--- a
+++ b/FastRCNN/subMed.sh
@@ -0,0 +1,47 @@
+#!/usr/bin/env bash
+
+# Ron the short-list GPU queue
+#SBATCH -p slurm_priority
+#SBATCH --account=cmg --qos=priority 
+
+## Request one CPU core from the scheduler
+#SBATCH -c 1
+
+## Request a GPU from the scheduler, we don't care what kind
+#SBATCH --gres=gpu:p100:1
+#SBATCH -t 14-3:00 # time (D-HH:MM)
+
+## Create a unique output file for the job
+#SBATCH -o cuda_Training-%j.log
+
+## Load CUDA into your environment
+## load custimized CUDA and cudaToolkit
+
+module load usermods
+module load user/cuda
+#module load cuda/9.0
+
+# activate retina virtual environment
+source activate chainercv
+#conda install -c anaconda --name retina cudatoolkit==9.0 --yes
+#conda install -c anaconda --name retina cudnn --yes
+#conda install -c anaconda --name retina keras --yes
+
+# install tensorflow and other libraries for machine learning
+
+#/srv/home/shenmr/anaconda3/envs/retina/bin/pip install tensorflow-gpu==1.6
+#/srv/home/shenmr/anaconda3/envs/retina/bin/pip install numpy scipy scikit-learn pandas matplotlib seaborn
+#
+#/srv/home/shenmr/anaconda3/envs/retina/bin/pip msgpack 
+#conda install -c anaconda --name retina keras-gpu
+##/srv/home/shenmr/anaconda3/envs/retina/bin/pip install keras 
+#
+
+/srv/home/shenmr/anaconda3/envs/chainercv/bin/pip install scikit-image 
+/srv/home/shenmr/anaconda3/envs/chainercv/bin/pip install cupy-cuda90 
+/srv/home/shenmr/anaconda3/envs/chainercv/bin/pip install opencv-python
+/srv/home/shenmr/anaconda3/envs/chainercv/bin/pip install Pillow
+
+# run the training scripts
+python train.py
+