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  1. .gitattributes +34 -0
  2. 1rhki7g4/episode_rosbags/aligned_depth_to_color_K.npy +3 -0
  3. 1rhki7g4/episode_rosbags/cam_tf_world.npy +3 -0
  4. 1rhki7g4/episode_rosbags/color_K.npy +3 -0
  5. 1rhki7g4/episode_rosbags/depth_K.npy +3 -0
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  22. aq8qih16/episode_rosbags/aligned_depth_to_color_K.npy +3 -0
  23. aq8qih16/episode_rosbags/cam_tf_world.npy +3 -0
  24. aq8qih16/episode_rosbags/color_K.npy +3 -0
  25. aq8qih16/episode_rosbags/depth_K.npy +3 -0
  26. aq8qih16/eval_robot.log +12 -0
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  35. aq8qih16/wandb/run-20250121_215627-aq8qih16/files/code/FISH/eval_robot.py +606 -0
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+ _target_: agent.encoder.ContextInputConfig
697
+ use_color: false
698
+ use_depth: false
699
+ mask_input_dict:
700
+ _target_: agent.encoder.MaskInputDict
701
+ enable: false
702
+ representation: channels
703
+ mask_list:
704
+ - EE_obj_mask
705
+ crop_input_config:
706
+ _target_: agent.encoder.CropInputConfig
707
+ color_crop_type: null
708
+ depth_crop_type: null
709
+ segmask_crop_type: null
710
+ crop_hw:
711
+ - 144
712
+ - 144
713
+ crop_down_offset: 48
714
+ add_crop_binary_mask: false
715
+ add_coord_conv_map: false
716
+ mask_soft_approx_scheduler_config:
717
+ _target_: agent.encoder.MaskSoftApproxSchedulerConfig
718
+ num_steps: 40000
719
+ initial_value: 10.0
720
+ final_value: 1000.0
721
+ interpolation_scheme: cosine
722
+ use_contact_map: true
723
+ use_sdf_maps: true
724
+ use_normals_maps: true
725
+ which_objects: both
726
+ grasped_dtc_max_value: 0.2
727
+ env_dtc_max_value: 0.4
728
+ grasped_normals_mask_max_dtc_value: 0.2
729
+ env_normals_mask_max_dtc_value: 0.4
730
+ clamp_dtc: true
731
+ max_contact_prob: 0.1
732
+ mask_normals_within_sdf: true
733
+ dtc_adaptive_normalization: false
734
+ adaptive_normals_mask: true
735
+ max_depth: 2.0
736
+ image_shape:
737
+ - 13
738
+ - 180
739
+ - 240
740
+ learnable_contact_preprocess_params: true
741
+ learning_rate: 0.0001
742
+ weight_decay: 0.0
743
+ contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9
744
+ zero_centered: false
745
+ crop_distractors_tlhw:
746
+ - 32
747
+ - 68
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+ - 174
749
+ - 174
750
+ true_action_history: false
751
+ num_train_frames_bc:
752
+ desc: null
753
+ value: 50000
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+ num_train_frames_drq:
755
+ desc: null
756
+ value: 1100000
757
+ stddev_schedule_drq:
758
+ desc: null
759
+ value: linear(1.0,0.1,100000)
760
+ task_name:
761
+ desc: null
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+ value: FrankaInsertion-v1
763
+ num_train_frames_vinn:
764
+ desc: null
765
+ value: 25000
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+ num_train_frames_diffusion:
767
+ desc: null
768
+ value: 1000000
769
+ num_train_epochs_bc:
770
+ desc: null
771
+ value: 5000
772
+ num_train_epochs_diffusion:
773
+ desc: null
774
+ value: 15000
775
+ validate_every_epochs_bc:
776
+ desc: null
777
+ value: 5
778
+ validate_every_epochs_diffusion:
779
+ desc: null
780
+ value: 250
781
+ validate_diffusion_on_action_loss_every_epochs:
782
+ desc: null
783
+ value: 250
784
+ train_eval_diffusion_on_action_loss_every_epochs:
785
+ desc: null
786
+ value: 250
787
+ check_topk_every_epochs:
788
+ desc: null
789
+ value: 5
790
+ check_topk_every_epochs_diffusion:
791
+ desc: null
792
+ value: 250
793
+ save_snapshot_every_epochs_diffusion:
794
+ desc: null
795
+ value: 1500
796
+ x_limit:
797
+ desc: null
798
+ value:
799
+ - 0.2
800
+ - 0.7
801
+ y_limit:
802
+ desc: null
803
+ value:
804
+ - -0.4
805
+ - 0.4
806
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807
+ desc: null
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+ value:
809
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810
+ - 0.55
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+ home_displacement:
812
+ desc: null
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+ value:
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+ - 0.55
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+ - 0.0
816
+ - 0.55
817
+ - 180.0
818
+ - 0.0
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+ - 0.0
820
+ enable_gripper:
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+ desc: null
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+ value: true
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+ start_with_gripper_open:
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+ desc: null
825
+ value: true
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+ offset_mask:
827
+ desc: null
828
+ value:
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+ - 1
830
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+ - 1
832
+ - 1
833
+ - 1
834
+ - 1
835
+ path_to_depth_extrinsics:
836
+ desc: null
837
+ value: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy
838
+ test:
839
+ desc: null
840
+ value:
841
+ username: leonmkim
842
+ hostname: grasp-login1
843
+ name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
844
+ root_dir: ~/fish_leon
845
+ expert_dataset_dirpath: ~/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
846
+ expert_dataset: ~/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
847
+ semantic_demo_grouping_name: semantic_demo_grouping.yaml
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+ semantic_demo_grouping: ~/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/semantic_demo_grouping.yaml
849
+ include_groups_list: all
850
+ batch_size: 128
851
+ store_dataset_in_memory: false
852
+ use_tb: true
853
+ local_snapshot_root_dir: /mnt/bighdd/fish_contact_backup
854
+ local_snapshot_dir: /mnt/bighdd/fish_contact_backup/exp_local/frankagym_pixels/FrankaInsertion-v1
855
+ resume_wandb_run: false
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+ feature_type:
857
+ desc: null
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+ value: 180x240_crpdstlhw24x51x130x130_1_D_2.0_msk_channels_EE_obj_mask_cntct_0.1_DTC_clmpd_lrnbl_nrmls_DTCmask_adpt_lrnbl_both_lr_0.0001_wd_0.0_local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9_acthist_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1
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+ save_buffer:
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+ desc: null
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+ value: true
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+ num_eval:
863
+ desc: null
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+ value: 5
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+ random_start:
866
+ desc: null
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+ value: false
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+ eval_starts:
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+ desc: null
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+ value: /home/leonmkim/fish_leon/FISH/eval_starts/frankagym_pixels/FrankaInsertion-v1
871
+ num_valid_demos:
872
+ desc: null
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+ value: null
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+ load_checkpoint:
875
+ desc: null
876
+ value: true
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+ checkpoint_epoch:
878
+ desc: null
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+ value: 7500
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+ load_residual_weight:
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+ desc: null
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+ value: false
883
+ checkpoint_root_dir:
884
+ desc: null
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+ value: /home/leonmkim/fish_leon/FISH
886
+ checkpoint_weight_dir:
887
+ desc: null
888
+ value: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2
889
+ residual_weight:
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+ desc: null
891
+ value: /home/leonmkim/fish_leon/FISH/weights/frankagym_pixels/FrankaInsertion-v1/weight.pt
892
+ final_experiment_dir:
893
+ desc: null
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+ value: ./exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/1rhki7g4
895
+ _wandb:
896
+ desc: null
897
+ value:
898
+ code_path: code/FISH/eval_robot.py
899
+ python_version: 3.10.14
900
+ cli_version: 0.17.5
901
+ framework: torch
902
+ is_jupyter_run: false
903
+ is_kaggle_kernel: false
904
+ start_time: 1737516138
905
+ t:
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+ 1:
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+ - 1
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+ - 41
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+ - 49
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+ - 50
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+ - 55
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+ - 83
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+ 2:
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+ - 1
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+ - 41
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+ - 49
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+ - 50
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+ - 55
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+ - 83
920
+ 3:
921
+ - 14
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+ - 16
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+ - 23
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+ - 35
925
+ - 62
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+ 4: 3.10.14
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+ 5: 0.17.5
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+ 8:
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+ - 5
930
+ 13: linux-x86_64
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+ grasped_obj_name:
932
+ desc: null
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+ value: greece
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+ left_book_slot:
935
+ desc: null
936
+ value: twodim
1rhki7g4/wandb/run-20250121_222218-1rhki7g4/files/diff.patch ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ diff --git a/FISH/cfgs/config_eval.yaml b/FISH/cfgs/config_eval.yaml
2
+ index bb5fa99..c37123f 100644
3
+ --- a/FISH/cfgs/config_eval.yaml
4
+ +++ b/FISH/cfgs/config_eval.yaml
5
+ @@ -82,7 +82,7 @@ contact_estimation_model_ckpt_path: '~/fish_leon/contact_estimation/artifacts/17
6
+
7
+ # Number of evaluation trajectories
8
+ # num_eval: 10
9
+ -num_eval: 20
10
+ +num_eval: 5
11
+
12
+ debug_timestamps: False
13
+ open_loop: False
14
+ @@ -144,9 +144,9 @@ load_checkpoint: ${agent.load_checkpoint}
15
+ # wandb_run_id: '3465_2' # seed 2
16
+
17
+ # crp_D+mask+contact+act history
18
+ -wandb_run_id: '4295_0'
19
+ +# wandb_run_id: '4295_0'
20
+ # wandb_run_id: '4295_1' # seed 1
21
+ -# wandb_run_id: '4295_2' # seed 2
22
+ +wandb_run_id: '4295_2' # seed 2
23
+
24
+ # RGBD+mask+act history
25
+ # wandb_run_id: '1009_1' # seed 1
1rhki7g4/wandb/run-20250121_222218-1rhki7g4/files/requirements.txt ADDED
@@ -0,0 +1,340 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Cython==3.0.10
2
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+ rostest==1.16.0
242
+ rostopic==1.16.0
243
+ rosunit==1.15.8
244
+ roswtf==1.16.0
245
+ rpds-py==0.19.1
246
+ rqt-console==0.4.12
247
+ rqt-image-view==0.4.17
248
+ rqt-logger-level==0.4.12
249
+ rqt-moveit==0.5.11
250
+ rqt-reconfigure==0.5.5
251
+ rqt-robot-dashboard==0.5.8
252
+ rqt-robot-monitor==0.5.15
253
+ rqt-runtime-monitor==0.5.10
254
+ rqt-rviz==0.7.0
255
+ rqt-tf-tree==0.6.4
256
+ rqt_action==0.4.9
257
+ rqt_bag==0.5.1
258
+ rqt_bag_plugins==0.5.1
259
+ rqt_dep==0.4.12
260
+ rqt_graph==0.4.14
261
+ rqt_gui==0.5.3
262
+ rqt_gui_py==0.5.3
263
+ rqt_launch==0.4.9
264
+ rqt_msg==0.4.10
265
+ rqt_nav_view==0.5.7
266
+ rqt_plot==0.4.13
267
+ rqt_pose_view==0.5.11
268
+ rqt_publisher==0.4.10
269
+ rqt_py_common==0.5.3
270
+ rqt_py_console==0.4.10
271
+ rqt_robot_steering==0.5.12
272
+ rqt_service_caller==0.4.10
273
+ rqt_shell==0.4.11
274
+ rqt_srv==0.4.9
275
+ rqt_top==0.4.10
276
+ rqt_topic==0.4.13
277
+ rqt_web==0.4.10
278
+ rsa==4.9
279
+ ruff==0.5.4
280
+ rviz==1.14.25
281
+ safetensors==0.4.3
282
+ scikit-image==0.24.0
283
+ scikit-video==1.1.11
284
+ scipy==1.14.0
285
+ seaborn==0.13.2
286
+ sensor-msgs==1.13.1
287
+ sentry-sdk==2.11.0
288
+ setproctitle==1.3.3
289
+ setuptools==65.5.0
290
+ shapely==2.0.5
291
+ signature_dispatch==1.0.1
292
+ six==1.16.0
293
+ smach-ros==2.5.2
294
+ smach==2.5.2
295
+ smclib==1.8.6
296
+ smmap==5.0.1
297
+ sniffio==1.3.1
298
+ soupsieve==2.5
299
+ std-msgs==0.5.13.post0
300
+ submitit==1.5.1
301
+ svg.path==6.3
302
+ sympy==1.13.1
303
+ tensorboard-data-server==0.7.2
304
+ tensorboard==2.14.0
305
+ termcolor==2.4.0
306
+ tf-conversions==1.13.2
307
+ tf2-geometry-msgs==0.7.7
308
+ tf2-kdl==0.7.7
309
+ tf2-msgs==0.7.2.post3
310
+ tf2-py==0.7.7
311
+ tf2-ros==0.6.5
312
+ tf2-ros==0.7.7
313
+ tf2_py==0.6.5.post1
314
+ tf==1.13.2
315
+ tifffile==2024.7.24
316
+ tomli==2.0.1
317
+ topic-tools==1.16.0
318
+ torch==2.4.0
319
+ torchaug==0.5.2
320
+ torchmetrics==1.4.0.post0
321
+ torchvision==0.19.0
322
+ tqdm==4.66.4
323
+ trimesh==4.4.3
324
+ triton==3.0.0
325
+ typeguard==3.0.2
326
+ typing_extensions==4.12.2
327
+ tzdata==2024.1
328
+ urchin==0.0.27
329
+ urllib3==2.2.2
330
+ vecrec==0.3.1
331
+ vhacdx==0.0.8.post1
332
+ wandb==0.17.5
333
+ wheel==0.43.0
334
+ xacro==1.14.18
335
+ xatlas==0.0.9
336
+ xxhash==3.4.1
337
+ yarl==1.9.4
338
+ zarr==2.18.2
339
+ zipp==3.19.2
340
+ zstandard==0.23.0
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1rhki7g4/wandb/run-20250121_222218-1rhki7g4/run-1rhki7g4.wandb ADDED
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7dl7quog/.hydra/config.yaml ADDED
@@ -0,0 +1,352 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ root_dir: /home/${oc.env:USER}/fish_leon
2
+ nstep: 3
3
+ seed: 41
4
+ dataset_shuffle_seed: ${seed}
5
+ device: cuda
6
+ save_video: true
7
+ save_buffer: true
8
+ use_tb: true
9
+ baseline: false
10
+ use_wandb: true
11
+ eval: true
12
+ process_contact_features: ${eval}
13
+ obs_type: pixels
14
+ use_color: true
15
+ use_depth: true
16
+ use_masks: false
17
+ mask_list:
18
+ - EE_obj_mask
19
+ mask_representation: channels
20
+ crop_hw:
21
+ - 144
22
+ - 144
23
+ crop_down_offset: 48
24
+ color_crop_type: null
25
+ depth_crop_type: null
26
+ segmask_crop_type: null
27
+ add_crop_binary_mask: false
28
+ add_coord_conv_map: false
29
+ use_context_color: false
30
+ use_context_depth: false
31
+ use_context_segmask: false
32
+ context_color_crop_type: null
33
+ context_depth_crop_type: null
34
+ context_segmask_crop_type: null
35
+ context_add_crop_binary_mask: false
36
+ context_add_coord_conv_map: false
37
+ use_contact_map: false
38
+ use_sdf_maps: false
39
+ use_normals_maps: false
40
+ which_objects: both
41
+ max_contact_prob: 0.1
42
+ max_depth: 2.0
43
+ grasped_dtc_max_value: 0.105
44
+ env_dtc_max_value: 0.425
45
+ grasped_normals_mask_max_dtc_value: 0.105
46
+ env_normals_mask_max_dtc_value: 0.425
47
+ clamp_dtc: true
48
+ dtc_adaptive_normalization: false
49
+ mask_normals_within_sdf: true
50
+ adaptive_normals_mask: true
51
+ learnable_contact_preprocess_params: false
52
+ contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_ctxt_seed_183386_epoch_9
53
+ contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
54
+ num_eval: 5
55
+ debug_timestamps: false
56
+ open_loop: false
57
+ action_trajectories: true
58
+ stop_after_action: false
59
+ interpolation_frequency: 25
60
+ policy_frequency: 5
61
+ wait_for_new_camera_frames: true
62
+ random_start: false
63
+ eval_starts: ${root_dir}/FISH/eval_starts/${suite.name}_${obs_type}/${task_name}
64
+ train_demo_idxs_list_or_num: null
65
+ num_valid_demos: null
66
+ val_num_groups: 3
67
+ name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
68
+ expert_dataset_dirpath: ${root_dir}/FISH/expert_demos/${suite.name}/${task_name}/${name_of_expert_demo}
69
+ expert_dataset: ${expert_dataset_dirpath}/demos.zarr
70
+ action_key: ${oc.if_else:${action_trajectories}, 'action_trajectory_${interpolation_frequency}hz',
71
+ 'action'}
72
+ semantic_demo_grouping_name: semantic_demo_grouping.yaml
73
+ semantic_demo_grouping: ${expert_dataset_dirpath}/${semantic_demo_grouping_name}
74
+ expert_dataset_config: ${expert_dataset_dirpath}/demo_config.yaml
75
+ bc_regularize: false
76
+ bc_weight_type: qfilter
77
+ load_checkpoint: ${agent.load_checkpoint}
78
+ wandb_run_id: '4295_2'
79
+ true_action_history: false
80
+ wandb_notes: null
81
+ checkpoint_epoch: 7500
82
+ load_residual_weight: false
83
+ checkpoint_root_dir: /home/${oc.env:USER}/fish_leon/FISH
84
+ checkpoint_weight_dir: ${checkpoint_root_dir}/exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
85
+ residual_weight: ${root_dir}/FISH/weights/${suite.name}_${obs_type}/${task_name}/weight.pt
86
+ experiment_dir: ./exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
87
+ final_experiment_dir: ${experiment_dir}/${oc.generate_run_id:}
88
+ agent:
89
+ _target_: agent.diffusion_policy.DiffusionPolicyAgent
90
+ name: diffusion_policy
91
+ load_checkpoint: ${eval}
92
+ device: ${device}
93
+ n_obs_steps: ${.config.policy_cfg.n_obs_steps}
94
+ suite_name: ${suite.name}
95
+ obs_type: ${obs_type}
96
+ enable_arm: ${eval}
97
+ enable_camera: ${eval}
98
+ use_tb: ${use_tb}
99
+ desired_image_shape:
100
+ - 13
101
+ - 180
102
+ - 240
103
+ orig_cam_shape:
104
+ - 3
105
+ - 240
106
+ - 320
107
+ config:
108
+ _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
109
+ compile: false
110
+ device: ${device}
111
+ cam_resize_shape: ${agent.desired_image_shape}
112
+ orig_cam_shape: ${agent.orig_cam_shape}
113
+ policy_frequency: ${policy_frequency}
114
+ interpolation_frequency: ${interpolation_frequency}
115
+ policy_cfg:
116
+ _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
117
+ n_obs_steps: 1
118
+ horizon: 36
119
+ n_action_steps: ${agent.config.policy_cfg.horizon}
120
+ input_shapes:
121
+ observation.image: ${agent.config.cam_resize_shape}
122
+ context_observation.image: ${agent.config.cam_resize_shape}
123
+ observation.state:
124
+ - 8
125
+ observation.action_history:
126
+ - 7
127
+ output_shapes:
128
+ action:
129
+ - 7
130
+ input_normalization_modes:
131
+ observation.image: mean_std
132
+ observation.state: min_max
133
+ observation.action_history: min_max
134
+ output_normalization_modes:
135
+ action: min_max
136
+ vision_backbone: resnet18
137
+ crop_distractors_tlhw: null
138
+ pretrained_backbone_weights: null
139
+ transforms:
140
+ - _target_: torchaug.transforms.RandomAffine
141
+ degrees:
142
+ - -5
143
+ - 5
144
+ translate:
145
+ - 0.05
146
+ - 0.05
147
+ batch_transform: true
148
+ num_chunks: -1
149
+ batch_inplace: true
150
+ - _target_: torchaug.transforms.RandomColorJitter
151
+ brightness: 0.3
152
+ contrast: 0.4
153
+ saturation: 0.5
154
+ hue: 0.08
155
+ batch_transform: true
156
+ num_chunks: -1
157
+ batch_inplace: true
158
+ use_group_norm: true
159
+ spatial_softmax_num_keypoints: 32
160
+ action_history_encoder_config:
161
+ _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
162
+ in_channels: 7
163
+ out_channels: 32
164
+ history_length: ${agent.config.policy_cfg.n_action_steps}
165
+ kernel_size: ${agent.config.policy_cfg.kernel_size}
166
+ downsample_kernel_size: 3
167
+ downsample_stride: 2
168
+ downsample_padding: 1
169
+ down_dims:
170
+ - 256
171
+ - 512
172
+ - 1024
173
+ kernel_size: 5
174
+ n_groups: 8
175
+ diffusion_step_embed_dim: 128
176
+ use_film_scale_modulation: true
177
+ noise_scheduler_type: DDIM
178
+ beta_schedule: squaredcos_cap_v2
179
+ beta_start: 0.0001
180
+ beta_end: 0.02
181
+ prediction_type: epsilon
182
+ clip_sample: true
183
+ clip_sample_range: 1.0
184
+ num_train_timesteps: 50
185
+ num_inference_steps: 10
186
+ do_mask_loss_for_padding: false
187
+ train_cfg:
188
+ _target_: utils.TrainConfig
189
+ lr: 0.0001
190
+ lr_scheduler: cosine
191
+ lr_warmup_steps: 500
192
+ adam_betas:
193
+ - 0.95
194
+ - 0.999
195
+ adam_eps: 1.0e-08
196
+ adam_weight_decay: 1.0e-06
197
+ grad_clip_norm: 10
198
+ offline_steps: ${num_train_frames_diffusion}
199
+ use_amp: true
200
+ observation_cfg:
201
+ _target_: agent.encoder.VisualFeatureSet
202
+ use_depth: ${use_depth}
203
+ use_color: ${use_color}
204
+ mask_input_dict:
205
+ _target_: agent.encoder.MaskInputDict
206
+ enable: ${use_masks}
207
+ representation: ${mask_representation}
208
+ mask_list: ${mask_list}
209
+ crop_input_config:
210
+ _target_: agent.encoder.CropInputConfig
211
+ color_crop_type: ${color_crop_type}
212
+ depth_crop_type: ${depth_crop_type}
213
+ segmask_crop_type: ${segmask_crop_type}
214
+ crop_hw: ${crop_hw}
215
+ crop_down_offset: ${crop_down_offset}
216
+ add_crop_binary_mask: ${add_crop_binary_mask}
217
+ add_coord_conv_map: ${add_coord_conv_map}
218
+ context_input_config:
219
+ _target_: agent.encoder.ContextInputConfig
220
+ use_color: ${use_context_color}
221
+ use_depth: ${use_context_depth}
222
+ mask_input_dict:
223
+ _target_: agent.encoder.MaskInputDict
224
+ enable: ${use_context_segmask}
225
+ representation: ${mask_representation}
226
+ mask_list: ${mask_list}
227
+ crop_input_config:
228
+ _target_: agent.encoder.CropInputConfig
229
+ color_crop_type: ${context_color_crop_type}
230
+ depth_crop_type: ${context_depth_crop_type}
231
+ segmask_crop_type: ${context_segmask_crop_type}
232
+ crop_hw: ${crop_hw}
233
+ crop_down_offset: ${crop_down_offset}
234
+ add_crop_binary_mask: ${context_add_crop_binary_mask}
235
+ add_coord_conv_map: ${context_add_coord_conv_map}
236
+ mask_soft_approx_scheduler_config:
237
+ _target_: agent.encoder.MaskSoftApproxSchedulerConfig
238
+ num_steps: 40000
239
+ initial_value: 10.0
240
+ final_value: 1000.0
241
+ interpolation_scheme: constant
242
+ use_contact_map: ${use_contact_map}
243
+ use_sdf_maps: ${use_sdf_maps}
244
+ use_normals_maps: ${use_normals_maps}
245
+ which_objects: ${which_objects}
246
+ grasped_dtc_max_value: ${grasped_dtc_max_value}
247
+ env_dtc_max_value: ${env_dtc_max_value}
248
+ grasped_normals_mask_max_dtc_value: ${grasped_normals_mask_max_dtc_value}
249
+ env_normals_mask_max_dtc_value: ${env_normals_mask_max_dtc_value}
250
+ clamp_dtc: ${clamp_dtc}
251
+ max_contact_prob: ${max_contact_prob}
252
+ mask_normals_within_sdf: ${mask_normals_within_sdf}
253
+ dtc_adaptive_normalization: ${dtc_adaptive_normalization}
254
+ adaptive_normals_mask: ${adaptive_normals_mask}
255
+ max_depth: ${max_depth}
256
+ image_shape: ${agent.desired_image_shape}
257
+ learnable_contact_preprocess_params: ${learnable_contact_preprocess_params}
258
+ learning_rate: ${agent.config.train_cfg.lr}
259
+ weight_decay: 0.0
260
+ contact_model_name: ${contact_model_name}
261
+ zero_centered: false
262
+ crop_distractors_tlhw: ${agent.config.policy_cfg.crop_distractors_tlhw}
263
+ suite:
264
+ suite: frankagym
265
+ name: frankagym
266
+ frame_stack: ${agent.n_obs_steps}
267
+ action_repeat: 1
268
+ discount: 0.99
269
+ hidden_dim: 1024
270
+ num_train_frames: 2010
271
+ num_seed_frames: 260
272
+ num_train_epochs: 5000
273
+ validate_every_epochs: 100
274
+ validate_diffusion_on_action_loss_every_epochs: 500
275
+ train_eval_diffusion_on_action_loss_every_epochs: 500
276
+ check_topk_every_epochs: 10
277
+ save_snapshot_every_epochs: 5000
278
+ eval_every_frames: 2000
279
+ num_eval_episodes: 5
280
+ save_snapshot: true
281
+ wait_for_user_to_start_episode: true
282
+ task_make_fn:
283
+ _target_: suite.frankagym.make
284
+ name: ${task_name}
285
+ height: 240
286
+ width: 320
287
+ frame_stack: ${suite.frame_stack}
288
+ action_repeat: ${suite.action_repeat}
289
+ seed: ${seed}
290
+ enable_arm: ${agent.enable_arm}
291
+ enable_gripper: ${enable_gripper}
292
+ start_with_gripper_open: ${start_with_gripper_open}
293
+ enable_camera: ${agent.enable_camera}
294
+ path_to_depth_extrinsics: ${path_to_depth_extrinsics}
295
+ contact_estimation_model_ckpt_path: ${contact_estimation_model_ckpt_path}
296
+ x_limit: ${x_limit}
297
+ y_limit: ${y_limit}
298
+ z_limit: ${z_limit}
299
+ device: ${device}
300
+ interpolation_frequency: ${interpolation_frequency}
301
+ policy_frequency: ${policy_frequency}
302
+ debug_timestamps: ${debug_timestamps}
303
+ stop_after_action: ${stop_after_action}
304
+ open_loop: ${open_loop}
305
+ wait_for_new_camera_frames: ${wait_for_new_camera_frames}
306
+ action_key: ${action_key}
307
+ action_trajectory_horizon: ${agent.config.policy_cfg.horizon}
308
+ action_trajectories: ${action_trajectories}
309
+ path_to_zarr_dataset: ${expert_dataset}
310
+ agent_policy_cfg: ???
311
+ true_action_history: ${true_action_history}
312
+ num_train_frames_bc: 50000
313
+ num_train_frames_drq: 1100000
314
+ stddev_schedule_drq: linear(1.0,0.1,100000)
315
+ task_name: FrankaInsertion-v1
316
+ num_train_frames_vinn: 25000
317
+ num_train_frames_diffusion: 1000000
318
+ num_train_epochs_bc: 5000
319
+ num_train_epochs_diffusion: 5000
320
+ validate_every_epochs_bc: 5
321
+ validate_every_epochs_diffusion: 25
322
+ validate_diffusion_on_action_loss_every_epochs: 50
323
+ train_eval_diffusion_on_action_loss_every_epochs: 500
324
+ check_topk_every_epochs: 5
325
+ check_topk_every_epochs_diffusion: ${validate_diffusion_on_action_loss_every_epochs}
326
+ save_snapshot_every_epochs_diffusion: 5000
327
+ x_limit:
328
+ - 0.2
329
+ - 0.7
330
+ y_limit:
331
+ - -0.4
332
+ - 0.4
333
+ z_limit:
334
+ - -0.05
335
+ - 0.55
336
+ home_displacement:
337
+ - 0.55
338
+ - 0.0
339
+ - 0.55
340
+ - 180.0
341
+ - 0.0
342
+ - 0.0
343
+ enable_gripper: true
344
+ start_with_gripper_open: true
345
+ offset_mask:
346
+ - 1
347
+ - 1
348
+ - 1
349
+ - 1
350
+ - 1
351
+ - 1
352
+ path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy
7dl7quog/.hydra/hydra.yaml ADDED
@@ -0,0 +1,169 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ hydra:
2
+ run:
3
+ dir: ${final_experiment_dir}
4
+ sweep:
5
+ dir: ${final_experiment_dir}
6
+ subdir: ${hydra.job.num}
7
+ launcher:
8
+ submitit_folder: ${final_experiment_dir}/.slurm
9
+ timeout_min: 60
10
+ cpus_per_task: null
11
+ gpus_per_node: null
12
+ tasks_per_node: 1
13
+ mem_gb: null
14
+ nodes: 1
15
+ name: ${hydra.job.name}
16
+ stderr_to_stdout: false
17
+ _target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
18
+ sweeper:
19
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
20
+ max_batch_size: null
21
+ params: null
22
+ help:
23
+ app_name: ${hydra.job.name}
24
+ header: '${hydra.help.app_name} is powered by Hydra.
25
+
26
+ '
27
+ footer: 'Powered by Hydra (https://hydra.cc)
28
+
29
+ Use --hydra-help to view Hydra specific help
30
+
31
+ '
32
+ template: '${hydra.help.header}
33
+
34
+ == Configuration groups ==
35
+
36
+ Compose your configuration from those groups (group=option)
37
+
38
+
39
+ $APP_CONFIG_GROUPS
40
+
41
+
42
+ == Config ==
43
+
44
+ Override anything in the config (foo.bar=value)
45
+
46
+
47
+ $CONFIG
48
+
49
+
50
+ ${hydra.help.footer}
51
+
52
+ '
53
+ hydra_help:
54
+ template: 'Hydra (${hydra.runtime.version})
55
+
56
+ See https://hydra.cc for more info.
57
+
58
+
59
+ == Flags ==
60
+
61
+ $FLAGS_HELP
62
+
63
+
64
+ == Configuration groups ==
65
+
66
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
67
+ to command line)
68
+
69
+
70
+ $HYDRA_CONFIG_GROUPS
71
+
72
+
73
+ Use ''--cfg hydra'' to Show the Hydra config.
74
+
75
+ '
76
+ hydra_help: ???
77
+ hydra_logging:
78
+ version: 1
79
+ formatters:
80
+ simple:
81
+ format: '[%(asctime)s][HYDRA] %(message)s'
82
+ handlers:
83
+ console:
84
+ class: logging.StreamHandler
85
+ formatter: simple
86
+ stream: ext://sys.stdout
87
+ root:
88
+ level: INFO
89
+ handlers:
90
+ - console
91
+ loggers:
92
+ logging_example:
93
+ level: DEBUG
94
+ disable_existing_loggers: false
95
+ job_logging:
96
+ version: 1
97
+ formatters:
98
+ simple:
99
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
100
+ handlers:
101
+ console:
102
+ class: logging.StreamHandler
103
+ formatter: simple
104
+ stream: ext://sys.stdout
105
+ file:
106
+ class: logging.FileHandler
107
+ formatter: simple
108
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
109
+ root:
110
+ level: INFO
111
+ handlers:
112
+ - console
113
+ - file
114
+ disable_existing_loggers: false
115
+ env: {}
116
+ mode: RUN
117
+ searchpath: []
118
+ callbacks: {}
119
+ output_subdir: .hydra
120
+ overrides:
121
+ hydra:
122
+ - hydra.mode=RUN
123
+ task:
124
+ - agent=diffusion
125
+ - suite=frankagym
126
+ - suite/frankagym_task@_global_=insertion
127
+ job:
128
+ name: eval_policy
129
+ chdir: true
130
+ override_dirname: agent=diffusion,suite/frankagym_task@_global_=insertion,suite=frankagym
131
+ id: ???
132
+ num: ???
133
+ config_name: config_eval
134
+ env_set: {}
135
+ env_copy: []
136
+ config:
137
+ override_dirname:
138
+ kv_sep: '='
139
+ item_sep: ','
140
+ exclude_keys: []
141
+ runtime:
142
+ version: 1.3.2
143
+ version_base: '1.1'
144
+ cwd: /home/leonmkim/fish_leon/FISH
145
+ config_sources:
146
+ - path: hydra.conf
147
+ schema: pkg
148
+ provider: hydra
149
+ - path: /home/leonmkim/fish_leon/FISH/cfgs
150
+ schema: file
151
+ provider: main
152
+ - path: ''
153
+ schema: structured
154
+ provider: schema
155
+ output_dir: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/7dl7quog
156
+ choices:
157
+ suite: frankagym
158
+ suite/frankagym_task@_global_: insertion
159
+ agent: diffusion
160
+ hydra/env: default
161
+ hydra/callbacks: null
162
+ hydra/job_logging: default
163
+ hydra/hydra_logging: default
164
+ hydra/hydra_help: default
165
+ hydra/help: default
166
+ hydra/sweeper: basic
167
+ hydra/launcher: submitit_local
168
+ hydra/output: default
169
+ verbose: false
7dl7quog/.hydra/overrides.yaml ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ - agent=diffusion
2
+ - suite=frankagym
3
+ - suite/frankagym_task@_global_=insertion
7dl7quog/eval_policy.log ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2025-01-21 22:22:10,667][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:429: UserWarning:
2
+ The version_base parameter is not specified.
3
+ Please specify a compatability version level, or None.
4
+ Will assume defaults for version 1.1
5
+ @hydra.main(config_path='cfgs', config_name='config_eval')
6
+
7
+ [2025-01-21 22:22:10,671][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:366: UserWarning:
8
+ The version_base parameter is not specified.
9
+ Please specify a compatability version level, or None.
10
+ Will assume defaults for version 1.1
11
+ hydra.initialize(
12
+
13
+ [2025-01-21 22:22:14,626][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:415: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
14
+ payload = torch.load(f)
15
+
aq8qih16/.hydra/config.yaml ADDED
@@ -0,0 +1,352 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ root_dir: /home/${oc.env:USER}/fish_leon
2
+ nstep: 3
3
+ seed: 41
4
+ dataset_shuffle_seed: ${seed}
5
+ device: cuda
6
+ save_video: true
7
+ save_buffer: true
8
+ use_tb: true
9
+ baseline: false
10
+ use_wandb: true
11
+ eval: true
12
+ process_contact_features: ${eval}
13
+ obs_type: pixels
14
+ use_color: true
15
+ use_depth: true
16
+ use_masks: false
17
+ mask_list:
18
+ - EE_obj_mask
19
+ mask_representation: channels
20
+ crop_hw:
21
+ - 144
22
+ - 144
23
+ crop_down_offset: 48
24
+ color_crop_type: null
25
+ depth_crop_type: null
26
+ segmask_crop_type: null
27
+ add_crop_binary_mask: false
28
+ add_coord_conv_map: false
29
+ use_context_color: false
30
+ use_context_depth: false
31
+ use_context_segmask: false
32
+ context_color_crop_type: null
33
+ context_depth_crop_type: null
34
+ context_segmask_crop_type: null
35
+ context_add_crop_binary_mask: false
36
+ context_add_coord_conv_map: false
37
+ use_contact_map: false
38
+ use_sdf_maps: false
39
+ use_normals_maps: false
40
+ which_objects: both
41
+ max_contact_prob: 0.1
42
+ max_depth: 2.0
43
+ grasped_dtc_max_value: 0.105
44
+ env_dtc_max_value: 0.425
45
+ grasped_normals_mask_max_dtc_value: 0.105
46
+ env_normals_mask_max_dtc_value: 0.425
47
+ clamp_dtc: true
48
+ dtc_adaptive_normalization: false
49
+ mask_normals_within_sdf: true
50
+ adaptive_normals_mask: true
51
+ learnable_contact_preprocess_params: false
52
+ contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_ctxt_seed_183386_epoch_9
53
+ contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
54
+ num_eval: 5
55
+ debug_timestamps: false
56
+ open_loop: false
57
+ action_trajectories: true
58
+ stop_after_action: false
59
+ interpolation_frequency: 25
60
+ policy_frequency: 5
61
+ wait_for_new_camera_frames: true
62
+ random_start: false
63
+ eval_starts: ${root_dir}/FISH/eval_starts/${suite.name}_${obs_type}/${task_name}
64
+ train_demo_idxs_list_or_num: null
65
+ num_valid_demos: null
66
+ val_num_groups: 3
67
+ name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
68
+ expert_dataset_dirpath: ${root_dir}/FISH/expert_demos/${suite.name}/${task_name}/${name_of_expert_demo}
69
+ expert_dataset: ${expert_dataset_dirpath}/demos.zarr
70
+ action_key: ${oc.if_else:${action_trajectories}, 'action_trajectory_${interpolation_frequency}hz',
71
+ 'action'}
72
+ semantic_demo_grouping_name: semantic_demo_grouping.yaml
73
+ semantic_demo_grouping: ${expert_dataset_dirpath}/${semantic_demo_grouping_name}
74
+ expert_dataset_config: ${expert_dataset_dirpath}/demo_config.yaml
75
+ bc_regularize: false
76
+ bc_weight_type: qfilter
77
+ load_checkpoint: ${agent.load_checkpoint}
78
+ wandb_run_id: '4295_2'
79
+ true_action_history: false
80
+ wandb_notes: null
81
+ checkpoint_epoch: 7500
82
+ load_residual_weight: false
83
+ checkpoint_root_dir: /home/${oc.env:USER}/fish_leon/FISH
84
+ checkpoint_weight_dir: ${checkpoint_root_dir}/exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
85
+ residual_weight: ${root_dir}/FISH/weights/${suite.name}_${obs_type}/${task_name}/weight.pt
86
+ experiment_dir: ./exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
87
+ final_experiment_dir: ${experiment_dir}/${oc.generate_run_id:}
88
+ agent:
89
+ _target_: agent.diffusion_policy.DiffusionPolicyAgent
90
+ name: diffusion_policy
91
+ load_checkpoint: ${eval}
92
+ device: ${device}
93
+ n_obs_steps: ${.config.policy_cfg.n_obs_steps}
94
+ suite_name: ${suite.name}
95
+ obs_type: ${obs_type}
96
+ enable_arm: ${eval}
97
+ enable_camera: ${eval}
98
+ use_tb: ${use_tb}
99
+ desired_image_shape:
100
+ - 13
101
+ - 180
102
+ - 240
103
+ orig_cam_shape:
104
+ - 3
105
+ - 240
106
+ - 320
107
+ config:
108
+ _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
109
+ compile: false
110
+ device: ${device}
111
+ cam_resize_shape: ${agent.desired_image_shape}
112
+ orig_cam_shape: ${agent.orig_cam_shape}
113
+ policy_frequency: ${policy_frequency}
114
+ interpolation_frequency: ${interpolation_frequency}
115
+ policy_cfg:
116
+ _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
117
+ n_obs_steps: 1
118
+ horizon: 36
119
+ n_action_steps: ${agent.config.policy_cfg.horizon}
120
+ input_shapes:
121
+ observation.image: ${agent.config.cam_resize_shape}
122
+ context_observation.image: ${agent.config.cam_resize_shape}
123
+ observation.state:
124
+ - 8
125
+ observation.action_history:
126
+ - 7
127
+ output_shapes:
128
+ action:
129
+ - 7
130
+ input_normalization_modes:
131
+ observation.image: mean_std
132
+ observation.state: min_max
133
+ observation.action_history: min_max
134
+ output_normalization_modes:
135
+ action: min_max
136
+ vision_backbone: resnet18
137
+ crop_distractors_tlhw: null
138
+ pretrained_backbone_weights: null
139
+ transforms:
140
+ - _target_: torchaug.transforms.RandomAffine
141
+ degrees:
142
+ - -5
143
+ - 5
144
+ translate:
145
+ - 0.05
146
+ - 0.05
147
+ batch_transform: true
148
+ num_chunks: -1
149
+ batch_inplace: true
150
+ - _target_: torchaug.transforms.RandomColorJitter
151
+ brightness: 0.3
152
+ contrast: 0.4
153
+ saturation: 0.5
154
+ hue: 0.08
155
+ batch_transform: true
156
+ num_chunks: -1
157
+ batch_inplace: true
158
+ use_group_norm: true
159
+ spatial_softmax_num_keypoints: 32
160
+ action_history_encoder_config:
161
+ _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
162
+ in_channels: 7
163
+ out_channels: 32
164
+ history_length: ${agent.config.policy_cfg.n_action_steps}
165
+ kernel_size: ${agent.config.policy_cfg.kernel_size}
166
+ downsample_kernel_size: 3
167
+ downsample_stride: 2
168
+ downsample_padding: 1
169
+ down_dims:
170
+ - 256
171
+ - 512
172
+ - 1024
173
+ kernel_size: 5
174
+ n_groups: 8
175
+ diffusion_step_embed_dim: 128
176
+ use_film_scale_modulation: true
177
+ noise_scheduler_type: DDIM
178
+ beta_schedule: squaredcos_cap_v2
179
+ beta_start: 0.0001
180
+ beta_end: 0.02
181
+ prediction_type: epsilon
182
+ clip_sample: true
183
+ clip_sample_range: 1.0
184
+ num_train_timesteps: 50
185
+ num_inference_steps: 10
186
+ do_mask_loss_for_padding: false
187
+ train_cfg:
188
+ _target_: utils.TrainConfig
189
+ lr: 0.0001
190
+ lr_scheduler: cosine
191
+ lr_warmup_steps: 500
192
+ adam_betas:
193
+ - 0.95
194
+ - 0.999
195
+ adam_eps: 1.0e-08
196
+ adam_weight_decay: 1.0e-06
197
+ grad_clip_norm: 10
198
+ offline_steps: ${num_train_frames_diffusion}
199
+ use_amp: true
200
+ observation_cfg:
201
+ _target_: agent.encoder.VisualFeatureSet
202
+ use_depth: ${use_depth}
203
+ use_color: ${use_color}
204
+ mask_input_dict:
205
+ _target_: agent.encoder.MaskInputDict
206
+ enable: ${use_masks}
207
+ representation: ${mask_representation}
208
+ mask_list: ${mask_list}
209
+ crop_input_config:
210
+ _target_: agent.encoder.CropInputConfig
211
+ color_crop_type: ${color_crop_type}
212
+ depth_crop_type: ${depth_crop_type}
213
+ segmask_crop_type: ${segmask_crop_type}
214
+ crop_hw: ${crop_hw}
215
+ crop_down_offset: ${crop_down_offset}
216
+ add_crop_binary_mask: ${add_crop_binary_mask}
217
+ add_coord_conv_map: ${add_coord_conv_map}
218
+ context_input_config:
219
+ _target_: agent.encoder.ContextInputConfig
220
+ use_color: ${use_context_color}
221
+ use_depth: ${use_context_depth}
222
+ mask_input_dict:
223
+ _target_: agent.encoder.MaskInputDict
224
+ enable: ${use_context_segmask}
225
+ representation: ${mask_representation}
226
+ mask_list: ${mask_list}
227
+ crop_input_config:
228
+ _target_: agent.encoder.CropInputConfig
229
+ color_crop_type: ${context_color_crop_type}
230
+ depth_crop_type: ${context_depth_crop_type}
231
+ segmask_crop_type: ${context_segmask_crop_type}
232
+ crop_hw: ${crop_hw}
233
+ crop_down_offset: ${crop_down_offset}
234
+ add_crop_binary_mask: ${context_add_crop_binary_mask}
235
+ add_coord_conv_map: ${context_add_coord_conv_map}
236
+ mask_soft_approx_scheduler_config:
237
+ _target_: agent.encoder.MaskSoftApproxSchedulerConfig
238
+ num_steps: 40000
239
+ initial_value: 10.0
240
+ final_value: 1000.0
241
+ interpolation_scheme: constant
242
+ use_contact_map: ${use_contact_map}
243
+ use_sdf_maps: ${use_sdf_maps}
244
+ use_normals_maps: ${use_normals_maps}
245
+ which_objects: ${which_objects}
246
+ grasped_dtc_max_value: ${grasped_dtc_max_value}
247
+ env_dtc_max_value: ${env_dtc_max_value}
248
+ grasped_normals_mask_max_dtc_value: ${grasped_normals_mask_max_dtc_value}
249
+ env_normals_mask_max_dtc_value: ${env_normals_mask_max_dtc_value}
250
+ clamp_dtc: ${clamp_dtc}
251
+ max_contact_prob: ${max_contact_prob}
252
+ mask_normals_within_sdf: ${mask_normals_within_sdf}
253
+ dtc_adaptive_normalization: ${dtc_adaptive_normalization}
254
+ adaptive_normals_mask: ${adaptive_normals_mask}
255
+ max_depth: ${max_depth}
256
+ image_shape: ${agent.desired_image_shape}
257
+ learnable_contact_preprocess_params: ${learnable_contact_preprocess_params}
258
+ learning_rate: ${agent.config.train_cfg.lr}
259
+ weight_decay: 0.0
260
+ contact_model_name: ${contact_model_name}
261
+ zero_centered: false
262
+ crop_distractors_tlhw: ${agent.config.policy_cfg.crop_distractors_tlhw}
263
+ suite:
264
+ suite: frankagym
265
+ name: frankagym
266
+ frame_stack: ${agent.n_obs_steps}
267
+ action_repeat: 1
268
+ discount: 0.99
269
+ hidden_dim: 1024
270
+ num_train_frames: 2010
271
+ num_seed_frames: 260
272
+ num_train_epochs: 5000
273
+ validate_every_epochs: 100
274
+ validate_diffusion_on_action_loss_every_epochs: 500
275
+ train_eval_diffusion_on_action_loss_every_epochs: 500
276
+ check_topk_every_epochs: 10
277
+ save_snapshot_every_epochs: 5000
278
+ eval_every_frames: 2000
279
+ num_eval_episodes: 5
280
+ save_snapshot: true
281
+ wait_for_user_to_start_episode: true
282
+ task_make_fn:
283
+ _target_: suite.frankagym.make
284
+ name: ${task_name}
285
+ height: 240
286
+ width: 320
287
+ frame_stack: ${suite.frame_stack}
288
+ action_repeat: ${suite.action_repeat}
289
+ seed: ${seed}
290
+ enable_arm: ${agent.enable_arm}
291
+ enable_gripper: ${enable_gripper}
292
+ start_with_gripper_open: ${start_with_gripper_open}
293
+ enable_camera: ${agent.enable_camera}
294
+ path_to_depth_extrinsics: ${path_to_depth_extrinsics}
295
+ contact_estimation_model_ckpt_path: ${contact_estimation_model_ckpt_path}
296
+ x_limit: ${x_limit}
297
+ y_limit: ${y_limit}
298
+ z_limit: ${z_limit}
299
+ device: ${device}
300
+ interpolation_frequency: ${interpolation_frequency}
301
+ policy_frequency: ${policy_frequency}
302
+ debug_timestamps: ${debug_timestamps}
303
+ stop_after_action: ${stop_after_action}
304
+ open_loop: ${open_loop}
305
+ wait_for_new_camera_frames: ${wait_for_new_camera_frames}
306
+ action_key: ${action_key}
307
+ action_trajectory_horizon: ${agent.config.policy_cfg.horizon}
308
+ action_trajectories: ${action_trajectories}
309
+ path_to_zarr_dataset: ${expert_dataset}
310
+ agent_policy_cfg: ???
311
+ true_action_history: ${true_action_history}
312
+ num_train_frames_bc: 50000
313
+ num_train_frames_drq: 1100000
314
+ stddev_schedule_drq: linear(1.0,0.1,100000)
315
+ task_name: FrankaInsertion-v1
316
+ num_train_frames_vinn: 25000
317
+ num_train_frames_diffusion: 1000000
318
+ num_train_epochs_bc: 5000
319
+ num_train_epochs_diffusion: 5000
320
+ validate_every_epochs_bc: 5
321
+ validate_every_epochs_diffusion: 25
322
+ validate_diffusion_on_action_loss_every_epochs: 50
323
+ train_eval_diffusion_on_action_loss_every_epochs: 500
324
+ check_topk_every_epochs: 5
325
+ check_topk_every_epochs_diffusion: ${validate_diffusion_on_action_loss_every_epochs}
326
+ save_snapshot_every_epochs_diffusion: 5000
327
+ x_limit:
328
+ - 0.2
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+ - 0.7
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+ y_limit:
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+ - -0.4
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+ - 0.4
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+ z_limit:
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+ - -0.05
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+ - 0.55
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+ home_displacement:
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+ - 0.55
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+ - 0.0
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+ - 0.55
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+ - 180.0
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+ - 0.0
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+ - 0.0
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+ enable_gripper: true
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+ start_with_gripper_open: true
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+ offset_mask:
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+ - 1
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+ - 1
348
+ - 1
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+ - 1
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+ - 1
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+ - 1
352
+ path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy
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+ hydra:
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+ run:
3
+ dir: ${final_experiment_dir}
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+ sweep:
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+ dir: ${final_experiment_dir}
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+ subdir: ${hydra.job.num}
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+ launcher:
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+ submitit_folder: ${final_experiment_dir}/.slurm
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+ timeout_min: 60
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+ cpus_per_task: null
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+ gpus_per_node: null
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+ tasks_per_node: 1
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+ mem_gb: null
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+ nodes: 1
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+ name: ${hydra.job.name}
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+ stderr_to_stdout: false
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+ _target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
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+ sweeper:
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+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
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+ max_batch_size: null
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+ params: null
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+ help:
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+ app_name: ${hydra.job.name}
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+ header: '${hydra.help.app_name} is powered by Hydra.
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+
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+ '
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+ footer: 'Powered by Hydra (https://hydra.cc)
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+
29
+ Use --hydra-help to view Hydra specific help
30
+
31
+ '
32
+ template: '${hydra.help.header}
33
+
34
+ == Configuration groups ==
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+
36
+ Compose your configuration from those groups (group=option)
37
+
38
+
39
+ $APP_CONFIG_GROUPS
40
+
41
+
42
+ == Config ==
43
+
44
+ Override anything in the config (foo.bar=value)
45
+
46
+
47
+ $CONFIG
48
+
49
+
50
+ ${hydra.help.footer}
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+
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+ '
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+ hydra_help:
54
+ template: 'Hydra (${hydra.runtime.version})
55
+
56
+ See https://hydra.cc for more info.
57
+
58
+
59
+ == Flags ==
60
+
61
+ $FLAGS_HELP
62
+
63
+
64
+ == Configuration groups ==
65
+
66
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
67
+ to command line)
68
+
69
+
70
+ $HYDRA_CONFIG_GROUPS
71
+
72
+
73
+ Use ''--cfg hydra'' to Show the Hydra config.
74
+
75
+ '
76
+ hydra_help: ???
77
+ hydra_logging:
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+ version: 1
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+ formatters:
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+ simple:
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+ format: '[%(asctime)s][HYDRA] %(message)s'
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+ handlers:
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+ class: logging.StreamHandler
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+ formatter: simple
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+ formatter: simple
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+ stream: ext://sys.stdout
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+ file:
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+ class: logging.FileHandler
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+ formatter: simple
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+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
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+ root:
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+ level: INFO
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+ handlers:
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+ - console
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+ - file
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+ disable_existing_loggers: false
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+ env: {}
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+ mode: RUN
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+ searchpath: []
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+ callbacks: {}
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+ output_subdir: .hydra
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+ overrides:
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+ hydra:
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+ task:
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+ name: eval_robot
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+ chdir: true
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+ override_dirname: agent=diffusion,suite/frankagym_task@_global_=insertion,suite=frankagym
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+ provider: hydra
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+ - path: /home/leonmkim/fish_leon/FISH/cfgs
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+ schema: file
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+ provider: main
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+ - path: ''
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+ schema: structured
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+ choices:
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+ suite: frankagym
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+ suite/frankagym_task@_global_: insertion
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+ agent: diffusion
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+ hydra/env: default
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+ hydra/callbacks: null
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+ hydra/job_logging: default
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+ hydra/hydra_logging: default
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+ hydra/hydra_help: default
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+ hydra/help: default
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+ hydra/sweeper: basic
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+ hydra/launcher: submitit_local
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+ hydra/output: default
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+ verbose: false
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+ 2025-01-21 21:56:27,639 INFO MainThread:2658535 [wandb_setup.py:_flush():76] Loading settings from /home/leonmkim/.config/wandb/settings
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+ 2025-01-21 21:56:27,639 INFO MainThread:2658535 [wandb_setup.py:_flush():76] Loading settings from /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/wandb/settings
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'crop_distractors_tlhw': [32, 68, 174, 174], 'pretrained_backbone_weights': None, 'transforms': [{'_target_': 'torchaug.transforms.RandomAffine', 'degrees': [-5, 5], 'translate': [0.05, 0.05], 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}, {'_target_': 'torchaug.transforms.RandomColorJitter', 'brightness': 0.3, 'contrast': 0.4, 'saturation': 0.5, 'hue': 0.08, 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}], 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'action_history_encoder_config': {'_target_': 'lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig', 'in_channels': 7, 'out_channels': 32, 'history_length': 6, 'kernel_size': 5, 'downsample_kernel_size': 3, 'downsample_stride': 2, 'downsample_padding': 1}, 'down_dims': [256, 512, 1024], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDIM', 'beta_schedule': 'squaredcos_cap_v2', 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aq8qih16/wandb/run-20250121_215627-aq8qih16/files/code/FISH/eval_robot.py ADDED
@@ -0,0 +1,606 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #%%
2
+ import warnings
3
+ import os
4
+
5
+ os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'
6
+ os.environ['MUJOCO_GL'] = 'egl'
7
+ from pathlib import Path
8
+ #%%
9
+ import hydra
10
+ import numpy as np
11
+ import torch
12
+
13
+ import utils
14
+ from utils import get_feature_dirname_from_configs
15
+
16
+ from video import VideoRecorder
17
+ import pickle
18
+ import time
19
+ import threading
20
+ import shutil
21
+ from logger import Logger
22
+
23
+ import wandb
24
+ from omegaconf import OmegaConf, open_dict
25
+
26
+ from replay_buffer_robot import RosbagEvalReplayBufferStorage
27
+ from lerobot.common.utils.utils import _relative_path_between
28
+
29
+ torch.backends.cudnn.benchmark = True
30
+ warnings.filterwarnings('ignore', category=DeprecationWarning)
31
+
32
+ # import specs for replay buffer
33
+ from dm_env import specs
34
+
35
+ import sys, signal
36
+ import yaml
37
+
38
+ import binomial_cis as bc
39
+
40
+ # get path of current file
41
+ current_path = os.path.dirname(os.path.realpath(__file__))
42
+ sys.path.append(os.path.join(current_path, os.pardir))
43
+ # from contact_estimation.src.utils.viz_utils import normalized_surface_normal_to_rgb, depth_map_to_im, grasped_env_dtc_map_to_im, contact_prob_map_to_im, desaturate_color_image, masked_overlay_im_list
44
+
45
+ def make_agent(obs_spec, action_spec, cfg):
46
+ cfg.obs_shape = obs_spec['pixels'].shape
47
+ dataset_statistics = None # this will be loaded from the checkpoint
48
+ try:
49
+ cfg.action_shape = action_spec.shape
50
+ except:
51
+ pass
52
+ return hydra.utils.instantiate(cfg, dataset_statistics)
53
+
54
+ class Workspace:
55
+ def __init__(self, cfg):
56
+ self.work_dir = Path.cwd()
57
+ print(f'workspace: {self.work_dir}')
58
+
59
+ signal.signal(signal.SIGINT, self.signal_handler)
60
+
61
+ self.cfg = cfg
62
+ self.loading_uncompiled_checkpoint_with_compile = False
63
+ self.loading_compiled_checkpoint_with_no_compile = False
64
+
65
+ snapshot_path = Path(self.cfg.checkpoint_weight_dir) / f'snapshot_{self.cfg.checkpoint_epoch}.pt'
66
+ self.load_checkpoint_conf(snapshot_path=snapshot_path)
67
+
68
+ # load config for action trajectories
69
+ utils.set_seed_everywhere(self.cfg.seed)
70
+ self.device = torch.device(self.cfg.device)
71
+ self.setup()
72
+
73
+ # self.agent = make_agent(self.eval_env.observation_spec(),
74
+ # self.eval_env.action_spec(), self.cfg.agent)
75
+ self.timer = utils.Timer()
76
+ # self._global_step = 0
77
+ self._global_episode = 0
78
+ self._global_epoch = 0
79
+ self.num_episode_successes = 0
80
+
81
+ self.alpha_range = [.01, .025, .05, .1]
82
+
83
+ # Need to convert hydra config to primitive container for wandb https://docs.wandb.ai/guides/integrations/hydra
84
+ with open_dict(self.cfg):
85
+ self.cfg.feature_type = get_feature_dirname_from_configs(
86
+ hydra.utils.instantiate(self.cfg.agent.config),
87
+ # hydra.utils.instantiate(self.cfg.agent.config.observation_cfg),
88
+ # self.cfg.agent.config.policy_cfg.input_shapes,
89
+ # hydra.utils.instantiate(self.cfg.agent.config.policy_cfg.action_history_encoder_config) if 'observation.action_history' in self.cfg.agent.config.policy_cfg.input_shapes else None,
90
+ )
91
+
92
+ wandb_config = OmegaConf.to_container(
93
+ self.cfg, resolve=True, throw_on_missing=True
94
+ )
95
+ # must be called before any tf summary writer is created
96
+ if self.cfg.use_wandb:
97
+ # get the run id from the final_experiment_dir directory
98
+ run_id = os.path.basename(os.path.normpath(self.cfg.final_experiment_dir))
99
+ wandb.init(project='extrinsic_contact_downstream', entity='serialexperimentsleon', job_type='eval', sync_tensorboard=self.cfg.use_tb, config=wandb_config, id=run_id)
100
+
101
+ self.logger = Logger(self.work_dir, use_tb=self.cfg.use_tb, use_wandb=self.cfg.use_wandb)
102
+
103
+ # if not self.loading_uncompiled_checkpoint_with_compile and self.cfg.agent.config.compile:
104
+ # self.agent.compile_modules()
105
+
106
+ # self.load_checkpoint(snapshot_path=snapshot_path)
107
+
108
+ # if self.loading_uncompiled_checkpoint_with_compile: # need to call compile after loading the checkpoint
109
+ # self.agent.compile_modules()
110
+
111
+ print(f"loaded agent with feature_type: {self.cfg.feature_type}")
112
+
113
+ def check_for_key_press(self):
114
+ while self.continue_keypress_thread:
115
+ inp = input("Press 'r' to restart current episode, 'n' to stop current episode and skip to next, 'q' to break entire eval\n")
116
+ if inp == 'n':
117
+ self.preempt_episode = True
118
+ print("preempting episode")
119
+ elif inp in ['', '0', '1']: # enter key
120
+ if inp in ['0', '1']:
121
+ self.num_episode_successes += int(inp)
122
+ self.proceed_after_env_reset_event.set()
123
+ print("proceeding to start episode!")
124
+ elif inp == 'q':
125
+ self.proceed_after_env_reset_event.set()
126
+ self.preempt_episode = True
127
+ self.exit_eval = True
128
+ self.continue_keypress_thread = False # will stop the keypress thread
129
+ print("quitting eval")
130
+ break
131
+ elif inp == 'r':
132
+ print('restarting episode')
133
+ self.preempt_episode = True
134
+ self.restart_episode = True
135
+ else:
136
+ print("Invalid key press, try again")
137
+
138
+ # self.keypress_input_thread.join() # wait for the keypress thread to finish
139
+
140
+ def signal_handler(self, signal, frame):
141
+ print("\nprogram exiting gracefully")
142
+ self.proceed_after_env_reset_event.set()
143
+ self.preempt_episode = True
144
+ self.exit_eval = True
145
+ self.continue_keypress_thread = False # will stop the keypress thread
146
+ self.keypress_input_thread.join() # wait for the keypress thread to finish
147
+ video_filepath = self.video_recorder.save()
148
+ # get the video file and convert to video tensor to log
149
+ self.logger.log_video('eval/video', video_filepath, self.global_step)
150
+ wandb.finish()
151
+ sys.exit(0)
152
+
153
+ def setup(self):
154
+ # create envs
155
+ self.eval_env = hydra.utils.call(self.cfg.suite.task_make_fn)
156
+ # expert_demo_config_path = os.path.join(os.path.dirname(self.cfg.expert_dataset), 'demo_config.yaml')
157
+ # self.expert_demo_config = yaml.load(open(expert_demo_config_path, 'r'), Loader=yaml.FullLoader)
158
+ # self.eval_env._env.action_trans_norm = expert_demo_config['max_translation_action_norm']
159
+ # self.eval_env._env.action_rot_norm = expert_demo_config['max_rotation_action_norm']
160
+ # self.eval_env._env.action_period = expert_demo_config['sample_period']
161
+ # print(f"setting max_translation_action_norm to {expert_demo_config['max_translation_action_norm']} and sample_period to {expert_demo_config['sample_period']}")
162
+ # print(f"setting max_rotation_action_norm to {expert_demo_config['max_rotation_action_norm']}")
163
+
164
+ # self.eval_env.set_demo_params(self.cfg.expert_dataset)
165
+
166
+ # Turn off random start
167
+ self.eval_env.random_start = False
168
+
169
+ # create replay buffer
170
+ # data_specs = [
171
+ # {
172
+ # 'observation': self.eval_env.observation_spec(),
173
+ # },
174
+ # # self.eval_env.observation_spec()['features'],
175
+ # self.eval_env.action_spec(),
176
+ # specs.Array(self.eval_env.action_spec().shape, self.eval_env.action_spec().dtype, 'vinn_action'),
177
+ # specs.Array((1, ), np.float32, 'reward'),
178
+ # specs.Array((1, ), np.float32, 'discount'),
179
+ # ]
180
+
181
+ # self.eval_replay_storage = ZarrEvalReplayBufferStorage(data_specs, self.work_dir / 'eval_buffer', debug_timestamps=self.cfg.debug_timestamps, save_buffer=self.cfg.save_buffer, debug_info_data_specs=self.eval_env.debug_info_data_specs, camera_info_dict=self.eval_env.get_camera_info_dict())
182
+ self.eval_replay_storage = RosbagEvalReplayBufferStorage(self.work_dir)
183
+
184
+ self.video_recorder = VideoRecorder(
185
+ self.work_dir if self.cfg.save_video else None,
186
+ ros_enabled=True,
187
+ fps=self.cfg.agent.config.policy_frequency,
188
+ )
189
+
190
+ print('workspace setup complete')
191
+
192
+ @property
193
+ def global_step(self):
194
+ # return self._global_step
195
+ return self.eval_env.get_global_step()
196
+
197
+ @property
198
+ def global_episode(self):
199
+ return self._global_episode
200
+
201
+ @property
202
+ def global_frame(self):
203
+ return self.global_step * self.cfg.action_repeat
204
+
205
+ @property
206
+ def global_epoch(self):
207
+ return self._global_epoch
208
+
209
+ def reset(self, eval_idx):
210
+ if not self.eval_env.enable_arm:
211
+ return np.array([0,0,0], dtype=np.float32)
212
+ self.eval_env.arm_refresh(reset=False)
213
+ # Set start position
214
+ try:
215
+ self.eval_env.set_position(self.start_pos[eval_idx])
216
+ except:
217
+ self.eval_env.arm.set_position(self.start_pos[eval_idx])
218
+ if self.eval_env.arm.keep_gripper_closed:
219
+ self.eval_env.arm.close_gripper_fully()
220
+ else:
221
+ self.eval_env.arm.open_gripper_fully()
222
+ time.sleep(0.1)
223
+ time_step = self.eval_env.step(np.zeros(self.eval_env.action_spec().shape[0], dtype=np.float32),
224
+ np.zeros(self.eval_env.action_spec().shape[0], dtype=np.float32))
225
+ return time_step
226
+
227
+ def eval(self):
228
+ # before evals start, prompt user for name of grasped object and the left book of the slot location
229
+ grasped_obj_name = input("Enter the name of the grasped object: ")
230
+ left_book_slot = input("Enter the left book slot location: ")
231
+ # update wandb config
232
+ if self.cfg.use_wandb:
233
+ wandb.config.update({'grasped_obj_name': grasped_obj_name, 'left_book_slot': left_book_slot})
234
+
235
+ self.preempt_episode = False
236
+ self.exit_eval = False
237
+ self.restart_episode = False
238
+
239
+ self.continue_keypress_thread = True
240
+ self.proceed_after_env_reset_event = threading.Event()
241
+ self.keypress_input_thread = threading.Thread(target=self.check_for_key_press)
242
+ self.keypress_input_thread.start()
243
+
244
+ # # Set model to eval mode
245
+ # self.agent.train(False)
246
+
247
+ eval_until_episode = utils.Until(self.cfg.num_eval)
248
+
249
+ self.use_action_history = False
250
+ # if "dp" in repr(self.agent) and "observation.action_history" in self.cfg.agent.config.policy_cfg.input_shapes:
251
+ if "observation.action_history" in self.cfg.agent.config.policy_cfg.input_shapes:
252
+ self.use_action_history = True
253
+
254
+ # self.eval_replay_storage._new_eval_step(0)
255
+
256
+ # if 'vinn' in repr(self.agent) or 'openloop' in repr(self.agent):
257
+ # with open(self.cfg.expert_dataset, 'rb') as f:
258
+ # if self.cfg.obs_type == 'pixels':
259
+ # self.expert_demo, _, self.expert_action, self.expert_reward = pickle.load(f)
260
+ # elif self.cfg.obs_type == 'features':
261
+ # _, self.expert_demo, self.expert_action, self.expert_reward = pickle.load(f)
262
+
263
+ # if self.cfg.action_trajectories:
264
+ # with open(self.cfg.expert_action_trajectories, 'rb') as f:
265
+ # self.expert_action = pickle.load(f)
266
+
267
+ # if isinstance(self.cfg.train_demo_idxs_list_or_num, int):
268
+ # if self.cfg.train_demo_idxs_list_or_num == -1:
269
+ # self.cfg.train_demo_idxs_list_or_num = len(self.expert_demo)
270
+ # train_demo_idxs_list_or_num = list(range(self.cfg.train_demo_idxs_list_or_num))
271
+
272
+ # self.expert_demo = self.expert_demo[train_demo_idxs_list_or_num]
273
+ # self.expert_action = self.expert_action[train_demo_idxs_list_or_num]
274
+ # self.expert_reward = self.expert_reward[train_demo_idxs_list_or_num]
275
+ # # if self.cfg.action_plans:
276
+ # # self.expert_action_plans = self.expert_action_plans[self.cfg.train_demo_idxs_list_or_num]
277
+ # # self.expert_demo = self.expert_demo[:self.cfg.num_demos]
278
+ # # self.expert_action = self.expert_action[:self.cfg.num_demos]
279
+ # # self.expert_reward = self.expert_reward[:self.cfg.num_demos]
280
+
281
+ # self.expert_demo = np.concatenate(self.expert_demo, axis=0)
282
+ # self.expert_rgb_obs = np.ascontiguousarray(np.transpose(self.expert_demo, (0,2,3,1))[:, :,:,:3].astype(np.uint8))
283
+ # self.expert_action = np.concatenate(self.expert_action, axis=0)
284
+
285
+ # self.agent.save_representations(self.expert_demo, self.expert_action, 128, config=self.expert_demo_config)
286
+
287
+ # Get start points
288
+ if self.cfg.random_start:
289
+ eval_starts = Path(self.cfg.eval_starts) / 'starts.pkl'
290
+ if eval_starts.exists():
291
+ with eval_starts.open('rb') as f:
292
+ self.start_pos = pickle.load(f)
293
+ else:
294
+ eval_starts = Path(self.cfg.eval_starts)
295
+ eval_starts.mkdir(parents=True, exist_ok=True)
296
+
297
+ # Generate start points
298
+ self.start_pos = []
299
+ try:
300
+ for _ in range(self.cfg.num_eval):
301
+ self.start_pos.append(self.eval_env.get_random_pos())
302
+ except:
303
+ for _ in range(self.cfg.num_eval):
304
+ self.start_pos.append(self.eval_env.arm.get_random_pos())
305
+
306
+ # Save start points for the task
307
+ eval_starts = eval_starts / 'starts.pkl'
308
+ with eval_starts.open('wb') as f:
309
+ pickle.dump(self.start_pos, f)
310
+
311
+ time_step = self.eval_env.reset()
312
+ # replay_thread = None
313
+ while eval_until_episode(self.global_episode) and not self.exit_eval:
314
+ # self.video_recorder.init(self.eval_env, video_filename=f'{self.global_episode}_eval.mp4')
315
+ print(f"Starting episode {self.global_episode}")
316
+ time_step = self.eval_env.reset() #Leon: need to call reset twice in case objects are trapped
317
+ self.video_recorder.init(self.eval_env, video_filename=f'{self.global_episode}_eval.mp4')
318
+ # x = input("Press Enter to continue... after reseting env")
319
+ print("Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success")
320
+ self.proceed_after_env_reset_event.clear() # clear the event flag
321
+ self.proceed_after_env_reset_event.wait() # blocking wait for the event flag to be set
322
+ if self.global_episode > 0:
323
+ self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
324
+ self.logger.log_metrics({'success_rate': self.num_episode_successes/self.global_episode}, self.global_step, 'eval', episode=self.global_episode)
325
+
326
+ # log confidence intervals for success rate
327
+ k = self.num_episode_successes # number of successes
328
+ n = self.global_episode # number of trials
329
+
330
+ table_columns = []
331
+ table_data = []
332
+ for alpha in self.alpha_range:
333
+ lb = bc.binom_ci(k, n, alpha, 'lb')
334
+ ub = bc.binom_ci(k, n, alpha, 'ub')
335
+
336
+ self.logger.log_metrics({f'success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=self.global_episode)
337
+ self.logger.log_metrics({f'success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=self.global_episode)
338
+
339
+ time_step = self.eval_env.reset()
340
+ # debug_info_dict = self.eval_env.debug_info_dict
341
+ # if replay_thread is not None:
342
+ # # wait for the last replay thread to finish
343
+ # replay_thread.join()
344
+
345
+ # self.eval_replay_storage.add(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict)
346
+ # replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict))
347
+ # replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step, debug_info_dict))
348
+
349
+ # replay_thread.start()
350
+ if self.cfg.random_start:
351
+ time_step = self.reset(self.global_episode)
352
+ time.sleep(2) #5)
353
+ # if 'vinn' in repr(self.agent):
354
+ # self.agent.reset()
355
+ # # self.agent.buffer.reset()
356
+ # # if self.cfg.open_loop:
357
+ # # self.agent.current_step = 0
358
+ # if 'openloop' in repr(self.agent):
359
+ # self.agent.curr_step = 0
360
+ # at start of each episode, provide zero action for policies that use action history
361
+ # shape should be (T_o, T_a, action_dim)
362
+
363
+ # while not time_step.last() and not self.preempt_episode:
364
+ self.video_recorder.ros_start_recording()
365
+ self.eval_replay_storage.start_episode()
366
+ self.eval_env.start_policy_timer()
367
+ while not self.eval_env.episode_done() and not self.preempt_episode:
368
+ # with torch.no_grad(), utils.eval_mode(self.agent):
369
+ # # if self.cfg.agent.provide_topk:
370
+ # # action, vinn_action, topk = self.agent.act(
371
+ # # time_step.observation['pixels'],
372
+ # # self.global_step,
373
+ # # eval_mode=True)
374
+ # # elif self.cfg.agent.provide_obs:
375
+ # # action, vinn_action, obs = self.agent.act(
376
+ # # time_step.observation['pixels'],
377
+ # # self.global_step,
378
+ # # eval_mode=True)
379
+ # # else:
380
+ # action, vinn_action = self.agent.act(
381
+ # time_step.observation,
382
+ # self.global_step,
383
+ # eval_mode=True,
384
+ # obs_timestamp=time_step.observation['timestamp'],
385
+ # obs_seq=time_step.observation['seq'],
386
+ # action_history=action_history,
387
+ # action_history_start_timestamp=action_history_start_timestamp,
388
+ # )
389
+ # DONT WAIT FOR POLICY TO GET AN ACTION
390
+ # we dont want to slow down grabbing obs and passing to sam/contact features
391
+
392
+ self.eval_env.run_policy_threads() # this just does a rospy sleep
393
+
394
+ # if self.use_action_history:
395
+ # action_history_start_timestamp = time_step.observation['timestamp']
396
+ # # action_history = action[:self.cfg.agent.config.policy_cfg.action_history_encoder_config.history_length, ...]
397
+ # # add n_obs_steps dimension to action_history, for now we assume n_obs_steps = 1
398
+ # # TODO: handle n_obs_steps > 1
399
+ # action_history = action[np.newaxis, ...]
400
+
401
+ # time_step = self.eval_env.step(action, vinn_action) # obs, reward after action has been taken
402
+ # debug_info_dict = self.eval_env.debug_info_dict
403
+
404
+ # time_step = self.eval_env.ros_step()
405
+
406
+ # replay_thread.join()
407
+
408
+ # time how long it takes to execute the step
409
+ # time_before_add = time.perf_counter()
410
+ # self.eval_replay_storage.add(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict)
411
+ # use thread to call the add function in a separate thread
412
+ # replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict))
413
+
414
+ # replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step, debug_info_dict))
415
+ # replay_thread.start()
416
+
417
+ # print(f"Time to add to replay buffer: {time.perf_counter() - time_before_add}")
418
+
419
+ # self.video_recorder.record(self.eval_env)
420
+ # self._global_step += 1
421
+
422
+ self.eval_env.stop_policy_timer()
423
+
424
+ if self.restart_episode:
425
+ # means we should delete the current episode and start again
426
+ self.restart_episode = False
427
+ self.eval_replay_storage.reset_current_episode()
428
+ self.video_recorder.reset_current_episode()
429
+
430
+ else:
431
+ self.eval_replay_storage.store_current_episode()
432
+ video_filepath = self.video_recorder.save()
433
+ self.logger.log_video(f"eval/{video_filepath.name.rstrip('.mp4')}", video_filepath, self.global_step)
434
+ self._global_episode += 1
435
+
436
+ self.preempt_episode = False # reset preempt_episode flag
437
+
438
+ # self.video_recorder.save(f'{episode}_eval.mp4')
439
+ # get the video file and convert to video tensor to log
440
+
441
+ self.eval_env.reset()
442
+
443
+ print("Evaluation finished. To wrap up, rate prev episode, press 0 for failure and 1 for success")
444
+ self.proceed_after_env_reset_event.clear() # clear the event flag
445
+ self.proceed_after_env_reset_event.wait() # blocking wait for the event flag to be set
446
+ if self.global_episode > 0:
447
+ # self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
448
+ self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
449
+ self.logger.log_metrics({'success_rate': self.num_episode_successes/self.global_episode}, self.global_step, 'eval', episode=self.global_episode)
450
+
451
+ # log confidence intervals for success rate
452
+ k = self.num_episode_successes # number of successes
453
+ n = self.global_episode # number of trials
454
+
455
+ table_columns = ['success_rate']
456
+ table_data = [self.num_episode_successes/self.global_episode]
457
+ for alpha in self.alpha_range:
458
+ lb = bc.binom_ci(k, n, alpha, 'lb')
459
+ ub = bc.binom_ci(k, n, alpha, 'ub')
460
+
461
+ self.logger.log_metrics({f'success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=self.global_episode)
462
+ self.logger.log_metrics({f'success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=self.global_episode)
463
+
464
+ table_columns.extend([f'success_rate_lb_{alpha}', f'success_rate_ub_{alpha}'])
465
+ table_data.extend([lb, ub])
466
+
467
+ table_data = [table_data]
468
+
469
+ # seperately log as a table
470
+ wandb.log({
471
+ "eval/success_rate_ci": wandb.Table(data=table_data, columns=table_columns)
472
+ })
473
+
474
+ # also accumulate eval metrics across previous eval runs
475
+ # TODO: change wandb init to resume from an existing run!!!
476
+ run_filter={
477
+ "jobType": "eval",
478
+ "config.wandb_run_id": self.cfg.wandb_run_id,
479
+ "summary_metrics.episode": {"$gte": 5},
480
+ "config.checkpoint_epoch": self.cfg.checkpoint_epoch,
481
+ "state": "finished",
482
+ # "config.grasped_obj_name": grasped_obj_name,
483
+ # "config.left_book_slot": left_book_slot,
484
+ }
485
+
486
+ api = wandb.Api()
487
+ filtered_runs = api.runs("serialexperimentsleon/extrinsic_contact_downstream", filters=run_filter)
488
+ total_num_successes = self.num_episode_successes
489
+ total_num_episodes = self.global_episode
490
+ list_of_historical_run_ids = []
491
+ if len(filtered_runs) > 0:
492
+ for filtered_run in filtered_runs:
493
+ total_num_successes += filtered_run.summary_metrics['eval/num_success']
494
+ # total_num_episodes += filtered_run.summary_metrics['episode']
495
+ total_num_episodes += filtered_run.config['num_eval']
496
+ list_of_historical_run_ids.append(filtered_run.id)
497
+
498
+ wandb.summary['total_num_successes'] = total_num_successes
499
+ wandb.summary['total_num_episodes'] = total_num_episodes
500
+ wandb.summary['total_success_rate'] = total_num_successes/total_num_episodes
501
+
502
+ # log the accumulated metrics as a table
503
+ total_table_columns = ['total_num_successes', 'total_num_episodes', 'total_success_rate']
504
+ total_table_data = [total_num_successes, total_num_episodes, total_num_successes/total_num_episodes]
505
+ self.logger.log_metrics({'total_success_rate': total_num_successes/total_num_episodes}, self.global_step, 'eval', episode=total_num_episodes)
506
+
507
+ for alpha in self.alpha_range:
508
+ lb = bc.binom_ci(total_num_successes, total_num_episodes, alpha, 'lb')
509
+ ub = bc.binom_ci(total_num_successes, total_num_episodes, alpha, 'ub')
510
+ total_table_columns.extend([f'total_success_rate_lb_{alpha}', f'total_success_rate_ub_{alpha}'])
511
+ total_table_data.extend([lb, ub])
512
+ wandb.summary[f'total_success_rate_lb_{alpha}'] = lb
513
+ wandb.summary[f'total_success_rate_ub_{alpha}'] = ub
514
+
515
+ self.logger.log_metrics({f'total_success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=total_num_episodes)
516
+ self.logger.log_metrics({f'total_success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=total_num_episodes)
517
+
518
+ total_table_data = [total_table_data]
519
+ wandb.log({
520
+ 'eval/total_success_rate_ci': wandb.Table(data=total_table_data, columns=total_table_columns)
521
+ })
522
+
523
+ self.continue_keypress_thread = False # will stop the keypress thread
524
+ self.keypress_input_thread.join() # wait for the keypress thread to finish
525
+
526
+ def load_checkpoint_conf(self, snapshot_path):
527
+ config_path = snapshot_path.parent / 'config.yaml'
528
+ if not config_path.exists():
529
+ raise FileNotFoundError(f'No snapshot conf found at {config_path}')
530
+ else:
531
+ # load the omegaconf config
532
+ hydra.core.global_hydra.GlobalHydra.instance().clear()
533
+ hydra.initialize(
534
+ str(_relative_path_between(Path(config_path).absolute().parent, Path(__file__).absolute().parent)),
535
+ )
536
+ cfg = hydra.compose(Path(config_path).stem)
537
+ from deepdiff import DeepDiff
538
+ from omegaconf import open_dict
539
+ diff = DeepDiff(OmegaConf.to_container(cfg), OmegaConf.to_container(self.cfg)) # old, new
540
+ # import re
541
+ overwriteable_keys = [f"root{overwritable_key}" for overwritable_key in ["['use_wandb']", "['path_to_depth_extrinsics']", "['eval']", "['root_dir']", "['wandb_notes']", "['agent']['config']['train_cfg']['use_amp']", "['agent']['config']['compile']", "['agent']['config']['policy_cfg']['num_inference_steps']"]]
542
+ if "values_changed" in diff:
543
+ # top_k_checkpoints, wandb_notes, agent.config.train_cfg.use_amp, save_snapshot_every_epochs_diffusion, check_topk_every_epochs_diffusion, validate_diffusion_on_action_loss_every_epochs, train_eval_diffusion_on_action_loss_every_epochs, validate_every_epochs_diffusion
544
+ # for keys above, overwrite the old config with the new config
545
+ for k, v in diff['values_changed'].items():
546
+ # replace any keys that are under "root['suite']"
547
+ if k in overwriteable_keys or k.startswith("root['suite']"):
548
+ print(f"Found changed key {k} with value {v}. Overwriting old checkpoint config")
549
+ if k == "root['agent']['config']['compile']":
550
+ if diff['values_changed'][k]['new_value']:
551
+ self.loading_uncompiled_checkpoint_with_compile = True
552
+ elif not diff['values_changed'][k]['new_value']:
553
+ # raise ValueError("Cannot load a compiled checkpoint without compile")
554
+ self.loading_compiled_checkpoint_with_no_compile = True
555
+ exec(f"{k.replace('root[', 'cfg[')} = {k.replace('root[', 'self.cfg[')}")
556
+ # for any new values, update the old checkpoint config
557
+ if "dictionary_item_added" in diff:
558
+ for new_key in diff['dictionary_item_added']: # this is a list
559
+ # if new_key == "root['suite']['task_make_fn']['observation_cfg']":
560
+ if new_key == "root['suite']['task_make_fn']['agent_policy_cfg']":
561
+ # pass the agents observation_cfg to the suite task_make_fn
562
+ with open_dict(cfg): # to allow addition of non-existing keys
563
+ # cfg.suite.task_make_fn.observation_cfg = cfg.agent.config.observation_cfg
564
+ cfg.suite.task_make_fn.agent_policy_cfg = cfg.agent.config
565
+ continue
566
+ elif "['agent']['config']['policy_cfg']['input_shapes']" in new_key:
567
+ # skip adding the new key if it is the input_shapes of the policy_cfg
568
+ continue
569
+ else:
570
+ print(f"Found new key {new_key} with value {eval(new_key.replace('root[', 'self.cfg['))}. Adding to checkpoint config")
571
+ # eval(new_key.replace('root', 'cfg')) = eval(new_key.replace('root', 'self.cfg'))
572
+ if new_key == "root['agent']['config']['compile']":
573
+ if self.cfg.agent.config.compile:
574
+ self.loading_uncompiled_checkpoint_with_compile = True
575
+
576
+ with open_dict(cfg):
577
+ exec(f"{new_key.replace('root[', 'cfg[')}={new_key.replace('root[', 'self.cfg[')}")
578
+ self.cfg = cfg
579
+
580
+ def load_checkpoint(self, snapshot_path, bc=False):
581
+ print(f'resuming {repr(self.agent)}: {snapshot_path}')
582
+ with snapshot_path.open('rb') as f:
583
+ payload = torch.load(f)
584
+ agent_payload = {}
585
+ for k, v in payload.items():
586
+ if k not in self.__dict__:
587
+ agent_payload[k] = v
588
+ elif k == '_global_epoch':
589
+ self._global_epoch = v
590
+ print(f'loaded epoch: {v}')
591
+ if self.cfg.use_wandb:
592
+ # add to config of wandb
593
+ wandb.config.update({'epoch': v})
594
+
595
+ # self.agent.load_snapshot_eval(agent_payload, bc)
596
+
597
+ @hydra.main(config_path='cfgs', config_name='config_eval')
598
+ def main(cfg):
599
+ from eval_robot import Workspace as W
600
+ root_dir = Path.cwd()
601
+ workspace = W(cfg)
602
+
603
+ workspace.eval()
604
+
605
+ if __name__ == '__main__':
606
+ main()
aq8qih16/wandb/run-20250121_215627-aq8qih16/files/config.yaml ADDED
@@ -0,0 +1,936 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wandb_version: 1
2
+
3
+ root_dir:
4
+ desc: null
5
+ value: /home/leonmkim/fish_leon
6
+ replay_buffer_size:
7
+ desc: null
8
+ value: 150000
9
+ replay_buffer_num_workers:
10
+ desc: null
11
+ value: 2
12
+ nstep:
13
+ desc: null
14
+ value: 3
15
+ batch_size:
16
+ desc: null
17
+ value: 128
18
+ seed:
19
+ desc: null
20
+ value: 2
21
+ dataset_shuffle_seed:
22
+ desc: null
23
+ value: 0
24
+ device:
25
+ desc: null
26
+ value: cuda
27
+ save_video:
28
+ desc: null
29
+ value: true
30
+ save_train_video:
31
+ desc: null
32
+ value: true
33
+ use_tb:
34
+ desc: null
35
+ value: true
36
+ use_wandb:
37
+ desc: null
38
+ value: true
39
+ wandb_run_id:
40
+ desc: null
41
+ value: '4295_2'
42
+ wandb_notes:
43
+ desc: null
44
+ value: 4295_2_restarted_1
45
+ eval:
46
+ desc: null
47
+ value: true
48
+ true_action_history:
49
+ desc: null
50
+ value: false
51
+ train_pad_after:
52
+ desc: null
53
+ value: 4
54
+ process_contact_features:
55
+ desc: null
56
+ value: true
57
+ obs_type:
58
+ desc: null
59
+ value: pixels
60
+ use_color:
61
+ desc: null
62
+ value: false
63
+ use_depth:
64
+ desc: null
65
+ value: true
66
+ use_masks:
67
+ desc: null
68
+ value: true
69
+ mask_list:
70
+ desc: null
71
+ value:
72
+ - EE_obj_mask
73
+ mask_representation:
74
+ desc: null
75
+ value: channels
76
+ crop_hw:
77
+ desc: null
78
+ value:
79
+ - 144
80
+ - 144
81
+ crop_down_offset:
82
+ desc: null
83
+ value: 48
84
+ color_crop_type:
85
+ desc: null
86
+ value: null
87
+ depth_crop_type:
88
+ desc: null
89
+ value: null
90
+ segmask_crop_type:
91
+ desc: null
92
+ value: null
93
+ add_crop_binary_mask:
94
+ desc: null
95
+ value: false
96
+ add_coord_conv_map:
97
+ desc: null
98
+ value: false
99
+ use_context_color:
100
+ desc: null
101
+ value: false
102
+ use_context_depth:
103
+ desc: null
104
+ value: false
105
+ use_context_segmask:
106
+ desc: null
107
+ value: false
108
+ context_color_crop_type:
109
+ desc: null
110
+ value: null
111
+ context_depth_crop_type:
112
+ desc: null
113
+ value: null
114
+ context_segmask_crop_type:
115
+ desc: null
116
+ value: null
117
+ context_add_crop_binary_mask:
118
+ desc: null
119
+ value: false
120
+ context_add_coord_conv_map:
121
+ desc: null
122
+ value: false
123
+ use_contact_map:
124
+ desc: null
125
+ value: true
126
+ use_sdf_maps:
127
+ desc: null
128
+ value: true
129
+ use_normals_maps:
130
+ desc: null
131
+ value: true
132
+ which_objects:
133
+ desc: null
134
+ value: both
135
+ max_contact_prob:
136
+ desc: null
137
+ value: 0.1
138
+ max_depth:
139
+ desc: null
140
+ value: 2.0
141
+ grasped_dtc_max_value:
142
+ desc: null
143
+ value: 0.2
144
+ env_dtc_max_value:
145
+ desc: null
146
+ value: 0.4
147
+ grasped_normals_mask_max_dtc_value:
148
+ desc: null
149
+ value: 0.2
150
+ env_normals_mask_max_dtc_value:
151
+ desc: null
152
+ value: 0.4
153
+ clamp_dtc:
154
+ desc: null
155
+ value: true
156
+ dtc_adaptive_normalization:
157
+ desc: null
158
+ value: false
159
+ mask_normals_within_sdf:
160
+ desc: null
161
+ value: true
162
+ adaptive_normals_mask:
163
+ desc: null
164
+ value: true
165
+ learnable_contact_preprocess_params:
166
+ desc: null
167
+ value: true
168
+ contact_model_name:
169
+ desc: null
170
+ value: local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9
171
+ contact_estimation_model_ckpt_path:
172
+ desc: null
173
+ value: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
174
+ encoder_type:
175
+ desc: null
176
+ value: small
177
+ debug_timestamps:
178
+ desc: null
179
+ value: false
180
+ open_loop:
181
+ desc: null
182
+ value: false
183
+ action_trajectories:
184
+ desc: null
185
+ value: true
186
+ stop_after_action:
187
+ desc: null
188
+ value: false
189
+ interpolation_frequency:
190
+ desc: null
191
+ value: 25
192
+ policy_frequency:
193
+ desc: null
194
+ value: 5
195
+ wait_for_new_camera_frames:
196
+ desc: null
197
+ value: true
198
+ baseline:
199
+ desc: null
200
+ value: false
201
+ train_demo_idxs_list_or_num:
202
+ desc: null
203
+ value: -1
204
+ log_train_every_steps:
205
+ desc: null
206
+ value: 25
207
+ name_of_expert_demo:
208
+ desc: null
209
+ value: 120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
210
+ expert_dataset_dirpath:
211
+ desc: null
212
+ value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
213
+ store_dataset_in_memory:
214
+ desc: null
215
+ value: false
216
+ expert_dataset:
217
+ desc: null
218
+ value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
219
+ action_key:
220
+ desc: null
221
+ value: action_trajectory_25hz
222
+ semantic_demo_grouping_name:
223
+ desc: null
224
+ value: semantic_demo_grouping.yaml
225
+ semantic_demo_grouping:
226
+ desc: null
227
+ value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/semantic_demo_grouping.yaml
228
+ include_groups_list:
229
+ desc: null
230
+ value: all
231
+ expert_dataset_config:
232
+ desc: null
233
+ value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demo_config.yaml
234
+ name_of_valid_demo:
235
+ desc: null
236
+ value: 120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
237
+ valid_dataset_dir:
238
+ desc: null
239
+ value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
240
+ valid_demo_idxs_list_or_num:
241
+ desc: null
242
+ value: null
243
+ val_num_groups:
244
+ desc: null
245
+ value: 7
246
+ load_bc:
247
+ desc: null
248
+ value: true
249
+ checkpoint_epoch_list:
250
+ desc: null
251
+ value:
252
+ - 99
253
+ - 199
254
+ - 299
255
+ - 399
256
+ - 499
257
+ - 599
258
+ - 699
259
+ - 799
260
+ - 899
261
+ - 999
262
+ - 1249
263
+ - 1499
264
+ - 1749
265
+ - 1999
266
+ - 2999
267
+ - 3999
268
+ - 4999
269
+ - 5999
270
+ - 6999
271
+ - 7999
272
+ - 8999
273
+ - 9999
274
+ snapshot_root_dir:
275
+ desc: null
276
+ value: /mnt/grasp_high_usage/leonmkim/contact_estimation/FISH
277
+ save_snapshot:
278
+ desc: null
279
+ value: true
280
+ save_last_snapshot:
281
+ desc: null
282
+ value: true
283
+ save_snapshot_when_done:
284
+ desc: null
285
+ value: true
286
+ top_k_checkpoints:
287
+ desc: null
288
+ value: 5
289
+ save_snapshot_link_to_weights_dir:
290
+ desc: null
291
+ value: deprecated
292
+ restore_missing_checkpoint:
293
+ desc: null
294
+ value: null
295
+ bc_regularize:
296
+ desc: null
297
+ value: false
298
+ bc_weight_type:
299
+ desc: null
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aq8qih16/wandb/run-20250121_215627-aq8qih16/files/diff.patch ADDED
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+ diff --git a/FISH/cfgs/config_eval.yaml b/FISH/cfgs/config_eval.yaml
2
+ index bb5fa99..c37123f 100644
3
+ --- a/FISH/cfgs/config_eval.yaml
4
+ +++ b/FISH/cfgs/config_eval.yaml
5
+ @@ -82,7 +82,7 @@ contact_estimation_model_ckpt_path: '~/fish_leon/contact_estimation/artifacts/17
6
+
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+ # Number of evaluation trajectories
8
+ # num_eval: 10
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+ -num_eval: 20
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+ +num_eval: 5
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+
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+ debug_timestamps: False
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+ open_loop: False
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+ @@ -144,9 +144,9 @@ load_checkpoint: ${agent.load_checkpoint}
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+ # wandb_run_id: '3465_2' # seed 2
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+
17
+ # crp_D+mask+contact+act history
18
+ -wandb_run_id: '4295_0'
19
+ +# wandb_run_id: '4295_0'
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+ # wandb_run_id: '4295_1' # seed 1
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+ -# wandb_run_id: '4295_2' # seed 2
22
+ +wandb_run_id: '4295_2' # seed 2
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+
24
+ # RGBD+mask+act history
25
+ # wandb_run_id: '1009_1' # seed 1
aq8qih16/wandb/run-20250121_215627-aq8qih16/files/media/table/eval/success_rate_ci_5_50e92e293996504485a1.table.json ADDED
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aq8qih16/wandb/run-20250121_215627-aq8qih16/files/media/table/eval/total_success_rate_ci_6_5f51e5dd50014acd45f6.table.json ADDED
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1
+
2
+ loaded agent with feature_type: 180x240_crpdstlhw24x51x130x130_1_D_2.0_msk_channels_EE_obj_mask_cntct_0.1_DTC_clmpd_lrnbl_nrmls_DTCmask_adpt_lrnbl_both_lr_0.0001_wd_0.0_local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9_acthist_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1
3
+ [INFO] [1737514596.691561]: resetting environment
4
+ [INFO] [1737514596.699027]: cleared current plan
5
+ [INFO] [1737514596.700395]: moving to home
6
+ [INFO] [1737514597.702531]: reached home
7
+ [INFO] [1737514597.703768]: reset action history
8
+ [INFO] [1737514600.413148]: environment reset
9
+ Starting episode 0
10
+ [INFO] [1737514600.417071]: resetting environment
11
+ [INFO] [1737514600.425348]: cleared current plan
12
+ [INFO] [1737514600.426590]: moving to home
13
+ [INFO] [1737514601.428677]: reached home
14
+ [INFO] [1737514601.429937]: reset action history
15
+ [INFO] [1737514604.139755]: environment reset
16
+ Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
17
+ proceeding to start episode!
18
+ [INFO] [1737514610.243278]: resetting environment
19
+ [INFO] [1737514610.247497]: cleared current plan
20
+ [INFO] [1737514610.248347]: moving to home
21
+ [INFO] [1737514611.251252]: reached home
22
+ [INFO] [1737514611.252508]: reset action history
23
+ [INFO] [1737514613.961512]: environment reset
24
+ bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/episode_rosbags/episode_0_2025-01-21-21-56-53.bag
25
+ ... logging to /home/leonmkim/.ros/log/1b77c894-d3af-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2658535.log
26
+ started roslaunch server http://158.130.50.37:37103/
27
+ SUMMARY
28
+ ========
29
+ PARAMETERS
30
+ * /rosdistro: noetic
31
+ * /rosversion: 1.16.0
32
+ NODES
33
+ /
34
+ print_text (rostopic/rostopic)
35
+ pub_text (rostopic/rostopic)
36
+ rosbag_record (rosbag/record)
37
+ ROS_MASTER_URI=http://localhost:11311
38
+ process[pub_text-1]: started with pid [2658816]
39
+ process[print_text-2]: started with pid [2658817]
40
+ process[rosbag_record-3]: started with pid [2658841]
41
+ started bagging!
42
+ For topic gripper_width: timestamp difference is -110124898 for nearest: 1737514623412475753 - target: 1737514623522600651 at idx 118
43
+ For topic gripper_width: timestamp difference is 104995647 for nearest: 1737514631879097381 - target: 1737514631774101734 at idx 227
44
+ [INFO] [1737514648.649560]: Storing episode...
45
+ [rosbag_record-3] killing on exit
46
+ [print_text-2] killing on exit[pub_text-1] killing on exit
47
+ [INFO] [1737514649.432774]: Stored episode 1.
48
+ [INFO] [1737514649.433055]: Saving video...
49
+ [INFO] [1737514649.620873]: Video saved!
50
+ Starting episode 1
51
+ [INFO] [1737514649.654856]: resetting environment
52
+ [INFO] [1737514649.665393]: cleared current plan
53
+ [INFO] [1737514649.665646]: moving to home
54
+ [INFO] [1737514653.268612]: reached home
55
+ [INFO] [1737514653.269476]: reset action history
56
+ [INFO] [1737514655.985281]: environment reset
57
+ Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
58
+ proceeding to start episode!Comuting lower confidence bound
59
+ Comuting upper confidence bound
60
+ Comuting lower confidence bound
61
+ Comuting upper confidence bound
62
+ Comuting lower confidence bound
63
+ Comuting upper confidence bound
64
+ Comuting lower confidence bound
65
+ Comuting upper confidence bound
66
+ [INFO] [1737514660.919071]: resetting environment
67
+ [INFO] [1737514660.922799]: cleared current plan
68
+ [INFO] [1737514660.923004]: moving to home
69
+ [INFO] [1737514661.924446]: reached home
70
+ [INFO] [1737514661.924851]: reset action history
71
+ [INFO] [1737514664.631682]: environment reset
72
+ bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/episode_rosbags/episode_1_2025-01-21-21-57-44.bag
73
+ ... logging to /home/leonmkim/.ros/log/1b77c894-d3af-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2658535.log
74
+ started roslaunch server http://158.130.50.37:33751/
75
+ SUMMARY
76
+ ========
77
+ PARAMETERS
78
+ * /rosdistro: noetic
79
+ * /rosversion: 1.16.0
80
+ NODES
81
+ /
82
+ print_text (rostopic/rostopic)
83
+ pub_text (rostopic/rostopic)
84
+ rosbag_record (rosbag/record)
85
+ ROS_MASTER_URI=http://localhost:11311
86
+ process[pub_text-4]: started with pid [2658966]
87
+ process[print_text-5]: started with pid [2658967]
88
+ process[rosbag_record-6]: started with pid [2658991]
89
+ started bagging!
90
+ For topic gripper_width: timestamp difference is 106593307 for nearest: 1737514674179100450 - target: 1737514674072507143 at idx 131
91
+ For topic gripper_width: timestamp difference is 103005633 for nearest: 1737514676479166970 - target: 1737514676376161337 at idx 158
92
+ For topic gripper_width: timestamp difference is 107633475 for nearest: 1737514682212495927 - target: 1737514682104862452 at idx 229
93
+ For topic gripper_width: timestamp difference is 110766128 for nearest: 1737514686179140285 - target: 1737514686068374157 at idx 249
94
+ preempting episode
95
+ [INFO] [1737514688.385825]: Storing episode...
96
+ [rosbag_record-6] killing on exit
97
+ [print_text-5] killing on exit
98
+ [pub_text-4] killing on exit
99
+ [INFO] [1737514689.151948]: Stored episode 2.
100
+ [INFO] [1737514689.152710]: Saving video...
101
+ [INFO] [1737514689.758224]: Video saved!
102
+ Starting episode 2
103
+ [INFO] [1737514689.797635]: resetting environment
104
+ [INFO] [1737514689.810071]: cleared current plan
105
+ [INFO] [1737514689.810295]: moving to home
106
+ [WARN] [1737514689.569529]: Plan exhausted
107
+ [WARN] [1737514689.603680]: Plan exhausted
108
+ [WARN] [1737514689.643940]: Plan exhausted
109
+ [WARN] [1737514689.682726]: Plan exhausted
110
+ [WARN] [1737514689.723833]: Plan exhausted
111
+ [WARN] [1737514689.762747]: Plan exhausted
112
+ [WARN] [1737514689.802912]: Plan exhausted
113
+ [INFO] [1737514693.313321]: reached home
114
+ [INFO] [1737514693.314041]: reset action history
115
+ [INFO] [1737514696.046713]: environment reset
116
+ Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
117
+ proceeding to start episode!Comuting lower confidence bound
118
+ Comuting upper confidence bound
119
+ Comuting lower confidence bound
120
+ Comuting upper confidence bound
121
+ Comuting lower confidence bound
122
+ Comuting upper confidence bound
123
+ Comuting lower confidence bound
124
+ Comuting upper confidence bound
125
+ [INFO] [1737514699.453717]: resetting environment
126
+ [INFO] [1737514699.464025]: cleared current plan
127
+ [INFO] [1737514699.464673]: moving to home
128
+ [INFO] [1737514700.465255]: reached home
129
+ [INFO] [1737514700.466124]: reset action history
130
+ [INFO] [1737514703.176436]: environment reset
131
+ bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/episode_rosbags/episode_2_2025-01-21-21-58-23.bag
132
+ ... logging to /home/leonmkim/.ros/log/1b77c894-d3af-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2658535.log
133
+ started roslaunch server http://158.130.50.37:39825/
134
+ SUMMARY
135
+ ========
136
+ PARAMETERS
137
+ * /rosdistro: noetic
138
+ * /rosversion: 1.16.0
139
+ NODES
140
+ /
141
+ print_text (rostopic/rostopic)
142
+ pub_text (rostopic/rostopic)
143
+ rosbag_record (rosbag/record)
144
+ ROS_MASTER_URI=http://localhost:11311
145
+ process[pub_text-7]: started with pid [2659131]
146
+ process[print_text-8]: started with pid [2659132]
147
+ process[rosbag_record-9]: started with pid [2659133]
148
+ started bagging!
149
+ preempting episode
150
+ [INFO] [1737514724.738794]: Storing episode...
151
+ [rosbag_record-9] killing on exit
152
+ [print_text-8] killing on exit
153
+ [pub_text-7] killing on exit
154
+ [INFO] [1737514725.479513]: Stored episode 3.
155
+ [INFO] [1737514725.482895]: Saving video...
156
+ [INFO] [1737514725.797913]: Video saved!
157
+ Starting episode 3
158
+ [INFO] [1737514725.848090]: resetting environment
159
+ [INFO] [1737514725.864290]: cleared current plan
160
+ [INFO] [1737514725.864522]: moving to home
161
+ [WARN] [1737514725.856519]: Plan exhausted
162
+ [INFO] [1737514729.266786]: reached home
163
+ [INFO] [1737514729.278136]: reset action history
164
+ [INFO] [1737514732.065395]: environment reset
165
+ Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
166
+ proceeding to start episode!Comuting lower confidence bound
167
+ Comuting upper confidence bound
168
+ Comuting lower confidence bound
169
+ Comuting upper confidence bound
170
+ Comuting lower confidence bound
171
+ Comuting upper confidence bound
172
+ Comuting lower confidence bound
173
+ Comuting upper confidence bound
174
+ [INFO] [1737514732.893853]: resetting environment
175
+ [INFO] [1737514732.918730]: cleared current plan
176
+ [INFO] [1737514732.919291]: moving to home
177
+ [INFO] [1737514733.924172]: reached home
178
+ [INFO] [1737514733.925422]: reset action history
179
+ [INFO] [1737514736.703683]: environment reset
180
+ bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/episode_rosbags/episode_3_2025-01-21-21-58-56.bag
181
+ ... logging to /home/leonmkim/.ros/log/1b77c894-d3af-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2658535.log
182
+ started roslaunch server http://158.130.50.37:39607/
183
+ SUMMARY
184
+ ========
185
+ PARAMETERS
186
+ * /rosdistro: noetic
187
+ * /rosversion: 1.16.0
188
+ NODES
189
+ /
190
+ print_text (rostopic/rostopic)
191
+ pub_text (rostopic/rostopic)
192
+ rosbag_record (rosbag/record)
193
+ ROS_MASTER_URI=http://localhost:11311
194
+ process[pub_text-10]: started with pid [2659249]
195
+ process[print_text-11]: started with pid [2659250]
196
+ process[rosbag_record-12]: started with pid [2659274]
197
+ started bagging!
198
+ For topic gripper_width: timestamp difference is -105606791 for nearest: 1737514755412481311 - target: 1737514755518088102 at idx 249
199
+ preempting episode
200
+ [INFO] [1737514758.329752]: Storing episode...
201
+ [rosbag_record-12] killing on exit
202
+ [print_text-11] killing on exit[pub_text-10] killing on exit
203
+ [INFO] [1737514759.183883]: Stored episode 4.
204
+ [INFO] [1737514759.197186]: Saving video...
205
+ [INFO] [1737514759.846453]: Video saved!
206
+ Starting episode 4
207
+ [INFO] [1737514759.911809]: resetting environment
208
+ [INFO] [1737514759.953629]: cleared current plan
209
+ [INFO] [1737514759.958289]: moving to home
210
+ [WARN] [1737514759.578898]: Plan exhausted
211
+ [WARN] [1737514759.616068]: Plan exhausted
212
+ [WARN] [1737514759.655707]: Plan exhausted
213
+ [WARN] [1737514759.697895]: Plan exhausted
214
+ [WARN] [1737514759.743804]: Plan exhausted
215
+ [WARN] [1737514759.786479]: Plan exhausted
216
+ [WARN] [1737514759.815648]: Plan exhausted
217
+ [WARN] [1737514759.856194]: Plan exhausted
218
+ [WARN] [1737514759.895733]: Plan exhausted
219
+ [WARN] [1737514759.936064]: Plan exhausted
220
+ [INFO] [1737514763.366534]: reached home
221
+ [INFO] [1737514763.377586]: reset action history
222
+ [INFO] [1737514766.173014]: environment reset
223
+ Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
224
+ proceeding to start episode!
225
+ Comuting lower confidence bound
226
+ Comuting upper confidence bound
227
+ Comuting lower confidence bound
228
+ Comuting upper confidence bound
229
+ Comuting lower confidence bound
230
+ Comuting upper confidence bound
231
+ Comuting lower confidence bound
232
+ Comuting upper confidence bound
233
+ [INFO] [1737514766.255645]: resetting environment
234
+ [INFO] [1737514766.276761]: cleared current plan
235
+ [INFO] [1737514766.277018]: moving to home
236
+ [INFO] [1737514767.288630]: reached home
237
+ [INFO] [1737514767.292424]: reset action history
238
+ [INFO] [1737514770.135118]: environment reset
239
+ bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/4295_2/aq8qih16/episode_rosbags/episode_4_2025-01-21-21-59-30.bag
240
+ ... logging to /home/leonmkim/.ros/log/1b77c894-d3af-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2658535.log
241
+ started roslaunch server http://158.130.50.37:36367/
242
+ SUMMARY
243
+ ========
244
+ PARAMETERS
245
+ * /rosdistro: noetic
246
+ * /rosversion: 1.16.0
247
+ NODES
248
+ /
249
+ print_text (rostopic/rostopic)
250
+ pub_text (rostopic/rostopic)
251
+ rosbag_record (rosbag/record)
252
+ ROS_MASTER_URI=http://localhost:11311
253
+ process[pub_text-13]: started with pid [2659411]
254
+ process[print_text-14]: started with pid [2659412]
255
+ process[rosbag_record-15]: started with pid [2659413]
256
+ started bagging!
257
+ preempting episode
258
+ [INFO] [1737514802.147038]: Storing episode...
259
+ [rosbag_record-15] killing on exit
260
+ [pub_text-13] killing on exit
261
+ [print_text-14] killing on exit
262
+ [INFO] [1737514802.902741]: Stored episode 5.
263
+ [INFO] [1737514802.906340]: Saving video...
264
+ [INFO] [1737514803.448148]: Video saved!
265
+ [INFO] [1737514803.508600]: resetting environment
266
+ [INFO] [1737514803.551344]: cleared current plan
267
+ [INFO] [1737514803.551591]: moving to home
268
+ [WARN] [1737514803.456230]: Plan exhausted
269
+ [WARN] [1737514803.495633]: Plan exhausted
270
+ [WARN] [1737514803.535896]: Plan exhausted
271
+ [INFO] [1737514807.053224]: reached home
272
+ [INFO] [1737514807.064935]: reset action history
273
+ [INFO] [1737514809.915953]: environment reset
274
+ Evaluation finished. To wrap up, rate prev episode, press 0 for failure and 1 for success
275
+ proceeding to start episode!Comuting lower confidence bound
276
+ Comuting upper confidence bound
277
+ Comuting lower confidence bound
278
+ Comuting upper confidence bound
279
+ Comuting lower confidence bound
280
+ Comuting upper confidence bound
281
+ Comuting lower confidence bound
282
+ Comuting upper confidence bound
283
+ Comuting lower confidence bound
284
+ Comuting upper confidence bound
285
+ Comuting lower confidence bound
286
+ Comuting upper confidence bound
287
+ Comuting lower confidence bound
288
+ Comuting upper confidence bound
289
+ Comuting lower confidence bound
290
+ Comuting upper confidence bound
291
+ proceeding to start episode!
aq8qih16/wandb/run-20250121_215627-aq8qih16/files/requirements.txt ADDED
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