3 # dyncnn is a deep-learning algorithm for the prediction of
4 # interacting object dynamics
6 # Copyright (c) 2016 Idiap Research Institute, http://www.idiap.ch/
7 # Written by Francois Fleuret <francois.fleuret@idiap.ch>
9 # This file is part of dyncnn.
11 # dyncnn is free software: you can redistribute it and/or modify it
12 # under the terms of the GNU General Public License version 3 as
13 # published by the Free Software Foundation.
15 # dyncnn is distributed in the hope that it will be useful, but
16 # WITHOUT ANY WARRANTY; without even the implied warranty of
17 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18 # General Public License for more details.
20 # You should have received a copy of the GNU General Public License
21 # along with dyncnn. If not, see <http://www.gnu.org/licenses/>.
23 # This script creates the synthetic data-set for shape collision
28 [[ "${TORCH_NB_THREADS}" ]] || echo "You can set \$TORCH_NB_THREADS to the proper value (default 1)."
29 [[ "${TORCH_USE_GPU}" ]] || echo "You can set \$TORCH_USE_GPU to 'yes' or 'no' (default 'no')."
30 [[ "${DYNCNN_DATA_DIR}" ]] || DYNCNN_DATA_DIR="./data/10p-mg"
32 [[ "${DYNCNN_RUNDIR}" ]] || DYNCNN_RUNDIR="./results"
34 ######################################################################
35 # Create the data-set if the directory does not exist
37 if [[ ! -d "${DYNCNN_DATA_DIR}" ]]; then
39 ***************************************************************************
41 ***************************************************************************
45 mkdir -p "${DYNCNN_DATA_DIR}"
46 # 17 frames every 16 is two frames: t+0, t+16
49 --multi_grasp --every_nth 16 --nb_frames 17 \
50 --dir "${DYNCNN_DATA_DIR}"
53 ######################################################################
54 # Train the model (takes 15h on a GTX 1080 with cuda 8.0, cudnn 5.1,
57 if [[ ! -f "${DYNCNN_RUNDIR}"/model_1000.t7 ]]; then
59 ***************************************************************************
60 Train the model (should take a while)
61 ***************************************************************************
63 ./dyncnn.lua -rundir "${DYNCNN_RUNDIR}"
66 ######################################################################
67 # Create the images of internal activations using the current.t7 in
71 ***************************************************************************
72 Save the internal activation images
73 ***************************************************************************
77 ./dyncnn.lua -rundir "${DYNCNN_RUNDIR}" -noLog -exampleInternals "${n}"
80 ######################################################################
81 # Plot the loss curves if gnuplot is here
83 if [[ $(which gnuplot) ]]; then
85 ***************************************************************************
87 ***************************************************************************
90 TERMINAL="pdfcairo color transparent enhanced font \"Times,14\""
94 set terminal ${TERMINAL}
95 set output "${DYNCNN_RUNDIR}/losses.${EXTENSION}"
99 set xlabel "Number of epochs"
101 plot '< grep "LOSS " "${DYNCNN_RUNDIR}"/log' using 4:6 with l lw 3 lc rgb '#c0c0ff' title 'Validation loss',\
102 '< grep "LOSS " "${DYNCNN_RUNDIR}"/log' using 4:5 with l lw 1 lc rgb '#000000' title 'Train loss'