to GPUs: 6 on Cedar, 16 on Graham.
+#SBATCH --mem=32000M       # Memory proportional to GPUs: 32000 Cedar, 64000 Graham.
+#SBATCH --account=def-mpederso
+#SBATCH --time=00:03:00
+#SBATCH --job-name=setup
+#SBATCH --output=log/%x-%j.out
+
+# Setup
+#sudo rm -rf ~/dataug/
+module load python/3.7.4
+virtualenv --no-download ~/stoch_pool
+source ~/stoch_pool/bin/activate
+pip install --no-index --upgrade pip
+
+pip install --no-index torch torchvision #torchviz
+
+pip install git+https://github.com/ildoonet/pytorch-gradual-warmup-lr.git
+pip install efficientnet_pytorch
+
+pip install --no-index matplotlib scipy opt-einsum
+#

jobs/test.sh

@@ -4,7 +4,7 @@
 #SBATCH --mem=32000M  #32000M       # Memory proportional to CPUs: 32000 Cedar, 64000 Graham.
 #SBATCH --account=def-mpederso
 #SBATCH --time=1:00:00
-#SBATCH --job-name=MyResNet18
+#SBATCH --job-name=MyLeNetMatNormalNoceil
 #SBATCH --output=log/%x-%j.out
 #SBATCH --mail-user=harle.collette.antoine@gmail.com
 #SBATCH --mail-type=END
@@ -12,15 +12,15 @@
 
 
 # Setup
-source ~/dataug/bin/activate
+source ~/stoch_pool/bin/activate
 
 #Execute
 # echo $(pwd) = /home/antoh/projects/def-mpederso/antoh/stoch/jobs
 cd ../
 
 time python main.py \
-    -n MyResNet18 \
+    -n MyLeNetMatNormalNoceil \
     -ep 10 \
     -sc cosine \
     -lr 5e-2 \
-    -pf _noCrop_Stoch
+    -pf _noCrop

main.py

@@ -49,7 +49,7 @@ checkpoint=False
 
 # Data
 print('==> Preparing data..')
-dataroot="./data"
+dataroot="~/scratch/data" #"./data"
 download_data=False
 transform_train = [
     # transforms.RandomCrop(32, padding=4),