Hi,

Running the following command

  --env Rope \
  --pstep 2 \
  --g_dim 32 \
  --len_seq 64 \
  --I_factor 10 \
  --fit_type structured \
  --fit_num 8 \
  --eval_set demo \
  --baseline

I get the following log

Loading chipmunk for Darwin (64bit) [/Users/stephentu/anaconda3/lib/python3.7/site-packages/pymunk/libchipmunk.dylib]
===== Experiment Configuration =====
env: Rope
dt: 0.02
pstep: 2
nf_relation: 120
nf_particle: 100
nf_effect: 100
g_dim: 32
fit_type: structured
attr_dim: 2
state_dim: 4
action_dim: 1
relation_dim: 8
baseline: True
baseline_order: 3
dataf: data/data_Rope
regular_data: 0
num_workers: 10
gen_data: 0
gen_stat: 1
group_size: 25
outf: dump_Rope/train_Rope_KoopmanBaseline_demo
lr: 0.0001
batch_size: 8
grad_clip: 5.0
n_epoch: 1000
beta1: 0.9
log_per_iter: 100
ckp_per_iter: 1000
resume_epoch: -1
resume_iter: -1
lambda_loss_metric: 0.3
len_seq: 64
I_factor: 10.0
fit_num: 8
eval: 0
evalf: dump_Rope/eval_Rope_KoopmanBaseline_demo
eval_type: koopman
eval_epoch: -1
eval_iter: -1
eval_set: demo
shootf: dump_Rope/shoot_Rope_KoopmanBaseline_demo
optim_iter_init: 100
optim_iter: 10
optim_type: qp
feedback: 1
shoot_set: valid
roll_start: 0
roll_step: 40
shoot_epoch: -1
shoot_iter: -1
data_names: ['attrs', 'states', 'actions']
n_rollout: 10000
train_valid_ratio: 0.9
time_step: 101
param_dim: 5
n_splits: 5
num_obj_range: [5, 6, 7, 8, 9]
extra_num_obj_range: [10, 11, 12, 13, 14]
act_scale: 2.0
demo: True
tmpf: dump_Rope/tmp
stat_path: data/data_Rope/stat_demo.h5
====================================
Load stored dataset statistics from data/data_Rope/stat_demo.h5!

=== Forward Simulation on Example 0 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/0.pred.avi

=== Forward Simulation on Example 25 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/25.pred.avi

=== Forward Simulation on Example 50 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/50.pred.avi

=== Forward Simulation on Example 75 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/75.pred.avi

=== Forward Simulation on Example 100 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/100.pred.avi

=== Forward Simulation on Example 125 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/125.pred.avi

=== Forward Simulation on Example 150 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/150.pred.avi

=== Forward Simulation on Example 175 ===
Save video as dump_Rope/eval_Rope_KoopmanBaseline_demo/175.pred.avi

However when I open the *.avi files, the videos are just a white canvas (no rope is visible). I tried opening them both in Quicktime and VLC.

A dump of my conda list is here: https://gist.github.com/stephentu/8f06f674905c2cb885708cbd97ec503a

Any tips on how to debug this? Thanks

So I can build on top of your project. Thanks!

In pymunk6.0.0, Vec2d no longer accepts objects that have .x and .y properties. Vec2d((x,y)) should be rewrite as Vec2d(x, y)

Hi, Yunzhu, I run the following command in my windows computer with some bug. Do you know how to fix it. Thanks advance.

(base) C:\Users\v-qunxizhu\OneDrive - Microsoft\Desktop\zqx\code\CompositionalKoopmanOperators-master\CompositionalKoopmanOperators-master>python eval.py --env Rope --pstep 2 --g_dim 32 --len_seq 64 --I_factor 10 --fit_type structured --fit_num 8 --eval_set demo
===== Experiment Configuration =====
env: Rope
dt: 0.02
pstep: 2
nf_relation: 120
nf_particle: 100
nf_effect: 100
g_dim: 32
fit_type: structured
attr_dim: 2
state_dim: 4
action_dim: 1
relation_dim: 8
baseline: False
baseline_order: 3
dataf: data/data_Rope
regular_data: 0
num_workers: 10
gen_data: 0
gen_stat: 1
group_size: 25
outf: dump_Rope/train_Rope_CKO_demo
lr: 0.0001
batch_size: 8
grad_clip: 5.0
n_epoch: 1000
beta1: 0.9
log_per_iter: 100
ckp_per_iter: 1000
resume_epoch: -1
resume_iter: -1
lambda_loss_metric: 0.3
len_seq: 64
I_factor: 10.0
fit_num: 8
eval: 0
evalf: dump_Rope/eval_Rope_CKO_demo
eval_type: koopman
eval_epoch: -1
eval_iter: -1
eval_set: demo
shootf: dump_Rope/shoot_Rope_CKO_demo
optim_iter_init: 100
optim_iter: 10
optim_type: qp
feedback: 1
shoot_set: valid
roll_start: 0
roll_step: 40
shoot_epoch: -1
shoot_iter: -1
data_names: ['attrs', 'states', 'actions']
n_rollout: 10000
train_valid_ratio: 0.9
time_step: 101
param_dim: 5
n_splits: 5
num_obj_range: [5, 6, 7, 8, 9]
extra_num_obj_range: [10, 11, 12, 13, 14]
act_scale: 2.0
demo: True
tmpf: dump_Rope/tmp
stat_path: data/data_Rope/stat_demo.h5

Load stored dataset statistics from data/data_Rope/stat_demo.h5!
The syntax of the command is incorrect.
Loading saved checkpoint from dump_Rope/train_Rope_CKO_demo\net_best.pth

=== Forward Simulation on Example 0 ===
Save video as dump_Rope/eval_Rope_CKO_demo\0.pred.avi
Save images to dump_Rope/eval_Rope_CKO_demo\0.pred_img
The syntax of the command is incorrect.
Traceback (most recent call last):
File "eval.py", line 197, in
eval(roll_idx)
File "eval.py", line 182, in eval
engine.render(states_pred, seq_data[2], param, act_scale=args.act_scale, video=True, image=True,
File "C:\Users\v-qunxizhu\OneDrive - Microsoft\Desktop\zqx\code\CompositionalKoopmanOperators-master\CompositionalKoopmanOperators-master\physics_engine.py", line 275, in render
frame = frame.reshape(fig.canvas.get_width_height()[::-1] + (3,))
ValueError: cannot reshape array of size 3686400 into shape (480,640,3)