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490
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514
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521
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530
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535
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541
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552
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558
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569
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+ - action.right_gripper_pos
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+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
584
+ default_instruction: Perform the default behavior.
585
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586
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587
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588
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589
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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635
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637
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639
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640
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642
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643
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644
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645
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646
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647
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648
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649
+ apply_to:
650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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669
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671
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675
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680
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681
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682
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686
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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700
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701
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702
+ - action.gripper_position
703
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
704
+ default_instruction: Perform the default behavior.
705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
+ real_gr1_arms_waist_annotated: 3
717
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718
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719
+ dexmg_gr1_arms_waist_fourier: 6
720
+ robocasa_single_arm: 7
721
+ onex_eve_gripper: 8
722
+ robocasa_gr1_arms_only_inspire_hands: 9
723
+ robocasa_gr1_arms_only_fourier_hands: 10
724
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
725
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
726
+ robocasa_panda_omron: 13
727
+ robocasa_bimanual_panda_parallel_gripper: 15
728
+ robocasa_bimanual_panda_inspire_hand: 16
729
+ oxe_droid: 17
730
+ oxe_fractal: 18
731
+ oxe_language_table: 19
732
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733
+ real_panda_single_arm: 21
734
+ hot3d_hands_only: 23
735
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736
+ robocasa_gr1_arms_waist_fourier_hands: 25
737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
+ language_table_sim: 7
748
+ gr1_isaac: 0
749
+ sim_behavior_r1_pro: 31
750
+ mecka_hands: 27
751
+ real_r1_pro_sharpa: 28
752
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
753
+ agibot:
754
+ _target_: groot.vla.data.transform.ComposedModalityTransform
755
+ transforms:
756
+ - _target_: groot.vla.data.transform.VideoToTensor
757
+ apply_to:
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762
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764
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767
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768
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769
+ apply_to:
770
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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785
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786
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791
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797
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799
+ apply_to:
800
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801
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806
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808
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809
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810
+ state.right_effector_position: q99
811
+ state.head_position: q99
812
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813
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814
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816
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823
+ apply_to:
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825
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826
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829
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830
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832
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833
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834
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+ - _target_: groot.vla.data.transform.ConcatTransform
840
+ video_concat_order:
841
+ - video.top_head
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+ - video.hand_left
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+ - video.hand_right
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+ state_concat_order:
845
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+ - state.right_arm_joint_position
847
+ - state.left_effector_position
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+ - state.right_effector_position
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+ - state.head_position
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+ - state.waist_position
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+ action_concat_order:
852
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853
+ - action.right_arm_joint_position
854
+ - action.left_effector_position
855
+ - action.right_effector_position
856
+ - action.head_position
857
+ - action.waist_position
858
+ - action.robot_velocity
859
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
860
+ default_instruction: Perform the default behavior.
861
+ language_dropout_prob: 0.0
862
+ always_use_default_instruction: false
863
+ max_state_dim: 64
864
+ max_action_dim: 32
865
+ max_length: 512
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+ state_horizon: 1
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+ action_horizon: 24
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+ embodiment_tag_mapping:
869
+ real_gr1_arms_only: 0
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+ real_gr1_arms_waist: 2
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+ real_gr1_arms_waist_annotated: 3
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+ dexmg_gr1_arms_only_inspire: 4
874
+ dexmg_gr1_arms_only_fourier: 5
875
+ dexmg_gr1_arms_waist_fourier: 6
876
+ robocasa_single_arm: 7
877
+ onex_eve_gripper: 8
878
+ robocasa_gr1_arms_only_inspire_hands: 9
879
+ robocasa_gr1_arms_only_fourier_hands: 10
880
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
881
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
882
+ robocasa_panda_omron: 13
883
+ robocasa_bimanual_panda_parallel_gripper: 15
884
+ robocasa_bimanual_panda_inspire_hand: 16
885
+ oxe_droid: 17
886
+ oxe_fractal: 18
887
+ oxe_language_table: 19
888
+ oxe_bridge: 20
889
+ real_panda_single_arm: 21
890
+ hot3d_hands_only: 23
891
+ gr1_unified: 24
892
+ robocasa_gr1_arms_waist_fourier_hands: 25
893
+ agibot: 26
894
+ bimanual_ur3: 26
895
+ lapa: 27
896
+ oxe_mutex: 28
897
+ oxe_roboset: 29
898
+ oxe_plex: 30
899
+ dream: 31
900
+ yam: 32
901
+ xdof: 22
902
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903
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904
+ gr1_isaac: 0
905
+ sim_behavior_r1_pro: 31
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+ mecka_hands: 27
907
+ real_r1_pro_sharpa: 28
908
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
909
+ yam:
910
+ _target_: groot.vla.data.transform.ComposedModalityTransform
911
+ transforms:
912
+ - _target_: groot.vla.data.transform.VideoToTensor
913
+ apply_to:
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+ - video.top_camera-images-rgb
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+ - video.left_camera-images-rgb
916
+ - video.right_camera-images-rgb
917
+ - _target_: groot.vla.data.transform.VideoCrop
918
+ apply_to:
919
+ - video.top_camera-images-rgb
920
+ - video.left_camera-images-rgb
921
+ - video.right_camera-images-rgb
922
+ scale: 0.95
923
+ mode: random
924
+ - _target_: groot.vla.data.transform.VideoResize
925
+ apply_to:
926
+ - video.top_camera-images-rgb
927
+ - video.left_camera-images-rgb
928
+ - video.right_camera-images-rgb
929
+ height: 176
930
+ width: 320
931
+ interpolation: linear
932
+ - _target_: groot.vla.data.transform.VideoColorJitter
933
+ apply_to:
934
+ - video.top_camera-images-rgb
935
+ - video.left_camera-images-rgb
936
+ - video.right_camera-images-rgb
937
+ brightness: 0.3
938
+ contrast: 0.4
939
+ saturation: 0.5
940
+ hue: 0.08
941
+ - _target_: groot.vla.data.transform.VideoToNumpy
942
+ apply_to:
943
+ - video.top_camera-images-rgb
944
+ - video.left_camera-images-rgb
945
+ - video.right_camera-images-rgb
946
+ - _target_: groot.vla.data.transform.StateActionToTensor
947
+ apply_to:
948
+ - state.left_joint_pos
949
+ - state.left_gripper_pos
950
+ - state.right_joint_pos
951
+ - state.right_gripper_pos
952
+ - _target_: groot.vla.data.transform.StateActionTransform
953
+ apply_to:
954
+ - state.left_joint_pos
955
+ - state.left_gripper_pos
956
+ - state.right_joint_pos
957
+ - state.right_gripper_pos
958
+ normalization_modes:
959
+ state.left_joint_pos: q99
960
+ state.left_gripper_pos: q99
961
+ state.right_joint_pos: q99
962
+ state.right_gripper_pos: q99
963
+ - _target_: groot.vla.data.transform.StateActionToTensor
964
+ apply_to:
965
+ - action.left_joint_pos
966
+ - action.left_gripper_pos
967
+ - action.right_joint_pos
968
+ - action.right_gripper_pos
969
+ - _target_: groot.vla.data.transform.StateActionTransform
970
+ apply_to:
971
+ - action.left_joint_pos
972
+ - action.left_gripper_pos
973
+ - action.right_joint_pos
974
+ - action.right_gripper_pos
975
+ normalization_modes:
976
+ action.left_joint_pos: q99
977
+ action.left_gripper_pos: q99
978
+ action.right_joint_pos: q99
979
+ action.right_gripper_pos: q99
980
+ - _target_: groot.vla.data.transform.ConcatTransform
981
+ video_concat_order:
982
+ - video.top_camera-images-rgb
983
+ - video.left_camera-images-rgb
984
+ - video.right_camera-images-rgb
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+ state_concat_order:
986
+ - state.left_joint_pos
987
+ - state.left_gripper_pos
988
+ - state.right_joint_pos
989
+ - state.right_gripper_pos
990
+ action_concat_order:
991
+ - action.left_joint_pos
992
+ - action.left_gripper_pos
993
+ - action.right_joint_pos
994
+ - action.right_gripper_pos
995
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
996
+ default_instruction: Perform the default behavior.
997
+ language_dropout_prob: 0.0
998
+ always_use_default_instruction: false
999
+ max_state_dim: 64
1000
+ max_action_dim: 32
1001
+ max_length: 512
1002
+ state_horizon: 1
1003
+ action_horizon: 24
1004
+ embodiment_tag_mapping:
1005
+ real_gr1_arms_only: 0
1006
+ real_gr1_arms_only_annotated: 1
1007
+ real_gr1_arms_waist: 2
1008
+ real_gr1_arms_waist_annotated: 3
1009
+ dexmg_gr1_arms_only_inspire: 4
1010
+ dexmg_gr1_arms_only_fourier: 5
1011
+ dexmg_gr1_arms_waist_fourier: 6
1012
+ robocasa_single_arm: 7
1013
+ onex_eve_gripper: 8
1014
+ robocasa_gr1_arms_only_inspire_hands: 9
1015
+ robocasa_gr1_arms_only_fourier_hands: 10
1016
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1017
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1018
+ robocasa_panda_omron: 13
1019
+ robocasa_bimanual_panda_parallel_gripper: 15
1020
+ robocasa_bimanual_panda_inspire_hand: 16
1021
+ oxe_droid: 17
1022
+ oxe_fractal: 18
1023
+ oxe_language_table: 19
1024
+ oxe_bridge: 20
1025
+ real_panda_single_arm: 21
1026
+ hot3d_hands_only: 23
1027
+ gr1_unified: 24
1028
+ robocasa_gr1_arms_waist_fourier_hands: 25
1029
+ agibot: 26
1030
+ bimanual_ur3: 26
1031
+ lapa: 27
1032
+ oxe_mutex: 28
1033
+ oxe_roboset: 29
1034
+ oxe_plex: 30
1035
+ dream: 31
1036
+ yam: 32
1037
+ xdof: 22
1038
+ gr1_unified_segmentation: 14
1039
+ language_table_sim: 7
1040
+ gr1_isaac: 0
1041
+ sim_behavior_r1_pro: 31
1042
+ mecka_hands: 27
1043
+ real_r1_pro_sharpa: 28
1044
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1045
+ metadata_versions:
1046
+ bimanual_ur3: '0221'
1047
+ oxe_droid: '0221'
1048
+ agibot: '0221'
1049
+ yam: '0221'
1050
+ fps:
1051
+ bimanual_ur3: 30
1052
+ yam: 30
1053
+ dataset_kwargs:
1054
+ video_backend: decord
1055
+ use_global_metadata: false
1056
+ max_chunk_size: 4
1057
+ relative_action: true
1058
+ relative_action_keys:
1059
+ - left_joint_pos
1060
+ - left_gripper_pos
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+ - right_joint_pos
1062
+ - right_gripper_pos
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+ relative_action_per_horizon: false
1064
+ mixture_kwargs:
1065
+ training: true
1066
+ balance_dataset_weights: false
1067
+ seed: 42
1068
+ shard_sampling_rate: 0.1
1069
+ trainer:
1070
+ _target_: groot.vla.experiment.VLATrainer
1071
+ _partial_: true
1072
+ _recursive_: false
1073
+ callbacks: null
1074
+ model: ???
1075
+ train_dataset: ???
1076
+ compute_dtype: ???
1077
+ benchmark_time: false
1078
+ enable_profiling: false
1079
+ profiling_steps: 5
1080
+ enable_prof_callback: false
1081
+ profile_start_step: 50
1082
+ profile_warmup_steps: 1
1083
+ profile_active_steps: 3
1084
+ profile_record_shapes: false
1085
+ profile_with_stack: false
1086
+ profile_memory: false
1087
+ wandb_project: dreamzero
1088
+ output_dir: /root/WAM/checkpoints/dreamzero_bimanual_ur3_lora
1089
+ load_from_yaml: null
1090
+ gear_credentials: null
1091
+ upload_checkpoints: false
1092
+ upload_every: 1000
1093
+ upload_last_n_checkpoints: 5
1094
+ remove_unused_columns: false
1095
+ bf16: true
1096
+ tf32: false
1097
+ global_batch_size: null
1098
+ raise_error_if_global_batch_size_not_set: false
1099
+ per_device_train_batch_size: 1
1100
+ per_device_eval_batch_size: 64
1101
+ gradient_accumulation_steps: 1
1102
+ dataloader_num_workers: 0
1103
+ dataloader_pin_memory: false
1104
+ dataloader_persistent_workers: true
1105
+ optim: adamw_torch
1106
+ learning_rate: 0.0001
1107
+ adam_beta1: 0.95
1108
+ adam_beta2: 0.999
1109
+ adam_epsilon: 1.0e-08
1110
+ weight_decay: 0
1111
+ lr_scheduler_type: cosine
1112
+ warmup_ratio: 0.05
1113
+ logging_steps: 10.0
1114
+ num_train_epochs: 1000
1115
+ max_steps: 20000
1116
+ save_strategy: steps
1117
+ save_steps: 10000
1118
+ eval_strategy: 'no'
1119
+ save_total_limit: 2
1120
+ report_to: none
1121
+ seed: 42
1122
+ do_eval: false
1123
+ gradient_checkpointing: false
1124
+ ddp_find_unused_parameters: false
1125
+ ddp_bucket_cap_mb: 100
1126
+ ray_num_workers: ???
1127
+ eval_bf16: true
1128
+ torch_compile_mode: null
1129
+ pretrained_model_path: /root/WAM/checkpoints/DreamZero-AgiBot
1130
+ only_tune_projectors: false
1131
+ save_llm: false
1132
+ save_lora_only: true
1133
+ save_value_model: false
1134
+ save_q_model: false
1135
+ download_cache: false
1136
+ training_args:
1137
+ _target_: transformers.TrainingArguments
1138
+ output_dir: /root/WAM/checkpoints/dreamzero_bimanual_ur3_lora
1139
+ run_name: dreamzero_bimanual_ur3_lora
1140
+ remove_unused_columns: false
1141
+ deepspeed: groot/vla/configs/deepspeed/zero2.json
1142
+ gradient_checkpointing: true
1143
+ bf16: true
1144
+ tf32: false
1145
+ per_device_train_batch_size: 1
1146
+ per_device_eval_batch_size: 64
1147
+ gradient_accumulation_steps: 1
1148
+ dataloader_num_workers: 0
1149
+ dataloader_pin_memory: false
1150
+ dataloader_persistent_workers: true
1151
+ optim: adamw_torch
1152
+ adam_beta1: 0.95
1153
+ adam_beta2: 0.999
1154
+ adam_epsilon: 1.0e-08
1155
+ learning_rate: 1.0e-05
1156
+ weight_decay: 0
1157
+ warmup_ratio: 0.05
1158
+ lr_scheduler_type: constant
1159
+ logging_steps: 10.0
1160
+ num_train_epochs: 1000
1161
+ max_steps: 20000
1162
+ save_strategy: steps
1163
+ save_steps: 10000
1164
+ save_total_limit: 2
1165
+ report_to: none
1166
+ seed: 42
1167
+ do_eval: false
1168
+ ddp_find_unused_parameters: false
1169
+ ddp_bucket_cap_mb: 100
1170
+ torch_compile_mode: null
1171
+ profile_dir: null
1172
+ backbone_hidden_size: 0
1173
+ backbone_cfg:
1174
+ _target_: groot.vla.model.dreamzero.backbone.identity.IdentityBackbone
1175
+ action_head_cfg:
1176
+ config:
1177
+ backbone_features_projector_cfg: null
1178
+ _target_: groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHeadConfig
1179
+ _recursive_: false
1180
+ tiled: false
1181
+ tile_size_height: 34
1182
+ tile_size_width: 34
1183
+ tile_stride_height: 18
1184
+ tile_stride_width: 16
1185
+ lora_rank: 4
1186
+ lora_alpha: 4
1187
+ num_frames: 33
1188
+ num_frame_per_block: 2
1189
+ lora_target_modules: q,k,v,o,ffn.0,ffn.2
1190
+ init_lora_weights: kaiming
1191
+ train_architecture: lora
1192
+ use_gradient_checkpointing: true
1193
+ add_pos_embed: true
1194
+ model_dtype: float32
1195
+ max_state_dim: 64
1196
+ max_action_dim: 32
1197
+ action_loss_embodiment_ids:
1198
+ - 26
1199
+ - 17
1200
+ - 32
1201
+ hidden_size: 64
1202
+ input_embedding_dim: 1536
1203
+ backbone_embedding_dim: 0
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+ repa_layer: 8
1205
+ repa_coeff: 1.0
1206
+ load_pretrained_det_decode_layer_path: null
1207
+ freeze_decode_layer: false
1208
+ expand_batch: null
1209
+ use_vlln: true
1210
+ vl_self_attention_cfg:
1211
+ _target_: groot.vla.model.n1_5.modules.cross_attention_dit.SelfAttentionTransformer
1212
+ positional_embeddings: null
1213
+ num_layers: 4
1214
+ num_attention_heads: 24
1215
+ attention_head_dim: 64
1216
+ dropout: 0.2
1217
+ final_dropout: true
1218
+ diffusion_model_cfg:
1219
+ _target_: groot.vla.model.dreamzero.modules.wan_video_dit_action_casual_chunk.CausalWanModel
1220
+ _convert_: object
1221
+ diffusion_model_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P
1222
+ model_type: i2v
1223
+ frame_seqlen: 880
1224
+ dim: 5120
1225
+ in_dim: 36
1226
+ ffn_dim: 13824
1227
+ out_dim: 16
1228
+ freq_dim: 256
1229
+ eps: 1.0e-06
1230
+ num_heads: 40
1231
+ num_layers: 40
1232
+ max_chunk_size: 4
1233
+ num_frame_per_block: 2
1234
+ num_action_per_block: 24
1235
+ num_state_per_block: 1
1236
+ text_encoder_cfg:
1237
+ _target_: groot.vla.model.dreamzero.modules.wan_video_text_encoder.WanTextEncoder
1238
+ _convert_: object
1239
+ text_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
1240
+ image_encoder_cfg:
1241
+ _target_: groot.vla.model.dreamzero.modules.wan_video_image_encoder.WanImageEncoder
1242
+ _convert_: object
1243
+ image_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
1244
+ vae_cfg:
1245
+ _target_: groot.vla.model.dreamzero.modules.wan_video_vae.WanVideoVAE
1246
+ _convert_: object
1247
+ vae_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
1248
+ action_dim: 32
1249
+ action_horizon: 24
1250
+ num_inference_timesteps: 4
1251
+ noise_beta_alpha: 1.5
1252
+ noise_beta_beta: 1.0
1253
+ noise_s: 0.999
1254
+ num_timestep_buckets: 1000
1255
+ decouple_video_action_noise: false
1256
+ video_noise_beta_alpha: 3.0
1257
+ video_noise_beta_beta: 1.0
1258
+ tune_projector: true
1259
+ tune_diffusion_model: true
1260
+ skip_component_loading: true
1261
+ defer_lora_injection: true
1262
+ _target_: groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHead
1263
+ _convert_: object
1264
+ add_pos_embed: true
1265
+ hidden_size: 64
1266
+ attn_dropout: 0.2
1267
+ repa_layer: 8
1268
+ repa_coeff: 1.0
1269
+ load_pretrained_det_decode_layer_path: null
1270
+ expand_batch: null
1271
+ dit_version: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P
1272
+ text_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
1273
+ image_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
1274
+ vae_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
1275
+ train_architecture: lora
1276
+ num_frame_per_block: 2
1277
+ num_action_per_block: 24
1278
+ num_state_per_block: 1
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+ frame_seqlen: 880
1280
+ embodiment_tag_to_projector_index:
1281
+ real_gr1_arms_only: 0
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+ real_gr1_arms_only_annotated: 1
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+ real_gr1_arms_waist: 2
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+ real_gr1_arms_waist_annotated: 3
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+ dexmg_gr1_arms_only_inspire: 4
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+ dexmg_gr1_arms_waist_fourier: 6
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+ onex_eve_gripper: 8
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+ robocasa_gr1_arms_only_inspire_hands: 9
1291
+ robocasa_gr1_arms_only_fourier_hands: 10
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+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
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+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
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+ robocasa_panda_omron: 13
1295
+ robocasa_bimanual_panda_parallel_gripper: 15
1296
+ robocasa_bimanual_panda_inspire_hand: 16
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+ oxe_droid: 17
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+ oxe_fractal: 18
1299
+ oxe_language_table: 19
1300
+ oxe_bridge: 20
1301
+ real_panda_single_arm: 21
1302
+ hot3d_hands_only: 23
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+ gr1_unified: 24
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1306
+ bimanual_ur3: 26
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+ oxe_plex: 30
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+ language_table_sim: 7
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+ mecka_hands: 27
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1320
+ max_length: 512
1321
+ num_views: 3
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+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1323
+ data_collator:
1324
+ _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DefaultDataCollator
1325
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1326
+ max_length: 512
1327
+ num_views: 3
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+ embodiment_tag_mapping:
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+ dexmg_gr1_arms_only_inspire: 4
1334
+ dexmg_gr1_arms_only_fourier: 5
1335
+ dexmg_gr1_arms_waist_fourier: 6
1336
+ robocasa_single_arm: 7
1337
+ onex_eve_gripper: 8
1338
+ robocasa_gr1_arms_only_inspire_hands: 9
1339
+ robocasa_gr1_arms_only_fourier_hands: 10
1340
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1341
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1342
+ robocasa_panda_omron: 13
1343
+ robocasa_bimanual_panda_parallel_gripper: 15
1344
+ robocasa_bimanual_panda_inspire_hand: 16
1345
+ oxe_droid: 17
1346
+ oxe_fractal: 18
1347
+ oxe_language_table: 19
1348
+ oxe_bridge: 20
1349
+ real_panda_single_arm: 21
1350
+ hot3d_hands_only: 23
1351
+ gr1_unified: 24
1352
+ robocasa_gr1_arms_waist_fourier_hands: 25
1353
+ agibot: 26
1354
+ bimanual_ur3: 26
1355
+ lapa: 27
1356
+ oxe_mutex: 28
1357
+ oxe_roboset: 29
1358
+ oxe_plex: 30
1359
+ dream: 31
1360
+ yam: 32
1361
+ xdof: 22
1362
+ gr1_unified_segmentation: 14
1363
+ language_table_sim: 7
1364
+ gr1_isaac: 0
1365
+ sim_behavior_r1_pro: 31
1366
+ mecka_hands: 27
1367
+ real_r1_pro_sharpa: 28
1368
+ num_visual_tokens_per_frame: 16
1369
+ max_state_dim: 64
1370
+ max_action_dim: 32
1371
+ language_dropout_prob: 0.0
1372
+ model_specific_transform:
1373
+ _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1374
+ default_instruction: Perform the default behavior.
1375
+ language_dropout_prob: 0.0
1376
+ always_use_default_instruction: false
1377
+ max_state_dim: 64
1378
+ max_action_dim: 32
1379
+ max_length: 512
1380
+ state_horizon: 1
1381
+ action_horizon: 24
1382
+ embodiment_tag_mapping:
1383
+ real_gr1_arms_only: 0
1384
+ real_gr1_arms_only_annotated: 1
1385
+ real_gr1_arms_waist: 2
1386
+ real_gr1_arms_waist_annotated: 3
1387
+ dexmg_gr1_arms_only_inspire: 4
1388
+ dexmg_gr1_arms_only_fourier: 5
1389
+ dexmg_gr1_arms_waist_fourier: 6
1390
+ robocasa_single_arm: 7
1391
+ onex_eve_gripper: 8
1392
+ robocasa_gr1_arms_only_inspire_hands: 9
1393
+ robocasa_gr1_arms_only_fourier_hands: 10
1394
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1395
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1396
+ robocasa_panda_omron: 13
1397
+ robocasa_bimanual_panda_parallel_gripper: 15
1398
+ robocasa_bimanual_panda_inspire_hand: 16
1399
+ oxe_droid: 17
1400
+ oxe_fractal: 18
1401
+ oxe_language_table: 19
1402
+ oxe_bridge: 20
1403
+ real_panda_single_arm: 21
1404
+ hot3d_hands_only: 23
1405
+ gr1_unified: 24
1406
+ robocasa_gr1_arms_waist_fourier_hands: 25
1407
+ agibot: 26
1408
+ bimanual_ur3: 26
1409
+ lapa: 27
1410
+ oxe_mutex: 28
1411
+ oxe_roboset: 29
1412
+ oxe_plex: 30
1413
+ dream: 31
1414
+ yam: 32
1415
+ xdof: 22
1416
+ gr1_unified_segmentation: 14
1417
+ language_table_sim: 7
1418
+ gr1_isaac: 0
1419
+ sim_behavior_r1_pro: 31
1420
+ mecka_hands: 27
1421
+ real_r1_pro_sharpa: 28
1422
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1423
+ use_global_metadata: false
1424
+ num_frames: 33
1425
+ action_horizon: 24
1426
+ state_horizon: 1
1427
+ image_resolution_width: 320
1428
+ image_resolution_height: 176
1429
+ image_resolution_width_single_frame: 256
1430
+ image_resolution_height_single_frame: 256
1431
+ totensor_cfg:
1432
+ _target_: groot.vla.data.transform.VideoToTensor
1433
+ apply_to: ???
1434
+ crop_cfg:
1435
+ _target_: groot.vla.data.transform.VideoCrop
1436
+ apply_to: ???
1437
+ scale: 0.95
1438
+ mode: random
1439
+ resize_cfg:
1440
+ _target_: groot.vla.data.transform.VideoResize
1441
+ apply_to: ???
1442
+ height: 176
1443
+ width: 320
1444
+ interpolation: linear
1445
+ resize_cfg_single_frame:
1446
+ _target_: groot.vla.data.transform.VideoResize
1447
+ apply_to: ???
1448
+ height: 256
1449
+ width: 256
1450
+ interpolation: linear
1451
+ color_jitter_cfg:
1452
+ _target_: groot.vla.data.transform.VideoColorJitter
1453
+ apply_to: ???
1454
+ brightness: 0.3
1455
+ contrast: 0.4
1456
+ saturation: 0.5
1457
+ hue: 0.08
1458
+ random_grayscale_cfg:
1459
+ _target_: groot.vla.data.transform.VideoRandomGrayscale
1460
+ apply_to: ???
1461
+ p: 0.1
1462
+ random_posterize_cfg:
1463
+ _target_: groot.vla.data.transform.VideoRandomPosterize
1464
+ apply_to: ???
1465
+ bits: 4
1466
+ p: 0.1
1467
+ normalize_cfg:
1468
+ _target_: groot.vla.data.transform.VideoNormalize
1469
+ apply_to: ???
1470
+ mean:
1471
+ - 0.5
1472
+ - 0.5
1473
+ - 0.5
1474
+ std:
1475
+ - 0.5
1476
+ - 0.5
1477
+ - 0.5
1478
+ to_numpy_cfg:
1479
+ _target_: groot.vla.data.transform.VideoToNumpy
1480
+ apply_to: ???
1481
+ modality_config_bimanual_ur3:
1482
+ video:
1483
+ _target_: groot.vla.data.dataset.ModalityConfig
1484
+ delta_indices:
1485
+ - 0
1486
+ - 1
1487
+ - 2
1488
+ - 3
1489
+ - 4
1490
+ - 5
1491
+ - 6
1492
+ - 7
1493
+ - 8
1494
+ - 9
1495
+ - 10
1496
+ - 11
1497
+ - 12
1498
+ - 13
1499
+ - 14
1500
+ - 15
1501
+ - 16
1502
+ - 17
1503
+ - 18
1504
+ - 19
1505
+ - 20
1506
+ - 21
1507
+ - 22
1508
+ - 23
1509
+ - 24
1510
+ - 25
1511
+ - 26
1512
+ - 27
1513
+ - 28
1514
+ - 29
1515
+ - 30
1516
+ - 31
1517
+ - 32
1518
+ eval_delta_indices:
1519
+ - 0
1520
+ modality_keys:
1521
+ - video.top_head
1522
+ - video.hand_left
1523
+ - video.hand_right
1524
+ state:
1525
+ _target_: groot.vla.data.dataset.ModalityConfig
1526
+ delta_indices:
1527
+ - 0
1528
+ modality_keys:
1529
+ - state.left_joint_pos
1530
+ - state.left_gripper_pos
1531
+ - state.right_joint_pos
1532
+ - state.right_gripper_pos
1533
+ action:
1534
+ _target_: groot.vla.data.dataset.ModalityConfig
1535
+ delta_indices:
1536
+ - 0
1537
+ - 1
1538
+ - 2
1539
+ - 3
1540
+ - 4
1541
+ - 5
1542
+ - 6
1543
+ - 7
1544
+ - 8
1545
+ - 9
1546
+ - 10
1547
+ - 11
1548
+ - 12
1549
+ - 13
1550
+ - 14
1551
+ - 15
1552
+ - 16
1553
+ - 17
1554
+ - 18
1555
+ - 19
1556
+ - 20
1557
+ - 21
1558
+ - 22
1559
+ - 23
1560
+ modality_keys:
1561
+ - action.left_joint_pos
1562
+ - action.left_gripper_pos
1563
+ - action.right_joint_pos
1564
+ - action.right_gripper_pos
1565
+ language:
1566
+ _target_: groot.vla.data.dataset.ModalityConfig
1567
+ delta_indices:
1568
+ - 0
1569
+ modality_keys:
1570
+ - annotation.task
1571
+ transform_bimanual_ur3:
1572
+ _target_: groot.vla.data.transform.ComposedModalityTransform
1573
+ transforms:
1574
+ - _target_: groot.vla.data.transform.VideoToTensor
1575
+ apply_to:
1576
+ - video.top_head
1577
+ - _target_: groot.vla.data.transform.VideoCrop
1578
+ apply_to:
1579
+ - video.top_head
1580
+ scale: 0.95
1581
+ mode: random
1582
+ - _target_: groot.vla.data.transform.VideoResize
1583
+ apply_to:
1584
+ - video.top_head
1585
+ height: 176
1586
+ width: 320
1587
+ interpolation: linear
1588
+ - _target_: groot.vla.data.transform.VideoToTensor
1589
+ apply_to:
1590
+ - video.hand_left
1591
+ - video.hand_right
1592
+ - _target_: groot.vla.data.transform.VideoCrop
1593
+ apply_to:
1594
+ - video.hand_left
1595
+ - video.hand_right
1596
+ scale: 0.95
1597
+ mode: random
1598
+ - _target_: groot.vla.data.transform.VideoResize
1599
+ apply_to:
1600
+ - video.hand_left
1601
+ - video.hand_right
1602
+ height: 176
1603
+ width: 320
1604
+ interpolation: linear
1605
+ - _target_: groot.vla.data.transform.VideoColorJitter
1606
+ apply_to:
1607
+ - video.top_head
1608
+ - video.hand_left
1609
+ - video.hand_right
1610
+ brightness: 0.3
1611
+ contrast: 0.4
1612
+ saturation: 0.5
1613
+ hue: 0.08
1614
+ - _target_: groot.vla.data.transform.VideoToNumpy
1615
+ apply_to:
1616
+ - video.top_head
1617
+ - video.hand_left
1618
+ - video.hand_right
1619
+ - _target_: groot.vla.data.transform.StateActionToTensor
1620
+ apply_to:
1621
+ - state.left_joint_pos
1622
+ - state.left_gripper_pos
1623
+ - state.right_joint_pos
1624
+ - state.right_gripper_pos
1625
+ - _target_: groot.vla.data.transform.StateActionTransform
1626
+ apply_to:
1627
+ - state.left_joint_pos
1628
+ - state.left_gripper_pos
1629
+ - state.right_joint_pos
1630
+ - state.right_gripper_pos
1631
+ normalization_modes:
1632
+ state.left_joint_pos: q99
1633
+ state.left_gripper_pos: q99
1634
+ state.right_joint_pos: q99
1635
+ state.right_gripper_pos: q99
1636
+ - _target_: groot.vla.data.transform.StateActionToTensor
1637
+ apply_to:
1638
+ - action.left_joint_pos
1639
+ - action.left_gripper_pos
1640
+ - action.right_joint_pos
1641
+ - action.right_gripper_pos
1642
+ - _target_: groot.vla.data.transform.StateActionTransform
1643
+ apply_to:
1644
+ - action.left_joint_pos
1645
+ - action.left_gripper_pos
1646
+ - action.right_joint_pos
1647
+ - action.right_gripper_pos
1648
+ normalization_modes:
1649
+ action.left_joint_pos: q99
1650
+ action.left_gripper_pos: q99
1651
+ action.right_joint_pos: q99
1652
+ action.right_gripper_pos: q99
1653
+ - _target_: groot.vla.data.transform.ConcatTransform
1654
+ video_concat_order:
1655
+ - video.top_head
1656
+ - video.hand_left
1657
+ - video.hand_right
1658
+ state_concat_order:
1659
+ - state.left_joint_pos
1660
+ - state.left_gripper_pos
1661
+ - state.right_joint_pos
1662
+ - state.right_gripper_pos
1663
+ action_concat_order:
1664
+ - action.left_joint_pos
1665
+ - action.left_gripper_pos
1666
+ - action.right_joint_pos
1667
+ - action.right_gripper_pos
1668
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1669
+ default_instruction: Perform the default behavior.
1670
+ language_dropout_prob: 0.0
1671
+ always_use_default_instruction: false
1672
+ max_state_dim: 64
1673
+ max_action_dim: 32
1674
+ max_length: 512
1675
+ state_horizon: 1
1676
+ action_horizon: 24
1677
+ embodiment_tag_mapping:
1678
+ real_gr1_arms_only: 0
1679
+ real_gr1_arms_only_annotated: 1
1680
+ real_gr1_arms_waist: 2
1681
+ real_gr1_arms_waist_annotated: 3
1682
+ dexmg_gr1_arms_only_inspire: 4
1683
+ dexmg_gr1_arms_only_fourier: 5
1684
+ dexmg_gr1_arms_waist_fourier: 6
1685
+ robocasa_single_arm: 7
1686
+ onex_eve_gripper: 8
1687
+ robocasa_gr1_arms_only_inspire_hands: 9
1688
+ robocasa_gr1_arms_only_fourier_hands: 10
1689
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1690
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1691
+ robocasa_panda_omron: 13
1692
+ robocasa_bimanual_panda_parallel_gripper: 15
1693
+ robocasa_bimanual_panda_inspire_hand: 16
1694
+ oxe_droid: 17
1695
+ oxe_fractal: 18
1696
+ oxe_language_table: 19
1697
+ oxe_bridge: 20
1698
+ real_panda_single_arm: 21
1699
+ hot3d_hands_only: 23
1700
+ gr1_unified: 24
1701
+ robocasa_gr1_arms_waist_fourier_hands: 25
1702
+ agibot: 26
1703
+ bimanual_ur3: 26
1704
+ lapa: 27
1705
+ oxe_mutex: 28
1706
+ oxe_roboset: 29
1707
+ oxe_plex: 30
1708
+ dream: 31
1709
+ yam: 32
1710
+ xdof: 22
1711
+ gr1_unified_segmentation: 14
1712
+ language_table_sim: 7
1713
+ gr1_isaac: 0
1714
+ sim_behavior_r1_pro: 31
1715
+ mecka_hands: 27
1716
+ real_r1_pro_sharpa: 28
1717
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1718
+ modality_config_oxe_droid:
1719
+ video:
1720
+ _target_: groot.vla.data.dataset.ModalityConfig
1721
+ delta_indices:
1722
+ - 0
1723
+ - 1
1724
+ - 2
1725
+ - 3
1726
+ - 4
1727
+ - 5
1728
+ - 6
1729
+ - 7
1730
+ - 8
1731
+ - 9
1732
+ - 10
1733
+ - 11
1734
+ - 12
1735
+ - 13
1736
+ - 14
1737
+ - 15
1738
+ - 16
1739
+ - 17
1740
+ - 18
1741
+ - 19
1742
+ - 20
1743
+ - 21
1744
+ - 22
1745
+ - 23
1746
+ - 24
1747
+ - 25
1748
+ - 26
1749
+ - 27
1750
+ - 28
1751
+ - 29
1752
+ - 30
1753
+ - 31
1754
+ - 32
1755
+ eval_delta_indices:
1756
+ - 0
1757
+ modality_keys:
1758
+ - video.exterior_image_1_left
1759
+ - video.exterior_image_2_left
1760
+ - video.wrist_image_left
1761
+ state:
1762
+ _target_: groot.vla.data.dataset.ModalityConfig
1763
+ delta_indices:
1764
+ - 0
1765
+ modality_keys:
1766
+ - state.joint_position
1767
+ - state.gripper_position
1768
+ action:
1769
+ _target_: groot.vla.data.dataset.ModalityConfig
1770
+ delta_indices:
1771
+ - 0
1772
+ - 1
1773
+ - 2
1774
+ - 3
1775
+ - 4
1776
+ - 5
1777
+ - 6
1778
+ - 7
1779
+ - 8
1780
+ - 9
1781
+ - 10
1782
+ - 11
1783
+ - 12
1784
+ - 13
1785
+ - 14
1786
+ - 15
1787
+ - 16
1788
+ - 17
1789
+ - 18
1790
+ - 19
1791
+ - 20
1792
+ - 21
1793
+ - 22
1794
+ - 23
1795
+ modality_keys:
1796
+ - action.joint_position
1797
+ - action.gripper_position
1798
+ language:
1799
+ _target_: groot.vla.data.dataset.ModalityConfig
1800
+ delta_indices:
1801
+ - 0
1802
+ modality_keys:
1803
+ - annotation.language.language_instruction
1804
+ - annotation.language.language_instruction_2
1805
+ - annotation.language.language_instruction_3
1806
+ lapa_action:
1807
+ _target_: groot.vla.data.dataset.ModalityConfig
1808
+ delta_indices:
1809
+ - 0
1810
+ modality_keys:
1811
+ - lapa_action
1812
+ transform_oxe_droid:
1813
+ _target_: groot.vla.data.transform.ComposedModalityTransform
1814
+ transforms:
1815
+ - _target_: groot.vla.data.transform.VideoToTensor
1816
+ apply_to:
1817
+ - video.exterior_image_1_left
1818
+ - video.exterior_image_2_left
1819
+ - video.wrist_image_left
1820
+ - _target_: groot.vla.data.transform.VideoCrop
1821
+ apply_to:
1822
+ - video.exterior_image_1_left
1823
+ - video.exterior_image_2_left
1824
+ - video.wrist_image_left
1825
+ scale: 0.95
1826
+ mode: random
1827
+ - _target_: groot.vla.data.transform.VideoResize
1828
+ apply_to:
1829
+ - video.exterior_image_1_left
1830
+ - video.exterior_image_2_left
1831
+ - video.wrist_image_left
1832
+ height: 176
1833
+ width: 320
1834
+ interpolation: linear
1835
+ - _target_: groot.vla.data.transform.VideoColorJitter
1836
+ apply_to:
1837
+ - video.exterior_image_1_left
1838
+ - video.exterior_image_2_left
1839
+ - video.wrist_image_left
1840
+ brightness: 0.3
1841
+ contrast: 0.4
1842
+ saturation: 0.5
1843
+ hue: 0.08
1844
+ - _target_: groot.vla.data.transform.VideoToNumpy
1845
+ apply_to:
1846
+ - video.exterior_image_1_left
1847
+ - video.exterior_image_2_left
1848
+ - video.wrist_image_left
1849
+ - _target_: groot.vla.data.transform.StateActionToTensor
1850
+ apply_to:
1851
+ - state.joint_position
1852
+ - state.gripper_position
1853
+ - _target_: groot.vla.data.transform.StateActionTransform
1854
+ apply_to:
1855
+ - state.joint_position
1856
+ - state.gripper_position
1857
+ normalization_modes:
1858
+ state.joint_position: q99
1859
+ state.gripper_position: q99
1860
+ - _target_: groot.vla.data.transform.StateActionToTensor
1861
+ apply_to:
1862
+ - action.joint_position
1863
+ - action.gripper_position
1864
+ - _target_: groot.vla.data.transform.StateActionTransform
1865
+ apply_to:
1866
+ - action.joint_position
1867
+ - action.gripper_position
1868
+ normalization_modes:
1869
+ action.joint_position: q99
1870
+ action.gripper_position: q99
1871
+ - _target_: groot.vla.data.transform.ConcatTransform
1872
+ video_concat_order:
1873
+ - video.exterior_image_1_left
1874
+ - video.exterior_image_2_left
1875
+ - video.wrist_image_left
1876
+ state_concat_order:
1877
+ - state.joint_position
1878
+ - state.gripper_position
1879
+ action_concat_order:
1880
+ - action.joint_position
1881
+ - action.gripper_position
1882
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1883
+ default_instruction: Perform the default behavior.
1884
+ language_dropout_prob: 0.0
1885
+ always_use_default_instruction: false
1886
+ max_state_dim: 64
1887
+ max_action_dim: 32
1888
+ max_length: 512
1889
+ state_horizon: 1
1890
+ action_horizon: 24
1891
+ embodiment_tag_mapping:
1892
+ real_gr1_arms_only: 0
1893
+ real_gr1_arms_only_annotated: 1
1894
+ real_gr1_arms_waist: 2
1895
+ real_gr1_arms_waist_annotated: 3
1896
+ dexmg_gr1_arms_only_inspire: 4
1897
+ dexmg_gr1_arms_only_fourier: 5
1898
+ dexmg_gr1_arms_waist_fourier: 6
1899
+ robocasa_single_arm: 7
1900
+ onex_eve_gripper: 8
1901
+ robocasa_gr1_arms_only_inspire_hands: 9
1902
+ robocasa_gr1_arms_only_fourier_hands: 10
1903
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1904
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1905
+ robocasa_panda_omron: 13
1906
+ robocasa_bimanual_panda_parallel_gripper: 15
1907
+ robocasa_bimanual_panda_inspire_hand: 16
1908
+ oxe_droid: 17
1909
+ oxe_fractal: 18
1910
+ oxe_language_table: 19
1911
+ oxe_bridge: 20
1912
+ real_panda_single_arm: 21
1913
+ hot3d_hands_only: 23
1914
+ gr1_unified: 24
1915
+ robocasa_gr1_arms_waist_fourier_hands: 25
1916
+ agibot: 26
1917
+ bimanual_ur3: 26
1918
+ lapa: 27
1919
+ oxe_mutex: 28
1920
+ oxe_roboset: 29
1921
+ oxe_plex: 30
1922
+ dream: 31
1923
+ yam: 32
1924
+ xdof: 22
1925
+ gr1_unified_segmentation: 14
1926
+ language_table_sim: 7
1927
+ gr1_isaac: 0
1928
+ sim_behavior_r1_pro: 31
1929
+ mecka_hands: 27
1930
+ real_r1_pro_sharpa: 28
1931
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1932
+ modality_config_agibot:
1933
+ video:
1934
+ _target_: groot.vla.data.dataset.ModalityConfig
1935
+ delta_indices:
1936
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1937
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1938
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1939
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1940
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1941
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1942
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1943
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1968
+ - 32
1969
+ eval_delta_indices:
1970
+ - -3
1971
+ - -2
1972
+ - -1
1973
+ - 0
1974
+ modality_keys:
1975
+ - video.top_head
1976
+ - video.hand_left
1977
+ - video.hand_right
1978
+ state:
1979
+ _target_: groot.vla.data.dataset.ModalityConfig
1980
+ delta_indices:
1981
+ - 0
1982
+ modality_keys:
1983
+ - state.left_arm_joint_position
1984
+ - state.right_arm_joint_position
1985
+ - state.left_effector_position
1986
+ - state.right_effector_position
1987
+ - state.head_position
1988
+ - state.waist_position
1989
+ action:
1990
+ _target_: groot.vla.data.dataset.ModalityConfig
1991
+ delta_indices:
1992
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1993
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1994
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1995
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2009
+ - 17
2010
+ - 18
2011
+ - 19
2012
+ - 20
2013
+ - 21
2014
+ - 22
2015
+ - 23
2016
+ modality_keys:
2017
+ - action.left_arm_joint_position
2018
+ - action.right_arm_joint_position
2019
+ - action.left_effector_position
2020
+ - action.right_effector_position
2021
+ - action.head_position
2022
+ - action.waist_position
2023
+ - action.robot_velocity
2024
+ language:
2025
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2026
+ delta_indices:
2027
+ - 0
2028
+ modality_keys:
2029
+ - annotation.language.action_text
2030
+ transform_agibot:
2031
+ _target_: groot.vla.data.transform.ComposedModalityTransform
2032
+ transforms:
2033
+ - _target_: groot.vla.data.transform.VideoToTensor
2034
+ apply_to:
2035
+ - video.top_head
2036
+ - video.hand_left
2037
+ - video.hand_right
2038
+ - _target_: groot.vla.data.transform.VideoCrop
2039
+ apply_to:
2040
+ - video.top_head
2041
+ - video.hand_left
2042
+ - video.hand_right
2043
+ scale: 0.95
2044
+ mode: random
2045
+ - _target_: groot.vla.data.transform.VideoResize
2046
+ apply_to:
2047
+ - video.top_head
2048
+ - video.hand_left
2049
+ - video.hand_right
2050
+ height: 176
2051
+ width: 320
2052
+ interpolation: linear
2053
+ - _target_: groot.vla.data.transform.VideoColorJitter
2054
+ apply_to:
2055
+ - video.top_head
2056
+ - video.hand_left
2057
+ - video.hand_right
2058
+ brightness: 0.3
2059
+ contrast: 0.4
2060
+ saturation: 0.5
2061
+ hue: 0.08
2062
+ - _target_: groot.vla.data.transform.VideoToNumpy
2063
+ apply_to:
2064
+ - video.top_head
2065
+ - video.hand_left
2066
+ - video.hand_right
2067
+ - _target_: groot.vla.data.transform.StateActionToTensor
2068
+ apply_to:
2069
+ - state.left_arm_joint_position
2070
+ - state.right_arm_joint_position
2071
+ - state.left_effector_position
2072
+ - state.right_effector_position
2073
+ - state.head_position
2074
+ - state.waist_position
2075
+ - _target_: groot.vla.data.transform.StateActionTransform
2076
+ apply_to:
2077
+ - state.left_arm_joint_position
2078
+ - state.right_arm_joint_position
2079
+ - state.left_effector_position
2080
+ - state.right_effector_position
2081
+ - state.head_position
2082
+ - state.waist_position
2083
+ normalization_modes:
2084
+ state.left_arm_joint_position: q99
2085
+ state.right_arm_joint_position: q99
2086
+ state.left_effector_position: q99
2087
+ state.right_effector_position: q99
2088
+ state.head_position: q99
2089
+ state.waist_position: q99
2090
+ - _target_: groot.vla.data.transform.StateActionToTensor
2091
+ apply_to:
2092
+ - action.left_arm_joint_position
2093
+ - action.right_arm_joint_position
2094
+ - action.left_effector_position
2095
+ - action.right_effector_position
2096
+ - action.head_position
2097
+ - action.waist_position
2098
+ - action.robot_velocity
2099
+ - _target_: groot.vla.data.transform.StateActionTransform
2100
+ apply_to:
2101
+ - action.left_arm_joint_position
2102
+ - action.right_arm_joint_position
2103
+ - action.left_effector_position
2104
+ - action.right_effector_position
2105
+ - action.head_position
2106
+ - action.waist_position
2107
+ - action.robot_velocity
2108
+ normalization_modes:
2109
+ action.left_arm_joint_position: q99
2110
+ action.right_arm_joint_position: q99
2111
+ action.left_effector_position: q99
2112
+ action.right_effector_position: q99
2113
+ action.head_position: q99
2114
+ action.waist_position: q99
2115
+ action.robot_velocity: q99
2116
+ - _target_: groot.vla.data.transform.ConcatTransform
2117
+ video_concat_order:
2118
+ - video.top_head
2119
+ - video.hand_left
2120
+ - video.hand_right
2121
+ state_concat_order:
2122
+ - state.left_arm_joint_position
2123
+ - state.right_arm_joint_position
2124
+ - state.left_effector_position
2125
+ - state.right_effector_position
2126
+ - state.head_position
2127
+ - state.waist_position
2128
+ action_concat_order:
2129
+ - action.left_arm_joint_position
2130
+ - action.right_arm_joint_position
2131
+ - action.left_effector_position
2132
+ - action.right_effector_position
2133
+ - action.head_position
2134
+ - action.waist_position
2135
+ - action.robot_velocity
2136
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
2137
+ default_instruction: Perform the default behavior.
2138
+ language_dropout_prob: 0.0
2139
+ always_use_default_instruction: false
2140
+ max_state_dim: 64
2141
+ max_action_dim: 32
2142
+ max_length: 512
2143
+ state_horizon: 1
2144
+ action_horizon: 24
2145
+ embodiment_tag_mapping:
2146
+ real_gr1_arms_only: 0
2147
+ real_gr1_arms_only_annotated: 1
2148
+ real_gr1_arms_waist: 2
2149
+ real_gr1_arms_waist_annotated: 3
2150
+ dexmg_gr1_arms_only_inspire: 4
2151
+ dexmg_gr1_arms_only_fourier: 5
2152
+ dexmg_gr1_arms_waist_fourier: 6
2153
+ robocasa_single_arm: 7
2154
+ onex_eve_gripper: 8
2155
+ robocasa_gr1_arms_only_inspire_hands: 9
2156
+ robocasa_gr1_arms_only_fourier_hands: 10
2157
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
2158
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
2159
+ robocasa_panda_omron: 13
2160
+ robocasa_bimanual_panda_parallel_gripper: 15
2161
+ robocasa_bimanual_panda_inspire_hand: 16
2162
+ oxe_droid: 17
2163
+ oxe_fractal: 18
2164
+ oxe_language_table: 19
2165
+ oxe_bridge: 20
2166
+ real_panda_single_arm: 21
2167
+ hot3d_hands_only: 23
2168
+ gr1_unified: 24
2169
+ robocasa_gr1_arms_waist_fourier_hands: 25
2170
+ agibot: 26
2171
+ bimanual_ur3: 26
2172
+ lapa: 27
2173
+ oxe_mutex: 28
2174
+ oxe_roboset: 29
2175
+ oxe_plex: 30
2176
+ dream: 31
2177
+ yam: 32
2178
+ xdof: 22
2179
+ gr1_unified_segmentation: 14
2180
+ language_table_sim: 7
2181
+ gr1_isaac: 0
2182
+ sim_behavior_r1_pro: 31
2183
+ mecka_hands: 27
2184
+ real_r1_pro_sharpa: 28
2185
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
2186
+ modality_config_yam:
2187
+ video:
2188
+ _target_: groot.vla.data.dataset.ModalityConfig
2189
+ delta_indices:
2190
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2191
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2192
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2193
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2194
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2195
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2196
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2197
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2198
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2200
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2201
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2202
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2203
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2204
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2205
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2206
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2208
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2210
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2214
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2217
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2218
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2219
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2220
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2221
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2222
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2223
+ eval_delta_indices:
2224
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2225
+ modality_keys:
2226
+ - video.top_camera-images-rgb
2227
+ - video.left_camera-images-rgb
2228
+ - video.right_camera-images-rgb
2229
+ state:
2230
+ _target_: groot.vla.data.dataset.ModalityConfig
2231
+ delta_indices:
2232
+ - 0
2233
+ modality_keys:
2234
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2235
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2236
+ - state.right_joint_pos
2237
+ - state.right_gripper_pos
2238
+ action:
2239
+ _target_: groot.vla.data.dataset.ModalityConfig
2240
+ delta_indices:
2241
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2242
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2243
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2258
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2259
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2260
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2261
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2262
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2263
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2264
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2265
+ modality_keys:
2266
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2267
+ - action.left_gripper_pos
2268
+ - action.right_joint_pos
2269
+ - action.right_gripper_pos
2270
+ language:
2271
+ _target_: groot.vla.data.dataset.ModalityConfig
2272
+ delta_indices:
2273
+ - 0
2274
+ modality_keys:
2275
+ - annotation.task
2276
+ transform_yam:
2277
+ _target_: groot.vla.data.transform.ComposedModalityTransform
2278
+ transforms:
2279
+ - _target_: groot.vla.data.transform.VideoToTensor
2280
+ apply_to:
2281
+ - video.top_camera-images-rgb
2282
+ - video.left_camera-images-rgb
2283
+ - video.right_camera-images-rgb
2284
+ - _target_: groot.vla.data.transform.VideoCrop
2285
+ apply_to:
2286
+ - video.top_camera-images-rgb
2287
+ - video.left_camera-images-rgb
2288
+ - video.right_camera-images-rgb
2289
+ scale: 0.95
2290
+ mode: random
2291
+ - _target_: groot.vla.data.transform.VideoResize
2292
+ apply_to:
2293
+ - video.top_camera-images-rgb
2294
+ - video.left_camera-images-rgb
2295
+ - video.right_camera-images-rgb
2296
+ height: 176
2297
+ width: 320
2298
+ interpolation: linear
2299
+ - _target_: groot.vla.data.transform.VideoColorJitter
2300
+ apply_to:
2301
+ - video.top_camera-images-rgb
2302
+ - video.left_camera-images-rgb
2303
+ - video.right_camera-images-rgb
2304
+ brightness: 0.3
2305
+ contrast: 0.4
2306
+ saturation: 0.5
2307
+ hue: 0.08
2308
+ - _target_: groot.vla.data.transform.VideoToNumpy
2309
+ apply_to:
2310
+ - video.top_camera-images-rgb
2311
+ - video.left_camera-images-rgb
2312
+ - video.right_camera-images-rgb
2313
+ - _target_: groot.vla.data.transform.StateActionToTensor
2314
+ apply_to:
2315
+ - state.left_joint_pos
2316
+ - state.left_gripper_pos
2317
+ - state.right_joint_pos
2318
+ - state.right_gripper_pos
2319
+ - _target_: groot.vla.data.transform.StateActionTransform
2320
+ apply_to:
2321
+ - state.left_joint_pos
2322
+ - state.left_gripper_pos
2323
+ - state.right_joint_pos
2324
+ - state.right_gripper_pos
2325
+ normalization_modes:
2326
+ state.left_joint_pos: q99
2327
+ state.left_gripper_pos: q99
2328
+ state.right_joint_pos: q99
2329
+ state.right_gripper_pos: q99
2330
+ - _target_: groot.vla.data.transform.StateActionToTensor
2331
+ apply_to:
2332
+ - action.left_joint_pos
2333
+ - action.left_gripper_pos
2334
+ - action.right_joint_pos
2335
+ - action.right_gripper_pos
2336
+ - _target_: groot.vla.data.transform.StateActionTransform
2337
+ apply_to:
2338
+ - action.left_joint_pos
2339
+ - action.left_gripper_pos
2340
+ - action.right_joint_pos
2341
+ - action.right_gripper_pos
2342
+ normalization_modes:
2343
+ action.left_joint_pos: q99
2344
+ action.left_gripper_pos: q99
2345
+ action.right_joint_pos: q99
2346
+ action.right_gripper_pos: q99
2347
+ - _target_: groot.vla.data.transform.ConcatTransform
2348
+ video_concat_order:
2349
+ - video.top_camera-images-rgb
2350
+ - video.left_camera-images-rgb
2351
+ - video.right_camera-images-rgb
2352
+ state_concat_order:
2353
+ - state.left_joint_pos
2354
+ - state.left_gripper_pos
2355
+ - state.right_joint_pos
2356
+ - state.right_gripper_pos
2357
+ action_concat_order:
2358
+ - action.left_joint_pos
2359
+ - action.left_gripper_pos
2360
+ - action.right_joint_pos
2361
+ - action.right_gripper_pos
2362
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
2363
+ default_instruction: Perform the default behavior.
2364
+ language_dropout_prob: 0.0
2365
+ always_use_default_instruction: false
2366
+ max_state_dim: 64
2367
+ max_action_dim: 32
2368
+ max_length: 512
2369
+ state_horizon: 1
2370
+ action_horizon: 24
2371
+ embodiment_tag_mapping:
2372
+ real_gr1_arms_only: 0
2373
+ real_gr1_arms_only_annotated: 1
2374
+ real_gr1_arms_waist: 2
2375
+ real_gr1_arms_waist_annotated: 3
2376
+ dexmg_gr1_arms_only_inspire: 4
2377
+ dexmg_gr1_arms_only_fourier: 5
2378
+ dexmg_gr1_arms_waist_fourier: 6
2379
+ robocasa_single_arm: 7
2380
+ onex_eve_gripper: 8
2381
+ robocasa_gr1_arms_only_inspire_hands: 9
2382
+ robocasa_gr1_arms_only_fourier_hands: 10
2383
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
2384
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
2385
+ robocasa_panda_omron: 13
2386
+ robocasa_bimanual_panda_parallel_gripper: 15
2387
+ robocasa_bimanual_panda_inspire_hand: 16
2388
+ oxe_droid: 17
2389
+ oxe_fractal: 18
2390
+ oxe_language_table: 19
2391
+ oxe_bridge: 20
2392
+ real_panda_single_arm: 21
2393
+ hot3d_hands_only: 23
2394
+ gr1_unified: 24
2395
+ robocasa_gr1_arms_waist_fourier_hands: 25
2396
+ agibot: 26
2397
+ bimanual_ur3: 26
2398
+ lapa: 27
2399
+ oxe_mutex: 28
2400
+ oxe_roboset: 29
2401
+ oxe_plex: 30
2402
+ dream: 31
2403
+ yam: 32
2404
+ xdof: 22
2405
+ gr1_unified_segmentation: 14
2406
+ language_table_sim: 7
2407
+ gr1_isaac: 0
2408
+ sim_behavior_r1_pro: 31
2409
+ mecka_hands: 27
2410
+ real_r1_pro_sharpa: 28
2411
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
2412
+ modality_configs:
2413
+ bimanual_ur3:
2414
+ video:
2415
+ _target_: groot.vla.data.dataset.ModalityConfig
2416
+ delta_indices:
2417
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2418
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2419
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2420
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2421
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2422
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2444
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2445
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2446
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2447
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2448
+ - 31
2449
+ - 32
2450
+ eval_delta_indices:
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2452
+ modality_keys:
2453
+ - video.top_head
2454
+ - video.hand_left
2455
+ - video.hand_right
2456
+ state:
2457
+ _target_: groot.vla.data.dataset.ModalityConfig
2458
+ delta_indices:
2459
+ - 0
2460
+ modality_keys:
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+ - state.right_joint_pos
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+ - state.right_gripper_pos
2465
+ action:
2466
+ _target_: groot.vla.data.dataset.ModalityConfig
2467
+ delta_indices:
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2491
+ - 23
2492
+ modality_keys:
2493
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2494
+ - action.left_gripper_pos
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+ - action.right_joint_pos
2496
+ - action.right_gripper_pos
2497
+ language:
2498
+ _target_: groot.vla.data.dataset.ModalityConfig
2499
+ delta_indices:
2500
+ - 0
2501
+ modality_keys:
2502
+ - annotation.task
2503
+ oxe_droid:
2504
+ video:
2505
+ _target_: groot.vla.data.dataset.ModalityConfig
2506
+ delta_indices:
2507
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2508
+ - 1
2509
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2510
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2993
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3004
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3005
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3007
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3009
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3015
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3018
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3019
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3020
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3023
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3024
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3025
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3026
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3027
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3028
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3029
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3031
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3033
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3034
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3037
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3038
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3042
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3043
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3044
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3045
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3046
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3047
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3048
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3050
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3051
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3069
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3091
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+ mixture_dataset_cls: groot.vla.data.dataset.lerobot_sharded.ShardedLeRobotMixtureDataset.from_mixture_spec
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+ single_dataset_cls: groot.vla.data.dataset.lerobot_sharded.ShardedLeRobotSubLangSingleActionChunkDatasetDROID
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+ bimanual_ur3_data_root: /root/WAM/datasets/bimanual-ur3-dreamzero-v2
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+ total_training_steps: 1048576000000
checkpoint-20000/experiment_cfg/metadata.json ADDED
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+ }
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+ "embodiment_tag": "bimanual_ur3"
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+ }
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+ }
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1
+ #!/usr/bin/env python
2
+
3
+ # Copyright (c) Microsoft Corporation.
4
+ # SPDX-License-Identifier: Apache-2.0
5
+
6
+ # DeepSpeed Team
7
+
8
+ # This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets
9
+ # copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
10
+ # the future. Once extracted, the weights don't require DeepSpeed and can be used in any
11
+ # application.
12
+ #
13
+ # example:
14
+ # python zero_to_fp32.py . output_dir/
15
+ # or
16
+ # python zero_to_fp32.py . output_dir/ --safe_serialization
17
+
18
+ import argparse
19
+ import torch
20
+ import glob
21
+ import math
22
+ import os
23
+ import re
24
+ import gc
25
+ import json
26
+ import numpy as np
27
+ from tqdm import tqdm
28
+ from collections import OrderedDict
29
+ from dataclasses import dataclass
30
+
31
+ # while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
32
+ # DeepSpeed data structures it has to be available in the current python environment.
33
+ from deepspeed.utils import logger
34
+ from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
35
+ FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
36
+ FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
37
+
38
+
39
+ @dataclass
40
+ class zero_model_state:
41
+ buffers: dict()
42
+ param_shapes: dict()
43
+ shared_params: list
44
+ ds_version: int
45
+ frozen_param_shapes: dict()
46
+ frozen_param_fragments: dict()
47
+
48
+
49
+ debug = 0
50
+
51
+ # load to cpu
52
+ device = torch.device('cpu')
53
+
54
+
55
+ def atoi(text):
56
+ return int(text) if text.isdigit() else text
57
+
58
+
59
+ def natural_keys(text):
60
+ '''
61
+ alist.sort(key=natural_keys) sorts in human order
62
+ http://nedbatchelder.com/blog/200712/human_sorting.html
63
+ (See Toothy's implementation in the comments)
64
+ '''
65
+ return [atoi(c) for c in re.split(r'(\d+)', text)]
66
+
67
+
68
+ def get_model_state_file(checkpoint_dir, zero_stage):
69
+ if not os.path.isdir(checkpoint_dir):
70
+ raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
71
+
72
+ # there should be only one file
73
+ if zero_stage <= 2:
74
+ file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
75
+ elif zero_stage == 3:
76
+ file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
77
+
78
+ if not os.path.exists(file):
79
+ raise FileNotFoundError(f"can't find model states file at '{file}'")
80
+
81
+ return file
82
+
83
+
84
+ def get_checkpoint_files(checkpoint_dir, glob_pattern):
85
+ # XXX: need to test that this simple glob rule works for multi-node setup too
86
+ ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
87
+
88
+ if len(ckpt_files) == 0:
89
+ raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
90
+
91
+ return ckpt_files
92
+
93
+
94
+ def get_optim_files(checkpoint_dir):
95
+ return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
96
+
97
+
98
+ def get_model_state_files(checkpoint_dir):
99
+ return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
100
+
101
+
102
+ def parse_model_states(files):
103
+ zero_model_states = []
104
+ for file in files:
105
+ state_dict = torch.load(file, map_location=device, weights_only=False)
106
+
107
+ if BUFFER_NAMES not in state_dict:
108
+ raise ValueError(f"{file} is not a model state checkpoint")
109
+ buffer_names = state_dict[BUFFER_NAMES]
110
+ if debug:
111
+ print("Found buffers:", buffer_names)
112
+
113
+ # recover just the buffers while restoring them to fp32 if they were saved in fp16
114
+ buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
115
+ param_shapes = state_dict[PARAM_SHAPES]
116
+
117
+ # collect parameters that are included in param_shapes
118
+ param_names = []
119
+ for s in param_shapes:
120
+ for name in s.keys():
121
+ param_names.append(name)
122
+
123
+ # update with frozen parameters
124
+ frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
125
+ if frozen_param_shapes is not None:
126
+ if debug:
127
+ print(f"Found frozen_param_shapes: {frozen_param_shapes}")
128
+ param_names += list(frozen_param_shapes.keys())
129
+
130
+ # handle shared params
131
+ shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
132
+
133
+ ds_version = state_dict.get(DS_VERSION, None)
134
+
135
+ frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
136
+
137
+ z_model_state = zero_model_state(buffers=buffers,
138
+ param_shapes=param_shapes,
139
+ shared_params=shared_params,
140
+ ds_version=ds_version,
141
+ frozen_param_shapes=frozen_param_shapes,
142
+ frozen_param_fragments=frozen_param_fragments)
143
+ zero_model_states.append(z_model_state)
144
+
145
+ return zero_model_states
146
+
147
+
148
+ def parse_optim_states(files, ds_checkpoint_dir):
149
+ total_files = len(files)
150
+ state_dicts = []
151
+ for f in tqdm(files, desc='Loading checkpoint shards'):
152
+ state_dict = torch.load(f, map_location=device, mmap=True, weights_only=False)
153
+ # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights
154
+ # and also handle the case where it was already removed by another helper script
155
+ state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None)
156
+ state_dicts.append(state_dict)
157
+
158
+ if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
159
+ raise ValueError(f"{files[0]} is not a zero checkpoint")
160
+ zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
161
+ world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
162
+
163
+ # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
164
+ # parameters can be different from data parallelism for non-expert parameters. So we can just
165
+ # use the max of the partition_count to get the dp world_size.
166
+
167
+ if type(world_size) is list:
168
+ world_size = max(world_size)
169
+
170
+ if world_size != total_files:
171
+ raise ValueError(
172
+ f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
173
+ "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
174
+ )
175
+
176
+ # the groups are named differently in each stage
177
+ if zero_stage <= 2:
178
+ fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
179
+ elif zero_stage == 3:
180
+ fp32_groups_key = FP32_FLAT_GROUPS
181
+ else:
182
+ raise ValueError(f"unknown zero stage {zero_stage}")
183
+
184
+ fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
185
+ return zero_stage, world_size, fp32_flat_groups
186
+
187
+
188
+ def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters):
189
+ """
190
+ Returns fp32 state_dict reconstructed from ds checkpoint
191
+
192
+ Args:
193
+ - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
194
+
195
+ """
196
+ print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
197
+
198
+ optim_files = get_optim_files(ds_checkpoint_dir)
199
+ zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
200
+ print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
201
+
202
+ model_files = get_model_state_files(ds_checkpoint_dir)
203
+
204
+ zero_model_states = parse_model_states(model_files)
205
+ print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
206
+
207
+ if zero_stage <= 2:
208
+ return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
209
+ exclude_frozen_parameters)
210
+ elif zero_stage == 3:
211
+ return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
212
+ exclude_frozen_parameters)
213
+
214
+
215
+ def _zero2_merge_frozen_params(state_dict, zero_model_states):
216
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
217
+ return
218
+
219
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
220
+ frozen_param_fragments = zero_model_states[0].frozen_param_fragments
221
+
222
+ if debug:
223
+ num_elem = sum(s.numel() for s in frozen_param_shapes.values())
224
+ print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
225
+
226
+ wanted_params = len(frozen_param_shapes)
227
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
228
+ avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
229
+ print(f'Frozen params: Have {avail_numel} numels to process.')
230
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
231
+
232
+ total_params = 0
233
+ total_numel = 0
234
+ for name, shape in frozen_param_shapes.items():
235
+ total_params += 1
236
+ unpartitioned_numel = shape.numel()
237
+ total_numel += unpartitioned_numel
238
+
239
+ state_dict[name] = frozen_param_fragments[name]
240
+
241
+ if debug:
242
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
243
+
244
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
245
+
246
+
247
+ def _has_callable(obj, fn):
248
+ attr = getattr(obj, fn, None)
249
+ return callable(attr)
250
+
251
+
252
+ def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
253
+ param_shapes = zero_model_states[0].param_shapes
254
+
255
+ # Reconstruction protocol:
256
+ #
257
+ # XXX: document this
258
+
259
+ if debug:
260
+ for i in range(world_size):
261
+ for j in range(len(fp32_flat_groups[0])):
262
+ print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
263
+
264
+ # XXX: memory usage doubles here (zero2)
265
+ num_param_groups = len(fp32_flat_groups[0])
266
+ merged_single_partition_of_fp32_groups = []
267
+ for i in range(num_param_groups):
268
+ merged_partitions = [sd[i] for sd in fp32_flat_groups]
269
+ full_single_fp32_vector = torch.cat(merged_partitions, 0)
270
+ merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
271
+ avail_numel = sum(
272
+ [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
273
+
274
+ if debug:
275
+ wanted_params = sum([len(shapes) for shapes in param_shapes])
276
+ wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
277
+ # not asserting if there is a mismatch due to possible padding
278
+ print(f"Have {avail_numel} numels to process.")
279
+ print(f"Need {wanted_numel} numels in {wanted_params} params.")
280
+
281
+ # params
282
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
283
+ # out-of-core computing solution
284
+ total_numel = 0
285
+ total_params = 0
286
+ for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
287
+ offset = 0
288
+ avail_numel = full_single_fp32_vector.numel()
289
+ for name, shape in shapes.items():
290
+
291
+ unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape)
292
+ total_numel += unpartitioned_numel
293
+ total_params += 1
294
+
295
+ if debug:
296
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
297
+ state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
298
+ offset += unpartitioned_numel
299
+
300
+ # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
301
+ # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
302
+ # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
303
+ # live optimizer object, so we are checking that the numbers are within the right range
304
+ align_to = 2 * world_size
305
+
306
+ def zero2_align(x):
307
+ return align_to * math.ceil(x / align_to)
308
+
309
+ if debug:
310
+ print(f"original offset={offset}, avail_numel={avail_numel}")
311
+
312
+ offset = zero2_align(offset)
313
+ avail_numel = zero2_align(avail_numel)
314
+
315
+ if debug:
316
+ print(f"aligned offset={offset}, avail_numel={avail_numel}")
317
+
318
+ # Sanity check
319
+ if offset != avail_numel:
320
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
321
+
322
+ print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
323
+
324
+
325
+ def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
326
+ exclude_frozen_parameters):
327
+ state_dict = OrderedDict()
328
+
329
+ # buffers
330
+ buffers = zero_model_states[0].buffers
331
+ state_dict.update(buffers)
332
+ if debug:
333
+ print(f"added {len(buffers)} buffers")
334
+
335
+ if not exclude_frozen_parameters:
336
+ _zero2_merge_frozen_params(state_dict, zero_model_states)
337
+
338
+ _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
339
+
340
+ # recover shared parameters
341
+ for pair in zero_model_states[0].shared_params:
342
+ if pair[1] in state_dict:
343
+ state_dict[pair[0]] = state_dict[pair[1]]
344
+
345
+ return state_dict
346
+
347
+
348
+ def zero3_partitioned_param_info(unpartitioned_numel, world_size):
349
+ remainder = unpartitioned_numel % world_size
350
+ padding_numel = (world_size - remainder) if remainder else 0
351
+ partitioned_numel = math.ceil(unpartitioned_numel / world_size)
352
+ return partitioned_numel, padding_numel
353
+
354
+
355
+ def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
356
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
357
+ return
358
+
359
+ if debug:
360
+ for i in range(world_size):
361
+ num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
362
+ print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
363
+
364
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
365
+ wanted_params = len(frozen_param_shapes)
366
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
367
+ avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
368
+ print(f'Frozen params: Have {avail_numel} numels to process.')
369
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
370
+
371
+ total_params = 0
372
+ total_numel = 0
373
+ for name, shape in zero_model_states[0].frozen_param_shapes.items():
374
+ total_params += 1
375
+ unpartitioned_numel = shape.numel()
376
+ total_numel += unpartitioned_numel
377
+
378
+ param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
379
+ state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
380
+
381
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
382
+
383
+ if debug:
384
+ print(
385
+ f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
386
+ )
387
+
388
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
389
+
390
+
391
+ class GatheredTensor:
392
+ """
393
+ A pseudo tensor that collects partitioned weights.
394
+ It is more memory efficient when there are multiple groups.
395
+ """
396
+
397
+ def __init__(self, flat_groups, flat_groups_offset, offset, partitioned_numel, shape):
398
+ self.flat_groups = flat_groups
399
+ self.flat_groups_offset = flat_groups_offset
400
+ self.offset = offset
401
+ self.partitioned_numel = partitioned_numel
402
+ self.shape = shape
403
+ self.dtype = self.flat_groups[0][0].dtype
404
+
405
+ def contiguous(self):
406
+ """
407
+ Merge partitioned weights from flat_groups into a single tensor.
408
+ """
409
+ end_idx = self.offset + self.partitioned_numel
410
+ world_size = len(self.flat_groups)
411
+ pad_flat_param_chunks = []
412
+
413
+ for rank_i in range(world_size):
414
+ # for each rank, we need to collect weights from related group/groups
415
+ flat_groups_at_rank_i = self.flat_groups[rank_i]
416
+ start_group_id = None
417
+ end_group_id = None
418
+ for group_id in range(len(self.flat_groups_offset)):
419
+ if self.flat_groups_offset[group_id] <= self.offset < self.flat_groups_offset[group_id + 1]:
420
+ start_group_id = group_id
421
+ if self.flat_groups_offset[group_id] < end_idx <= self.flat_groups_offset[group_id + 1]:
422
+ end_group_id = group_id
423
+ break
424
+ # collect weights from related group/groups
425
+ for group_id in range(start_group_id, end_group_id + 1):
426
+ flat_tensor = flat_groups_at_rank_i[group_id]
427
+ start_offset = self.offset - self.flat_groups_offset[group_id]
428
+ end_offset = min(end_idx, self.flat_groups_offset[group_id + 1]) - self.flat_groups_offset[group_id]
429
+ pad_flat_param_chunks.append(flat_tensor[start_offset:end_offset])
430
+
431
+ # collect weights from all ranks
432
+ pad_flat_param = torch.cat(pad_flat_param_chunks, dim=0)
433
+ param = pad_flat_param[:self.shape.numel()].view(self.shape).contiguous()
434
+ return param
435
+
436
+
437
+ def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
438
+ param_shapes = zero_model_states[0].param_shapes
439
+ avail_numel = sum([flat_group.numel() for flat_group in fp32_flat_groups[0]]) * world_size
440
+
441
+ # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
442
+ # param, re-consolidating each param, while dealing with padding if any
443
+
444
+ # merge list of dicts, preserving order
445
+ param_shapes = {k: v for d in param_shapes for k, v in d.items()}
446
+
447
+ if debug:
448
+ for i in range(world_size):
449
+ print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
450
+
451
+ wanted_params = len(param_shapes)
452
+ wanted_numel = sum(shape.numel() for shape in param_shapes.values())
453
+ # not asserting if there is a mismatch due to possible padding
454
+ avail_numel = fp32_flat_groups[0].numel() * world_size
455
+ print(f"Trainable params: Have {avail_numel} numels to process.")
456
+ print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
457
+
458
+ # params
459
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
460
+ # out-of-core computing solution
461
+ offset = 0
462
+ total_numel = 0
463
+ total_params = 0
464
+ flat_groups_offset = [0] + list(np.cumsum([flat_tensor.numel() for flat_tensor in fp32_flat_groups[0]]))
465
+ for name, shape in tqdm(param_shapes.items(), desc='Gathering sharded weights'):
466
+ unpartitioned_numel = shape.numel()
467
+ total_numel += unpartitioned_numel
468
+ total_params += 1
469
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
470
+
471
+ if debug:
472
+ print(
473
+ f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
474
+ )
475
+
476
+ # memory efficient tensor
477
+ tensor = GatheredTensor(fp32_flat_groups, flat_groups_offset, offset, partitioned_numel, shape)
478
+ state_dict[name] = tensor
479
+ offset += partitioned_numel
480
+
481
+ offset *= world_size
482
+
483
+ # Sanity check
484
+ if offset != avail_numel:
485
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
486
+
487
+ print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
488
+
489
+
490
+ def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
491
+ exclude_frozen_parameters):
492
+ state_dict = OrderedDict()
493
+
494
+ # buffers
495
+ buffers = zero_model_states[0].buffers
496
+ state_dict.update(buffers)
497
+ if debug:
498
+ print(f"added {len(buffers)} buffers")
499
+
500
+ if not exclude_frozen_parameters:
501
+ _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
502
+
503
+ _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
504
+
505
+ # recover shared parameters
506
+ for pair in zero_model_states[0].shared_params:
507
+ if pair[1] in state_dict:
508
+ state_dict[pair[0]] = state_dict[pair[1]]
509
+
510
+ return state_dict
511
+
512
+
513
+ def to_torch_tensor(state_dict, return_empty_tensor=False):
514
+ """
515
+ Convert state_dict of GatheredTensor to torch tensor
516
+ """
517
+ converted_tensors = {}
518
+ for name, tensor in state_dict.items():
519
+ tensor_id = id(tensor)
520
+ if tensor_id in converted_tensors:
521
+ shared_tensor = state_dict[converted_tensors[tensor_id]]
522
+ state_dict[name] = shared_tensor
523
+ else:
524
+ converted_tensors[tensor_id] = name
525
+ if return_empty_tensor:
526
+ state_dict[name] = torch.empty(tensor.shape, dtype=tensor.dtype)
527
+ else:
528
+ state_dict[name] = tensor.contiguous()
529
+ return state_dict
530
+
531
+
532
+ def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir,
533
+ tag=None,
534
+ exclude_frozen_parameters=False,
535
+ lazy_mode=False):
536
+ """
537
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
538
+ ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
539
+ via a model hub.
540
+
541
+ Args:
542
+ - ``checkpoint_dir``: path to the desired checkpoint folder
543
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
544
+ - ``exclude_frozen_parameters``: exclude frozen parameters
545
+ - ``lazy_mode``: get state_dict in lazy mode. It returns a dict of pesduo tensor instead of torch tensor, which is more memory efficient.
546
+ Convert the pesduo tensor to torch tensor by ``.contiguous()``
547
+
548
+ Returns:
549
+ - pytorch ``state_dict``
550
+
551
+ A typical usage might be ::
552
+
553
+ from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
554
+ # do the training and checkpoint saving
555
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
556
+ model = model.cpu() # move to cpu
557
+ model.load_state_dict(state_dict)
558
+ # submit to model hub or save the model to share with others
559
+
560
+ In this example the ``model`` will no longer be usable in the deepspeed context of the same
561
+ application. i.e. you will need to re-initialize the deepspeed engine, since
562
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
563
+
564
+ If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
565
+
566
+ Note: the above usage may not work if your application doesn't have sufficient free CPU memory.
567
+ You may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
568
+ the checkpoint. Or you can load state_dict in lazy mode ::
569
+
570
+ from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
571
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, lazy_mode=True) # not on cpu
572
+ for name, lazy_tensor in state_dict.item():
573
+ tensor = lazy_tensor.contiguous() # to cpu
574
+ print(name, tensor)
575
+ # del tensor to release memory if it no longer in use
576
+ """
577
+ if tag is None:
578
+ latest_path = os.path.join(checkpoint_dir, 'latest')
579
+ if os.path.isfile(latest_path):
580
+ with open(latest_path, 'r') as fd:
581
+ tag = fd.read().strip()
582
+ else:
583
+ raise ValueError(f"Unable to find 'latest' file at {latest_path}")
584
+
585
+ ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
586
+
587
+ if not os.path.isdir(ds_checkpoint_dir):
588
+ raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
589
+
590
+ state_dict = _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters)
591
+ if lazy_mode:
592
+ return state_dict
593
+ else:
594
+ return to_torch_tensor(state_dict)
595
+
596
+
597
+ def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir,
598
+ output_dir,
599
+ max_shard_size="5GB",
600
+ safe_serialization=False,
601
+ tag=None,
602
+ exclude_frozen_parameters=False):
603
+ """
604
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
605
+ loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
606
+
607
+ Args:
608
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
609
+ - ``output_dir``: directory to the pytorch fp32 state_dict output files
610
+ - ``max_shard_size``: the maximum size for a checkpoint before being sharded, default value is 5GB
611
+ - ``safe_serialization``: whether to save the model using `safetensors` or the traditional PyTorch way (that uses `pickle`).
612
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
613
+ - ``exclude_frozen_parameters``: exclude frozen parameters
614
+ """
615
+
616
+ # Dependency pre-check
617
+ if safe_serialization:
618
+ try:
619
+ from safetensors.torch import save_file
620
+ except ImportError:
621
+ print('If you want to use `safe_serialization`, please `pip install safetensors`')
622
+ raise
623
+ if max_shard_size is not None:
624
+ try:
625
+ from huggingface_hub import split_torch_state_dict_into_shards
626
+ except ImportError:
627
+ print('If you want to use `max_shard_size`, please `pip install huggingface_hub`')
628
+ raise
629
+
630
+ # Convert zero checkpoint to state_dict
631
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir,
632
+ tag,
633
+ exclude_frozen_parameters,
634
+ lazy_mode=True)
635
+
636
+ # Shard the model if it is too big.
637
+ weights_name = "model.safetensors" if safe_serialization else "pytorch_model.bin"
638
+ if max_shard_size is not None:
639
+ filename_pattern = weights_name.replace(".bin", "{suffix}.bin").replace(".safetensors", "{suffix}.safetensors")
640
+ # an memory-efficient approach for sharding
641
+ empty_state_dict = to_torch_tensor(state_dict, return_empty_tensor=True)
642
+ state_dict_split = split_torch_state_dict_into_shards(empty_state_dict,
643
+ filename_pattern=filename_pattern,
644
+ max_shard_size=max_shard_size)
645
+ else:
646
+ from collections import namedtuple
647
+ StateDictSplit = namedtuple("StateDictSplit", ["is_sharded", "filename_to_tensors"])
648
+ state_dict_split = StateDictSplit(is_sharded=False,
649
+ filename_to_tensors={weights_name: list(state_dict.keys())})
650
+
651
+ # Save the model by shard
652
+ os.makedirs(output_dir, exist_ok=True)
653
+ filename_to_tensors = state_dict_split.filename_to_tensors.items()
654
+ for shard_file, tensors in tqdm(filename_to_tensors, desc="Saving checkpoint shards"):
655
+ shard_state_dict = {tensor_name: state_dict[tensor_name] for tensor_name in tensors}
656
+ shard_state_dict = to_torch_tensor(shard_state_dict)
657
+ output_path = os.path.join(output_dir, shard_file)
658
+ if safe_serialization:
659
+ save_file(shard_state_dict, output_path, metadata={"format": "pt"})
660
+ else:
661
+ torch.save(shard_state_dict, output_path)
662
+ # release the memory of current shard
663
+ for tensor_name in shard_state_dict:
664
+ del state_dict[tensor_name]
665
+ del shard_state_dict
666
+ gc.collect()
667
+
668
+ # Save index if sharded
669
+ if state_dict_split.is_sharded:
670
+ index = {
671
+ "metadata": state_dict_split.metadata,
672
+ "weight_map": state_dict_split.tensor_to_filename,
673
+ }
674
+ save_index_file = "model.safetensors.index.json" if safe_serialization else "pytorch_model.bin.index.json"
675
+ save_index_file = os.path.join(output_dir, save_index_file)
676
+ with open(save_index_file, "w", encoding="utf-8") as f:
677
+ content = json.dumps(index, indent=2, sort_keys=True) + "\n"
678
+ f.write(content)
679
+
680
+
681
+ def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
682
+ """
683
+ 1. Put the provided model to cpu
684
+ 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
685
+ 3. Load it into the provided model
686
+
687
+ Args:
688
+ - ``model``: the model object to update
689
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
690
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
691
+
692
+ Returns:
693
+ - ``model`: modified model
694
+
695
+ Make sure you have plenty of CPU memory available before you call this function. If you don't
696
+ have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
697
+ conveniently placed for you in the checkpoint folder.
698
+
699
+ A typical usage might be ::
700
+
701
+ from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
702
+ model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
703
+ # submit to model hub or save the model to share with others
704
+
705
+ Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
706
+ of the same application. i.e. you will need to re-initialize the deepspeed engine, since
707
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
708
+
709
+ """
710
+ logger.info(f"Extracting fp32 weights")
711
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
712
+
713
+ logger.info(f"Overwriting model with fp32 weights")
714
+ model = model.cpu()
715
+ model.load_state_dict(state_dict, strict=False)
716
+
717
+ return model
718
+
719
+
720
+ if __name__ == "__main__":
721
+ parser = argparse.ArgumentParser()
722
+ parser.add_argument("checkpoint_dir",
723
+ type=str,
724
+ help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
725
+ parser.add_argument("output_dir",
726
+ type=str,
727
+ help="directory to the pytorch fp32 state_dict output files"
728
+ "(e.g. path/checkpoint-12-output/)")
729
+ parser.add_argument(
730
+ "--max_shard_size",
731
+ type=str,
732
+ default="5GB",
733
+ help="The maximum size for a checkpoint before being sharded. Checkpoints shard will then be each of size"
734
+ "lower than this size. If expressed as a string, needs to be digits followed by a unit (like `5MB`"
735
+ "We default it to 5GB in order for models to be able to run easily on free-tier google colab instances"
736
+ "without CPU OOM issues.")
737
+ parser.add_argument(
738
+ "--safe_serialization",
739
+ default=False,
740
+ action='store_true',
741
+ help="Whether to save the model using `safetensors` or the traditional PyTorch way (that uses `pickle`).")
742
+ parser.add_argument("-t",
743
+ "--tag",
744
+ type=str,
745
+ default=None,
746
+ help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1")
747
+ parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters")
748
+ parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
749
+ args = parser.parse_args()
750
+
751
+ debug = args.debug
752
+
753
+ convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir,
754
+ args.output_dir,
755
+ max_shard_size=args.max_shard_size,
756
+ safe_serialization=args.safe_serialization,
757
+ tag=args.tag,
758
+ exclude_frozen_parameters=args.exclude_frozen_parameters)
config.json ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "action_dim": 32,
3
+ "action_head_cfg": {
4
+ "_convert_": "object",
5
+ "_target_": "groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHead",
6
+ "config": {
7
+ "_recursive_": false,
8
+ "_target_": "groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHeadConfig",
9
+ "action_dim": 32,
10
+ "action_horizon": 24,
11
+ "action_loss_embodiment_ids": [
12
+ 26,
13
+ 17,
14
+ 32
15
+ ],
16
+ "add_pos_embed": true,
17
+ "backbone_embedding_dim": 0,
18
+ "backbone_features_projector_cfg": null,
19
+ "decouple_video_action_noise": false,
20
+ "defer_lora_injection": true,
21
+ "diffusion_model_cfg": {
22
+ "_convert_": "object",
23
+ "_target_": "groot.vla.model.dreamzero.modules.wan_video_dit_action_casual_chunk.CausalWanModel",
24
+ "diffusion_model_pretrained_path": "/root/WAM/checkpoints/Wan2.1-I2V-14B-480P",
25
+ "dim": 5120,
26
+ "eps": 1e-06,
27
+ "ffn_dim": 13824,
28
+ "frame_seqlen": 880,
29
+ "freq_dim": 256,
30
+ "in_dim": 36,
31
+ "max_chunk_size": 4,
32
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535
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552
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584
+ default_instruction: Perform the default behavior.
585
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587
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600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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620
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621
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622
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623
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625
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626
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628
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629
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630
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631
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632
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633
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635
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637
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642
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647
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648
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649
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651
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652
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653
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654
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655
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656
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657
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660
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661
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663
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665
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666
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671
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675
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686
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693
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
+ robocasa_bimanual_panda_inspire_hand: 16
729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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748
+ gr1_isaac: 0
749
+ sim_behavior_r1_pro: 31
750
+ mecka_hands: 27
751
+ real_r1_pro_sharpa: 28
752
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
753
+ agibot:
754
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755
+ transforms:
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757
+ apply_to:
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762
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764
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767
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768
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769
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770
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774
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775
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776
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777
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780
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781
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785
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786
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791
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799
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809
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810
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812
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813
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814
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820
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821
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822
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823
+ apply_to:
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825
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826
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829
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830
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832
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833
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834
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835
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837
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838
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840
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+ - state.right_effector_position
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+ - state.head_position
850
+ - state.waist_position
851
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+ - action.waist_position
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+ - action.robot_velocity
859
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
860
+ default_instruction: Perform the default behavior.
861
+ language_dropout_prob: 0.0
862
+ always_use_default_instruction: false
863
+ max_state_dim: 64
864
+ max_action_dim: 32
865
+ max_length: 512
866
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+ action_horizon: 24
868
+ embodiment_tag_mapping:
869
+ real_gr1_arms_only: 0
870
+ real_gr1_arms_only_annotated: 1
871
+ real_gr1_arms_waist: 2
872
+ real_gr1_arms_waist_annotated: 3
873
+ dexmg_gr1_arms_only_inspire: 4
874
+ dexmg_gr1_arms_only_fourier: 5
875
+ dexmg_gr1_arms_waist_fourier: 6
876
+ robocasa_single_arm: 7
877
+ onex_eve_gripper: 8
878
+ robocasa_gr1_arms_only_inspire_hands: 9
879
+ robocasa_gr1_arms_only_fourier_hands: 10
880
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
881
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
882
+ robocasa_panda_omron: 13
883
+ robocasa_bimanual_panda_parallel_gripper: 15
884
+ robocasa_bimanual_panda_inspire_hand: 16
885
+ oxe_droid: 17
886
+ oxe_fractal: 18
887
+ oxe_language_table: 19
888
+ oxe_bridge: 20
889
+ real_panda_single_arm: 21
890
+ hot3d_hands_only: 23
891
+ gr1_unified: 24
892
+ robocasa_gr1_arms_waist_fourier_hands: 25
893
+ agibot: 26
894
+ bimanual_ur3: 26
895
+ lapa: 27
896
+ oxe_mutex: 28
897
+ oxe_roboset: 29
898
+ oxe_plex: 30
899
+ dream: 31
900
+ yam: 32
901
+ xdof: 22
902
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903
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904
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+ sim_behavior_r1_pro: 31
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+ mecka_hands: 27
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+ real_r1_pro_sharpa: 28
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+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
909
+ yam:
910
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911
+ transforms:
912
+ - _target_: groot.vla.data.transform.VideoToTensor
913
+ apply_to:
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+ - video.top_camera-images-rgb
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+ - video.left_camera-images-rgb
916
+ - video.right_camera-images-rgb
917
+ - _target_: groot.vla.data.transform.VideoCrop
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+ apply_to:
919
+ - video.top_camera-images-rgb
920
+ - video.left_camera-images-rgb
921
+ - video.right_camera-images-rgb
922
+ scale: 0.95
923
+ mode: random
924
+ - _target_: groot.vla.data.transform.VideoResize
925
+ apply_to:
926
+ - video.top_camera-images-rgb
927
+ - video.left_camera-images-rgb
928
+ - video.right_camera-images-rgb
929
+ height: 176
930
+ width: 320
931
+ interpolation: linear
932
+ - _target_: groot.vla.data.transform.VideoColorJitter
933
+ apply_to:
934
+ - video.top_camera-images-rgb
935
+ - video.left_camera-images-rgb
936
+ - video.right_camera-images-rgb
937
+ brightness: 0.3
938
+ contrast: 0.4
939
+ saturation: 0.5
940
+ hue: 0.08
941
+ - _target_: groot.vla.data.transform.VideoToNumpy
942
+ apply_to:
943
+ - video.top_camera-images-rgb
944
+ - video.left_camera-images-rgb
945
+ - video.right_camera-images-rgb
946
+ - _target_: groot.vla.data.transform.StateActionToTensor
947
+ apply_to:
948
+ - state.left_joint_pos
949
+ - state.left_gripper_pos
950
+ - state.right_joint_pos
951
+ - state.right_gripper_pos
952
+ - _target_: groot.vla.data.transform.StateActionTransform
953
+ apply_to:
954
+ - state.left_joint_pos
955
+ - state.left_gripper_pos
956
+ - state.right_joint_pos
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+ - state.right_gripper_pos
958
+ normalization_modes:
959
+ state.left_joint_pos: q99
960
+ state.left_gripper_pos: q99
961
+ state.right_joint_pos: q99
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+ state.right_gripper_pos: q99
963
+ - _target_: groot.vla.data.transform.StateActionToTensor
964
+ apply_to:
965
+ - action.left_joint_pos
966
+ - action.left_gripper_pos
967
+ - action.right_joint_pos
968
+ - action.right_gripper_pos
969
+ - _target_: groot.vla.data.transform.StateActionTransform
970
+ apply_to:
971
+ - action.left_joint_pos
972
+ - action.left_gripper_pos
973
+ - action.right_joint_pos
974
+ - action.right_gripper_pos
975
+ normalization_modes:
976
+ action.left_joint_pos: q99
977
+ action.left_gripper_pos: q99
978
+ action.right_joint_pos: q99
979
+ action.right_gripper_pos: q99
980
+ - _target_: groot.vla.data.transform.ConcatTransform
981
+ video_concat_order:
982
+ - video.top_camera-images-rgb
983
+ - video.left_camera-images-rgb
984
+ - video.right_camera-images-rgb
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+ state_concat_order:
986
+ - state.left_joint_pos
987
+ - state.left_gripper_pos
988
+ - state.right_joint_pos
989
+ - state.right_gripper_pos
990
+ action_concat_order:
991
+ - action.left_joint_pos
992
+ - action.left_gripper_pos
993
+ - action.right_joint_pos
994
+ - action.right_gripper_pos
995
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
996
+ default_instruction: Perform the default behavior.
997
+ language_dropout_prob: 0.0
998
+ always_use_default_instruction: false
999
+ max_state_dim: 64
1000
+ max_action_dim: 32
1001
+ max_length: 512
1002
+ state_horizon: 1
1003
+ action_horizon: 24
1004
+ embodiment_tag_mapping:
1005
+ real_gr1_arms_only: 0
1006
+ real_gr1_arms_only_annotated: 1
1007
+ real_gr1_arms_waist: 2
1008
+ real_gr1_arms_waist_annotated: 3
1009
+ dexmg_gr1_arms_only_inspire: 4
1010
+ dexmg_gr1_arms_only_fourier: 5
1011
+ dexmg_gr1_arms_waist_fourier: 6
1012
+ robocasa_single_arm: 7
1013
+ onex_eve_gripper: 8
1014
+ robocasa_gr1_arms_only_inspire_hands: 9
1015
+ robocasa_gr1_arms_only_fourier_hands: 10
1016
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1017
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1018
+ robocasa_panda_omron: 13
1019
+ robocasa_bimanual_panda_parallel_gripper: 15
1020
+ robocasa_bimanual_panda_inspire_hand: 16
1021
+ oxe_droid: 17
1022
+ oxe_fractal: 18
1023
+ oxe_language_table: 19
1024
+ oxe_bridge: 20
1025
+ real_panda_single_arm: 21
1026
+ hot3d_hands_only: 23
1027
+ gr1_unified: 24
1028
+ robocasa_gr1_arms_waist_fourier_hands: 25
1029
+ agibot: 26
1030
+ bimanual_ur3: 26
1031
+ lapa: 27
1032
+ oxe_mutex: 28
1033
+ oxe_roboset: 29
1034
+ oxe_plex: 30
1035
+ dream: 31
1036
+ yam: 32
1037
+ xdof: 22
1038
+ gr1_unified_segmentation: 14
1039
+ language_table_sim: 7
1040
+ gr1_isaac: 0
1041
+ sim_behavior_r1_pro: 31
1042
+ mecka_hands: 27
1043
+ real_r1_pro_sharpa: 28
1044
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
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+ metadata_versions:
1046
+ bimanual_ur3: '0221'
1047
+ oxe_droid: '0221'
1048
+ agibot: '0221'
1049
+ yam: '0221'
1050
+ fps:
1051
+ bimanual_ur3: 30
1052
+ yam: 30
1053
+ dataset_kwargs:
1054
+ video_backend: decord
1055
+ use_global_metadata: false
1056
+ max_chunk_size: 4
1057
+ relative_action: true
1058
+ relative_action_keys:
1059
+ - left_joint_pos
1060
+ - left_gripper_pos
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+ - right_joint_pos
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+ - right_gripper_pos
1063
+ relative_action_per_horizon: false
1064
+ mixture_kwargs:
1065
+ training: true
1066
+ balance_dataset_weights: false
1067
+ seed: 42
1068
+ shard_sampling_rate: 0.1
1069
+ trainer:
1070
+ _target_: groot.vla.experiment.VLATrainer
1071
+ _partial_: true
1072
+ _recursive_: false
1073
+ callbacks: null
1074
+ model: ???
1075
+ train_dataset: ???
1076
+ compute_dtype: ???
1077
+ benchmark_time: false
1078
+ enable_profiling: false
1079
+ profiling_steps: 5
1080
+ enable_prof_callback: false
1081
+ profile_start_step: 50
1082
+ profile_warmup_steps: 1
1083
+ profile_active_steps: 3
1084
+ profile_record_shapes: false
1085
+ profile_with_stack: false
1086
+ profile_memory: false
1087
+ wandb_project: dreamzero
1088
+ output_dir: /root/WAM/checkpoints/dreamzero_bimanual_ur3_lora
1089
+ load_from_yaml: null
1090
+ gear_credentials: null
1091
+ upload_checkpoints: false
1092
+ upload_every: 1000
1093
+ upload_last_n_checkpoints: 5
1094
+ remove_unused_columns: false
1095
+ bf16: true
1096
+ tf32: false
1097
+ global_batch_size: null
1098
+ raise_error_if_global_batch_size_not_set: false
1099
+ per_device_train_batch_size: 1
1100
+ per_device_eval_batch_size: 64
1101
+ gradient_accumulation_steps: 1
1102
+ dataloader_num_workers: 0
1103
+ dataloader_pin_memory: false
1104
+ dataloader_persistent_workers: true
1105
+ optim: adamw_torch
1106
+ learning_rate: 0.0001
1107
+ adam_beta1: 0.95
1108
+ adam_beta2: 0.999
1109
+ adam_epsilon: 1.0e-08
1110
+ weight_decay: 0
1111
+ lr_scheduler_type: cosine
1112
+ warmup_ratio: 0.05
1113
+ logging_steps: 10.0
1114
+ num_train_epochs: 1000
1115
+ max_steps: 20000
1116
+ save_strategy: steps
1117
+ save_steps: 10000
1118
+ eval_strategy: 'no'
1119
+ save_total_limit: 2
1120
+ report_to: none
1121
+ seed: 42
1122
+ do_eval: false
1123
+ gradient_checkpointing: false
1124
+ ddp_find_unused_parameters: false
1125
+ ddp_bucket_cap_mb: 100
1126
+ ray_num_workers: ???
1127
+ eval_bf16: true
1128
+ torch_compile_mode: null
1129
+ pretrained_model_path: /root/WAM/checkpoints/DreamZero-AgiBot
1130
+ only_tune_projectors: false
1131
+ save_llm: false
1132
+ save_lora_only: true
1133
+ save_value_model: false
1134
+ save_q_model: false
1135
+ download_cache: false
1136
+ training_args:
1137
+ _target_: transformers.TrainingArguments
1138
+ output_dir: /root/WAM/checkpoints/dreamzero_bimanual_ur3_lora
1139
+ run_name: dreamzero_bimanual_ur3_lora
1140
+ remove_unused_columns: false
1141
+ deepspeed: groot/vla/configs/deepspeed/zero2.json
1142
+ gradient_checkpointing: true
1143
+ bf16: true
1144
+ tf32: false
1145
+ per_device_train_batch_size: 1
1146
+ per_device_eval_batch_size: 64
1147
+ gradient_accumulation_steps: 1
1148
+ dataloader_num_workers: 0
1149
+ dataloader_pin_memory: false
1150
+ dataloader_persistent_workers: true
1151
+ optim: adamw_torch
1152
+ adam_beta1: 0.95
1153
+ adam_beta2: 0.999
1154
+ adam_epsilon: 1.0e-08
1155
+ learning_rate: 1.0e-05
1156
+ weight_decay: 0
1157
+ warmup_ratio: 0.05
1158
+ lr_scheduler_type: constant
1159
+ logging_steps: 10.0
1160
+ num_train_epochs: 1000
1161
+ max_steps: 20000
1162
+ save_strategy: steps
1163
+ save_steps: 10000
1164
+ save_total_limit: 2
1165
+ report_to: none
1166
+ seed: 42
1167
+ do_eval: false
1168
+ ddp_find_unused_parameters: false
1169
+ ddp_bucket_cap_mb: 100
1170
+ torch_compile_mode: null
1171
+ profile_dir: null
1172
+ backbone_hidden_size: 0
1173
+ backbone_cfg:
1174
+ _target_: groot.vla.model.dreamzero.backbone.identity.IdentityBackbone
1175
+ action_head_cfg:
1176
+ config:
1177
+ backbone_features_projector_cfg: null
1178
+ _target_: groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHeadConfig
1179
+ _recursive_: false
1180
+ tiled: false
1181
+ tile_size_height: 34
1182
+ tile_size_width: 34
1183
+ tile_stride_height: 18
1184
+ tile_stride_width: 16
1185
+ lora_rank: 4
1186
+ lora_alpha: 4
1187
+ num_frames: 33
1188
+ num_frame_per_block: 2
1189
+ lora_target_modules: q,k,v,o,ffn.0,ffn.2
1190
+ init_lora_weights: kaiming
1191
+ train_architecture: lora
1192
+ use_gradient_checkpointing: true
1193
+ add_pos_embed: true
1194
+ model_dtype: float32
1195
+ max_state_dim: 64
1196
+ max_action_dim: 32
1197
+ action_loss_embodiment_ids:
1198
+ - 26
1199
+ - 17
1200
+ - 32
1201
+ hidden_size: 64
1202
+ input_embedding_dim: 1536
1203
+ backbone_embedding_dim: 0
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+ repa_layer: 8
1205
+ repa_coeff: 1.0
1206
+ load_pretrained_det_decode_layer_path: null
1207
+ freeze_decode_layer: false
1208
+ expand_batch: null
1209
+ use_vlln: true
1210
+ vl_self_attention_cfg:
1211
+ _target_: groot.vla.model.n1_5.modules.cross_attention_dit.SelfAttentionTransformer
1212
+ positional_embeddings: null
1213
+ num_layers: 4
1214
+ num_attention_heads: 24
1215
+ attention_head_dim: 64
1216
+ dropout: 0.2
1217
+ final_dropout: true
1218
+ diffusion_model_cfg:
1219
+ _target_: groot.vla.model.dreamzero.modules.wan_video_dit_action_casual_chunk.CausalWanModel
1220
+ _convert_: object
1221
+ diffusion_model_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P
1222
+ model_type: i2v
1223
+ frame_seqlen: 880
1224
+ dim: 5120
1225
+ in_dim: 36
1226
+ ffn_dim: 13824
1227
+ out_dim: 16
1228
+ freq_dim: 256
1229
+ eps: 1.0e-06
1230
+ num_heads: 40
1231
+ num_layers: 40
1232
+ max_chunk_size: 4
1233
+ num_frame_per_block: 2
1234
+ num_action_per_block: 24
1235
+ num_state_per_block: 1
1236
+ text_encoder_cfg:
1237
+ _target_: groot.vla.model.dreamzero.modules.wan_video_text_encoder.WanTextEncoder
1238
+ _convert_: object
1239
+ text_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
1240
+ image_encoder_cfg:
1241
+ _target_: groot.vla.model.dreamzero.modules.wan_video_image_encoder.WanImageEncoder
1242
+ _convert_: object
1243
+ image_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
1244
+ vae_cfg:
1245
+ _target_: groot.vla.model.dreamzero.modules.wan_video_vae.WanVideoVAE
1246
+ _convert_: object
1247
+ vae_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
1248
+ action_dim: 32
1249
+ action_horizon: 24
1250
+ num_inference_timesteps: 4
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+ noise_beta_alpha: 1.5
1252
+ noise_beta_beta: 1.0
1253
+ noise_s: 0.999
1254
+ num_timestep_buckets: 1000
1255
+ decouple_video_action_noise: false
1256
+ video_noise_beta_alpha: 3.0
1257
+ video_noise_beta_beta: 1.0
1258
+ tune_projector: true
1259
+ tune_diffusion_model: true
1260
+ skip_component_loading: true
1261
+ defer_lora_injection: true
1262
+ _target_: groot.vla.model.dreamzero.action_head.wan_flow_matching_action_tf.WANPolicyHead
1263
+ _convert_: object
1264
+ add_pos_embed: true
1265
+ hidden_size: 64
1266
+ attn_dropout: 0.2
1267
+ repa_layer: 8
1268
+ repa_coeff: 1.0
1269
+ load_pretrained_det_decode_layer_path: null
1270
+ expand_batch: null
1271
+ dit_version: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P
1272
+ text_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_t5_umt5-xxl-enc-bf16.pth
1273
+ image_encoder_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
1274
+ vae_pretrained_path: /root/WAM/checkpoints/Wan2.1-I2V-14B-480P/Wan2.1_VAE.pth
1275
+ train_architecture: lora
1276
+ num_frame_per_block: 2
1277
+ num_action_per_block: 24
1278
+ num_state_per_block: 1
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+ frame_seqlen: 880
1280
+ embodiment_tag_to_projector_index:
1281
+ real_gr1_arms_only: 0
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+ real_gr1_arms_only_annotated: 1
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+ real_gr1_arms_waist: 2
1284
+ real_gr1_arms_waist_annotated: 3
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+ dexmg_gr1_arms_only_inspire: 4
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+ dexmg_gr1_arms_only_fourier: 5
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+ dexmg_gr1_arms_waist_fourier: 6
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+ robocasa_single_arm: 7
1289
+ onex_eve_gripper: 8
1290
+ robocasa_gr1_arms_only_inspire_hands: 9
1291
+ robocasa_gr1_arms_only_fourier_hands: 10
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+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
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+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1294
+ robocasa_panda_omron: 13
1295
+ robocasa_bimanual_panda_parallel_gripper: 15
1296
+ robocasa_bimanual_panda_inspire_hand: 16
1297
+ oxe_droid: 17
1298
+ oxe_fractal: 18
1299
+ oxe_language_table: 19
1300
+ oxe_bridge: 20
1301
+ real_panda_single_arm: 21
1302
+ hot3d_hands_only: 23
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+ gr1_unified: 24
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+ bimanual_ur3: 26
1307
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+ oxe_plex: 30
1311
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+ yam: 32
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+ language_table_sim: 7
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+ sim_behavior_r1_pro: 31
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+ mecka_hands: 27
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+ real_r1_pro_sharpa: 28
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+ max_length: 512
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+ num_views: 3
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+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1323
+ data_collator:
1324
+ _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DefaultDataCollator
1325
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1326
+ max_length: 512
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+ num_views: 3
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+ embodiment_tag_mapping:
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+ real_gr1_arms_only: 0
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+ real_gr1_arms_waist: 2
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+ max_state_dim: 64
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+ max_action_dim: 32
1371
+ language_dropout_prob: 0.0
1372
+ model_specific_transform:
1373
+ _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1374
+ default_instruction: Perform the default behavior.
1375
+ language_dropout_prob: 0.0
1376
+ always_use_default_instruction: false
1377
+ max_state_dim: 64
1378
+ max_action_dim: 32
1379
+ max_length: 512
1380
+ state_horizon: 1
1381
+ action_horizon: 24
1382
+ embodiment_tag_mapping:
1383
+ real_gr1_arms_only: 0
1384
+ real_gr1_arms_only_annotated: 1
1385
+ real_gr1_arms_waist: 2
1386
+ real_gr1_arms_waist_annotated: 3
1387
+ dexmg_gr1_arms_only_inspire: 4
1388
+ dexmg_gr1_arms_only_fourier: 5
1389
+ dexmg_gr1_arms_waist_fourier: 6
1390
+ robocasa_single_arm: 7
1391
+ onex_eve_gripper: 8
1392
+ robocasa_gr1_arms_only_inspire_hands: 9
1393
+ robocasa_gr1_arms_only_fourier_hands: 10
1394
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1395
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1396
+ robocasa_panda_omron: 13
1397
+ robocasa_bimanual_panda_parallel_gripper: 15
1398
+ robocasa_bimanual_panda_inspire_hand: 16
1399
+ oxe_droid: 17
1400
+ oxe_fractal: 18
1401
+ oxe_language_table: 19
1402
+ oxe_bridge: 20
1403
+ real_panda_single_arm: 21
1404
+ hot3d_hands_only: 23
1405
+ gr1_unified: 24
1406
+ robocasa_gr1_arms_waist_fourier_hands: 25
1407
+ agibot: 26
1408
+ bimanual_ur3: 26
1409
+ lapa: 27
1410
+ oxe_mutex: 28
1411
+ oxe_roboset: 29
1412
+ oxe_plex: 30
1413
+ dream: 31
1414
+ yam: 32
1415
+ xdof: 22
1416
+ gr1_unified_segmentation: 14
1417
+ language_table_sim: 7
1418
+ gr1_isaac: 0
1419
+ sim_behavior_r1_pro: 31
1420
+ mecka_hands: 27
1421
+ real_r1_pro_sharpa: 28
1422
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1423
+ use_global_metadata: false
1424
+ num_frames: 33
1425
+ action_horizon: 24
1426
+ state_horizon: 1
1427
+ image_resolution_width: 320
1428
+ image_resolution_height: 176
1429
+ image_resolution_width_single_frame: 256
1430
+ image_resolution_height_single_frame: 256
1431
+ totensor_cfg:
1432
+ _target_: groot.vla.data.transform.VideoToTensor
1433
+ apply_to: ???
1434
+ crop_cfg:
1435
+ _target_: groot.vla.data.transform.VideoCrop
1436
+ apply_to: ???
1437
+ scale: 0.95
1438
+ mode: random
1439
+ resize_cfg:
1440
+ _target_: groot.vla.data.transform.VideoResize
1441
+ apply_to: ???
1442
+ height: 176
1443
+ width: 320
1444
+ interpolation: linear
1445
+ resize_cfg_single_frame:
1446
+ _target_: groot.vla.data.transform.VideoResize
1447
+ apply_to: ???
1448
+ height: 256
1449
+ width: 256
1450
+ interpolation: linear
1451
+ color_jitter_cfg:
1452
+ _target_: groot.vla.data.transform.VideoColorJitter
1453
+ apply_to: ???
1454
+ brightness: 0.3
1455
+ contrast: 0.4
1456
+ saturation: 0.5
1457
+ hue: 0.08
1458
+ random_grayscale_cfg:
1459
+ _target_: groot.vla.data.transform.VideoRandomGrayscale
1460
+ apply_to: ???
1461
+ p: 0.1
1462
+ random_posterize_cfg:
1463
+ _target_: groot.vla.data.transform.VideoRandomPosterize
1464
+ apply_to: ???
1465
+ bits: 4
1466
+ p: 0.1
1467
+ normalize_cfg:
1468
+ _target_: groot.vla.data.transform.VideoNormalize
1469
+ apply_to: ???
1470
+ mean:
1471
+ - 0.5
1472
+ - 0.5
1473
+ - 0.5
1474
+ std:
1475
+ - 0.5
1476
+ - 0.5
1477
+ - 0.5
1478
+ to_numpy_cfg:
1479
+ _target_: groot.vla.data.transform.VideoToNumpy
1480
+ apply_to: ???
1481
+ modality_config_bimanual_ur3:
1482
+ video:
1483
+ _target_: groot.vla.data.dataset.ModalityConfig
1484
+ delta_indices:
1485
+ - 0
1486
+ - 1
1487
+ - 2
1488
+ - 3
1489
+ - 4
1490
+ - 5
1491
+ - 6
1492
+ - 7
1493
+ - 8
1494
+ - 9
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+ - 10
1496
+ - 11
1497
+ - 12
1498
+ - 13
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+ - 14
1500
+ - 15
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+ - 16
1502
+ - 17
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+ - 18
1504
+ - 19
1505
+ - 20
1506
+ - 21
1507
+ - 22
1508
+ - 23
1509
+ - 24
1510
+ - 25
1511
+ - 26
1512
+ - 27
1513
+ - 28
1514
+ - 29
1515
+ - 30
1516
+ - 31
1517
+ - 32
1518
+ eval_delta_indices:
1519
+ - 0
1520
+ modality_keys:
1521
+ - video.top_head
1522
+ - video.hand_left
1523
+ - video.hand_right
1524
+ state:
1525
+ _target_: groot.vla.data.dataset.ModalityConfig
1526
+ delta_indices:
1527
+ - 0
1528
+ modality_keys:
1529
+ - state.left_joint_pos
1530
+ - state.left_gripper_pos
1531
+ - state.right_joint_pos
1532
+ - state.right_gripper_pos
1533
+ action:
1534
+ _target_: groot.vla.data.dataset.ModalityConfig
1535
+ delta_indices:
1536
+ - 0
1537
+ - 1
1538
+ - 2
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+ - 3
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+ - 4
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+ - 5
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+ - 6
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1544
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1545
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1546
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1547
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1548
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1549
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1551
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1552
+ - 16
1553
+ - 17
1554
+ - 18
1555
+ - 19
1556
+ - 20
1557
+ - 21
1558
+ - 22
1559
+ - 23
1560
+ modality_keys:
1561
+ - action.left_joint_pos
1562
+ - action.left_gripper_pos
1563
+ - action.right_joint_pos
1564
+ - action.right_gripper_pos
1565
+ language:
1566
+ _target_: groot.vla.data.dataset.ModalityConfig
1567
+ delta_indices:
1568
+ - 0
1569
+ modality_keys:
1570
+ - annotation.task
1571
+ transform_bimanual_ur3:
1572
+ _target_: groot.vla.data.transform.ComposedModalityTransform
1573
+ transforms:
1574
+ - _target_: groot.vla.data.transform.VideoToTensor
1575
+ apply_to:
1576
+ - video.top_head
1577
+ - _target_: groot.vla.data.transform.VideoCrop
1578
+ apply_to:
1579
+ - video.top_head
1580
+ scale: 0.95
1581
+ mode: random
1582
+ - _target_: groot.vla.data.transform.VideoResize
1583
+ apply_to:
1584
+ - video.top_head
1585
+ height: 176
1586
+ width: 320
1587
+ interpolation: linear
1588
+ - _target_: groot.vla.data.transform.VideoToTensor
1589
+ apply_to:
1590
+ - video.hand_left
1591
+ - video.hand_right
1592
+ - _target_: groot.vla.data.transform.VideoCrop
1593
+ apply_to:
1594
+ - video.hand_left
1595
+ - video.hand_right
1596
+ scale: 0.95
1597
+ mode: random
1598
+ - _target_: groot.vla.data.transform.VideoResize
1599
+ apply_to:
1600
+ - video.hand_left
1601
+ - video.hand_right
1602
+ height: 176
1603
+ width: 320
1604
+ interpolation: linear
1605
+ - _target_: groot.vla.data.transform.VideoColorJitter
1606
+ apply_to:
1607
+ - video.top_head
1608
+ - video.hand_left
1609
+ - video.hand_right
1610
+ brightness: 0.3
1611
+ contrast: 0.4
1612
+ saturation: 0.5
1613
+ hue: 0.08
1614
+ - _target_: groot.vla.data.transform.VideoToNumpy
1615
+ apply_to:
1616
+ - video.top_head
1617
+ - video.hand_left
1618
+ - video.hand_right
1619
+ - _target_: groot.vla.data.transform.StateActionToTensor
1620
+ apply_to:
1621
+ - state.left_joint_pos
1622
+ - state.left_gripper_pos
1623
+ - state.right_joint_pos
1624
+ - state.right_gripper_pos
1625
+ - _target_: groot.vla.data.transform.StateActionTransform
1626
+ apply_to:
1627
+ - state.left_joint_pos
1628
+ - state.left_gripper_pos
1629
+ - state.right_joint_pos
1630
+ - state.right_gripper_pos
1631
+ normalization_modes:
1632
+ state.left_joint_pos: q99
1633
+ state.left_gripper_pos: q99
1634
+ state.right_joint_pos: q99
1635
+ state.right_gripper_pos: q99
1636
+ - _target_: groot.vla.data.transform.StateActionToTensor
1637
+ apply_to:
1638
+ - action.left_joint_pos
1639
+ - action.left_gripper_pos
1640
+ - action.right_joint_pos
1641
+ - action.right_gripper_pos
1642
+ - _target_: groot.vla.data.transform.StateActionTransform
1643
+ apply_to:
1644
+ - action.left_joint_pos
1645
+ - action.left_gripper_pos
1646
+ - action.right_joint_pos
1647
+ - action.right_gripper_pos
1648
+ normalization_modes:
1649
+ action.left_joint_pos: q99
1650
+ action.left_gripper_pos: q99
1651
+ action.right_joint_pos: q99
1652
+ action.right_gripper_pos: q99
1653
+ - _target_: groot.vla.data.transform.ConcatTransform
1654
+ video_concat_order:
1655
+ - video.top_head
1656
+ - video.hand_left
1657
+ - video.hand_right
1658
+ state_concat_order:
1659
+ - state.left_joint_pos
1660
+ - state.left_gripper_pos
1661
+ - state.right_joint_pos
1662
+ - state.right_gripper_pos
1663
+ action_concat_order:
1664
+ - action.left_joint_pos
1665
+ - action.left_gripper_pos
1666
+ - action.right_joint_pos
1667
+ - action.right_gripper_pos
1668
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1669
+ default_instruction: Perform the default behavior.
1670
+ language_dropout_prob: 0.0
1671
+ always_use_default_instruction: false
1672
+ max_state_dim: 64
1673
+ max_action_dim: 32
1674
+ max_length: 512
1675
+ state_horizon: 1
1676
+ action_horizon: 24
1677
+ embodiment_tag_mapping:
1678
+ real_gr1_arms_only: 0
1679
+ real_gr1_arms_only_annotated: 1
1680
+ real_gr1_arms_waist: 2
1681
+ real_gr1_arms_waist_annotated: 3
1682
+ dexmg_gr1_arms_only_inspire: 4
1683
+ dexmg_gr1_arms_only_fourier: 5
1684
+ dexmg_gr1_arms_waist_fourier: 6
1685
+ robocasa_single_arm: 7
1686
+ onex_eve_gripper: 8
1687
+ robocasa_gr1_arms_only_inspire_hands: 9
1688
+ robocasa_gr1_arms_only_fourier_hands: 10
1689
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1690
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1691
+ robocasa_panda_omron: 13
1692
+ robocasa_bimanual_panda_parallel_gripper: 15
1693
+ robocasa_bimanual_panda_inspire_hand: 16
1694
+ oxe_droid: 17
1695
+ oxe_fractal: 18
1696
+ oxe_language_table: 19
1697
+ oxe_bridge: 20
1698
+ real_panda_single_arm: 21
1699
+ hot3d_hands_only: 23
1700
+ gr1_unified: 24
1701
+ robocasa_gr1_arms_waist_fourier_hands: 25
1702
+ agibot: 26
1703
+ bimanual_ur3: 26
1704
+ lapa: 27
1705
+ oxe_mutex: 28
1706
+ oxe_roboset: 29
1707
+ oxe_plex: 30
1708
+ dream: 31
1709
+ yam: 32
1710
+ xdof: 22
1711
+ gr1_unified_segmentation: 14
1712
+ language_table_sim: 7
1713
+ gr1_isaac: 0
1714
+ sim_behavior_r1_pro: 31
1715
+ mecka_hands: 27
1716
+ real_r1_pro_sharpa: 28
1717
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1718
+ modality_config_oxe_droid:
1719
+ video:
1720
+ _target_: groot.vla.data.dataset.ModalityConfig
1721
+ delta_indices:
1722
+ - 0
1723
+ - 1
1724
+ - 2
1725
+ - 3
1726
+ - 4
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1728
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1729
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1730
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1731
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1747
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+ - 26
1749
+ - 27
1750
+ - 28
1751
+ - 29
1752
+ - 30
1753
+ - 31
1754
+ - 32
1755
+ eval_delta_indices:
1756
+ - 0
1757
+ modality_keys:
1758
+ - video.exterior_image_1_left
1759
+ - video.exterior_image_2_left
1760
+ - video.wrist_image_left
1761
+ state:
1762
+ _target_: groot.vla.data.dataset.ModalityConfig
1763
+ delta_indices:
1764
+ - 0
1765
+ modality_keys:
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+ - state.joint_position
1767
+ - state.gripper_position
1768
+ action:
1769
+ _target_: groot.vla.data.dataset.ModalityConfig
1770
+ delta_indices:
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1772
+ - 1
1773
+ - 2
1774
+ - 3
1775
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1779
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1788
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1789
+ - 18
1790
+ - 19
1791
+ - 20
1792
+ - 21
1793
+ - 22
1794
+ - 23
1795
+ modality_keys:
1796
+ - action.joint_position
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+ - action.gripper_position
1798
+ language:
1799
+ _target_: groot.vla.data.dataset.ModalityConfig
1800
+ delta_indices:
1801
+ - 0
1802
+ modality_keys:
1803
+ - annotation.language.language_instruction
1804
+ - annotation.language.language_instruction_2
1805
+ - annotation.language.language_instruction_3
1806
+ lapa_action:
1807
+ _target_: groot.vla.data.dataset.ModalityConfig
1808
+ delta_indices:
1809
+ - 0
1810
+ modality_keys:
1811
+ - lapa_action
1812
+ transform_oxe_droid:
1813
+ _target_: groot.vla.data.transform.ComposedModalityTransform
1814
+ transforms:
1815
+ - _target_: groot.vla.data.transform.VideoToTensor
1816
+ apply_to:
1817
+ - video.exterior_image_1_left
1818
+ - video.exterior_image_2_left
1819
+ - video.wrist_image_left
1820
+ - _target_: groot.vla.data.transform.VideoCrop
1821
+ apply_to:
1822
+ - video.exterior_image_1_left
1823
+ - video.exterior_image_2_left
1824
+ - video.wrist_image_left
1825
+ scale: 0.95
1826
+ mode: random
1827
+ - _target_: groot.vla.data.transform.VideoResize
1828
+ apply_to:
1829
+ - video.exterior_image_1_left
1830
+ - video.exterior_image_2_left
1831
+ - video.wrist_image_left
1832
+ height: 176
1833
+ width: 320
1834
+ interpolation: linear
1835
+ - _target_: groot.vla.data.transform.VideoColorJitter
1836
+ apply_to:
1837
+ - video.exterior_image_1_left
1838
+ - video.exterior_image_2_left
1839
+ - video.wrist_image_left
1840
+ brightness: 0.3
1841
+ contrast: 0.4
1842
+ saturation: 0.5
1843
+ hue: 0.08
1844
+ - _target_: groot.vla.data.transform.VideoToNumpy
1845
+ apply_to:
1846
+ - video.exterior_image_1_left
1847
+ - video.exterior_image_2_left
1848
+ - video.wrist_image_left
1849
+ - _target_: groot.vla.data.transform.StateActionToTensor
1850
+ apply_to:
1851
+ - state.joint_position
1852
+ - state.gripper_position
1853
+ - _target_: groot.vla.data.transform.StateActionTransform
1854
+ apply_to:
1855
+ - state.joint_position
1856
+ - state.gripper_position
1857
+ normalization_modes:
1858
+ state.joint_position: q99
1859
+ state.gripper_position: q99
1860
+ - _target_: groot.vla.data.transform.StateActionToTensor
1861
+ apply_to:
1862
+ - action.joint_position
1863
+ - action.gripper_position
1864
+ - _target_: groot.vla.data.transform.StateActionTransform
1865
+ apply_to:
1866
+ - action.joint_position
1867
+ - action.gripper_position
1868
+ normalization_modes:
1869
+ action.joint_position: q99
1870
+ action.gripper_position: q99
1871
+ - _target_: groot.vla.data.transform.ConcatTransform
1872
+ video_concat_order:
1873
+ - video.exterior_image_1_left
1874
+ - video.exterior_image_2_left
1875
+ - video.wrist_image_left
1876
+ state_concat_order:
1877
+ - state.joint_position
1878
+ - state.gripper_position
1879
+ action_concat_order:
1880
+ - action.joint_position
1881
+ - action.gripper_position
1882
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
1883
+ default_instruction: Perform the default behavior.
1884
+ language_dropout_prob: 0.0
1885
+ always_use_default_instruction: false
1886
+ max_state_dim: 64
1887
+ max_action_dim: 32
1888
+ max_length: 512
1889
+ state_horizon: 1
1890
+ action_horizon: 24
1891
+ embodiment_tag_mapping:
1892
+ real_gr1_arms_only: 0
1893
+ real_gr1_arms_only_annotated: 1
1894
+ real_gr1_arms_waist: 2
1895
+ real_gr1_arms_waist_annotated: 3
1896
+ dexmg_gr1_arms_only_inspire: 4
1897
+ dexmg_gr1_arms_only_fourier: 5
1898
+ dexmg_gr1_arms_waist_fourier: 6
1899
+ robocasa_single_arm: 7
1900
+ onex_eve_gripper: 8
1901
+ robocasa_gr1_arms_only_inspire_hands: 9
1902
+ robocasa_gr1_arms_only_fourier_hands: 10
1903
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
1904
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
1905
+ robocasa_panda_omron: 13
1906
+ robocasa_bimanual_panda_parallel_gripper: 15
1907
+ robocasa_bimanual_panda_inspire_hand: 16
1908
+ oxe_droid: 17
1909
+ oxe_fractal: 18
1910
+ oxe_language_table: 19
1911
+ oxe_bridge: 20
1912
+ real_panda_single_arm: 21
1913
+ hot3d_hands_only: 23
1914
+ gr1_unified: 24
1915
+ robocasa_gr1_arms_waist_fourier_hands: 25
1916
+ agibot: 26
1917
+ bimanual_ur3: 26
1918
+ lapa: 27
1919
+ oxe_mutex: 28
1920
+ oxe_roboset: 29
1921
+ oxe_plex: 30
1922
+ dream: 31
1923
+ yam: 32
1924
+ xdof: 22
1925
+ gr1_unified_segmentation: 14
1926
+ language_table_sim: 7
1927
+ gr1_isaac: 0
1928
+ sim_behavior_r1_pro: 31
1929
+ mecka_hands: 27
1930
+ real_r1_pro_sharpa: 28
1931
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
1932
+ modality_config_agibot:
1933
+ video:
1934
+ _target_: groot.vla.data.dataset.ModalityConfig
1935
+ delta_indices:
1936
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1937
+ - 1
1938
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1939
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1940
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1941
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1942
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1968
+ - 32
1969
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1970
+ - -3
1971
+ - -2
1972
+ - -1
1973
+ - 0
1974
+ modality_keys:
1975
+ - video.top_head
1976
+ - video.hand_left
1977
+ - video.hand_right
1978
+ state:
1979
+ _target_: groot.vla.data.dataset.ModalityConfig
1980
+ delta_indices:
1981
+ - 0
1982
+ modality_keys:
1983
+ - state.left_arm_joint_position
1984
+ - state.right_arm_joint_position
1985
+ - state.left_effector_position
1986
+ - state.right_effector_position
1987
+ - state.head_position
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+ - state.waist_position
1989
+ action:
1990
+ _target_: groot.vla.data.dataset.ModalityConfig
1991
+ delta_indices:
1992
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1993
+ - 1
1994
+ - 2
1995
+ - 3
1996
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1997
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1998
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1999
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2008
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2009
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2010
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2011
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2012
+ - 20
2013
+ - 21
2014
+ - 22
2015
+ - 23
2016
+ modality_keys:
2017
+ - action.left_arm_joint_position
2018
+ - action.right_arm_joint_position
2019
+ - action.left_effector_position
2020
+ - action.right_effector_position
2021
+ - action.head_position
2022
+ - action.waist_position
2023
+ - action.robot_velocity
2024
+ language:
2025
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2026
+ delta_indices:
2027
+ - 0
2028
+ modality_keys:
2029
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2030
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2031
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2032
+ transforms:
2033
+ - _target_: groot.vla.data.transform.VideoToTensor
2034
+ apply_to:
2035
+ - video.top_head
2036
+ - video.hand_left
2037
+ - video.hand_right
2038
+ - _target_: groot.vla.data.transform.VideoCrop
2039
+ apply_to:
2040
+ - video.top_head
2041
+ - video.hand_left
2042
+ - video.hand_right
2043
+ scale: 0.95
2044
+ mode: random
2045
+ - _target_: groot.vla.data.transform.VideoResize
2046
+ apply_to:
2047
+ - video.top_head
2048
+ - video.hand_left
2049
+ - video.hand_right
2050
+ height: 176
2051
+ width: 320
2052
+ interpolation: linear
2053
+ - _target_: groot.vla.data.transform.VideoColorJitter
2054
+ apply_to:
2055
+ - video.top_head
2056
+ - video.hand_left
2057
+ - video.hand_right
2058
+ brightness: 0.3
2059
+ contrast: 0.4
2060
+ saturation: 0.5
2061
+ hue: 0.08
2062
+ - _target_: groot.vla.data.transform.VideoToNumpy
2063
+ apply_to:
2064
+ - video.top_head
2065
+ - video.hand_left
2066
+ - video.hand_right
2067
+ - _target_: groot.vla.data.transform.StateActionToTensor
2068
+ apply_to:
2069
+ - state.left_arm_joint_position
2070
+ - state.right_arm_joint_position
2071
+ - state.left_effector_position
2072
+ - state.right_effector_position
2073
+ - state.head_position
2074
+ - state.waist_position
2075
+ - _target_: groot.vla.data.transform.StateActionTransform
2076
+ apply_to:
2077
+ - state.left_arm_joint_position
2078
+ - state.right_arm_joint_position
2079
+ - state.left_effector_position
2080
+ - state.right_effector_position
2081
+ - state.head_position
2082
+ - state.waist_position
2083
+ normalization_modes:
2084
+ state.left_arm_joint_position: q99
2085
+ state.right_arm_joint_position: q99
2086
+ state.left_effector_position: q99
2087
+ state.right_effector_position: q99
2088
+ state.head_position: q99
2089
+ state.waist_position: q99
2090
+ - _target_: groot.vla.data.transform.StateActionToTensor
2091
+ apply_to:
2092
+ - action.left_arm_joint_position
2093
+ - action.right_arm_joint_position
2094
+ - action.left_effector_position
2095
+ - action.right_effector_position
2096
+ - action.head_position
2097
+ - action.waist_position
2098
+ - action.robot_velocity
2099
+ - _target_: groot.vla.data.transform.StateActionTransform
2100
+ apply_to:
2101
+ - action.left_arm_joint_position
2102
+ - action.right_arm_joint_position
2103
+ - action.left_effector_position
2104
+ - action.right_effector_position
2105
+ - action.head_position
2106
+ - action.waist_position
2107
+ - action.robot_velocity
2108
+ normalization_modes:
2109
+ action.left_arm_joint_position: q99
2110
+ action.right_arm_joint_position: q99
2111
+ action.left_effector_position: q99
2112
+ action.right_effector_position: q99
2113
+ action.head_position: q99
2114
+ action.waist_position: q99
2115
+ action.robot_velocity: q99
2116
+ - _target_: groot.vla.data.transform.ConcatTransform
2117
+ video_concat_order:
2118
+ - video.top_head
2119
+ - video.hand_left
2120
+ - video.hand_right
2121
+ state_concat_order:
2122
+ - state.left_arm_joint_position
2123
+ - state.right_arm_joint_position
2124
+ - state.left_effector_position
2125
+ - state.right_effector_position
2126
+ - state.head_position
2127
+ - state.waist_position
2128
+ action_concat_order:
2129
+ - action.left_arm_joint_position
2130
+ - action.right_arm_joint_position
2131
+ - action.left_effector_position
2132
+ - action.right_effector_position
2133
+ - action.head_position
2134
+ - action.waist_position
2135
+ - action.robot_velocity
2136
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
2137
+ default_instruction: Perform the default behavior.
2138
+ language_dropout_prob: 0.0
2139
+ always_use_default_instruction: false
2140
+ max_state_dim: 64
2141
+ max_action_dim: 32
2142
+ max_length: 512
2143
+ state_horizon: 1
2144
+ action_horizon: 24
2145
+ embodiment_tag_mapping:
2146
+ real_gr1_arms_only: 0
2147
+ real_gr1_arms_only_annotated: 1
2148
+ real_gr1_arms_waist: 2
2149
+ real_gr1_arms_waist_annotated: 3
2150
+ dexmg_gr1_arms_only_inspire: 4
2151
+ dexmg_gr1_arms_only_fourier: 5
2152
+ dexmg_gr1_arms_waist_fourier: 6
2153
+ robocasa_single_arm: 7
2154
+ onex_eve_gripper: 8
2155
+ robocasa_gr1_arms_only_inspire_hands: 9
2156
+ robocasa_gr1_arms_only_fourier_hands: 10
2157
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
2158
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
2159
+ robocasa_panda_omron: 13
2160
+ robocasa_bimanual_panda_parallel_gripper: 15
2161
+ robocasa_bimanual_panda_inspire_hand: 16
2162
+ oxe_droid: 17
2163
+ oxe_fractal: 18
2164
+ oxe_language_table: 19
2165
+ oxe_bridge: 20
2166
+ real_panda_single_arm: 21
2167
+ hot3d_hands_only: 23
2168
+ gr1_unified: 24
2169
+ robocasa_gr1_arms_waist_fourier_hands: 25
2170
+ agibot: 26
2171
+ bimanual_ur3: 26
2172
+ lapa: 27
2173
+ oxe_mutex: 28
2174
+ oxe_roboset: 29
2175
+ oxe_plex: 30
2176
+ dream: 31
2177
+ yam: 32
2178
+ xdof: 22
2179
+ gr1_unified_segmentation: 14
2180
+ language_table_sim: 7
2181
+ gr1_isaac: 0
2182
+ sim_behavior_r1_pro: 31
2183
+ mecka_hands: 27
2184
+ real_r1_pro_sharpa: 28
2185
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
2186
+ modality_config_yam:
2187
+ video:
2188
+ _target_: groot.vla.data.dataset.ModalityConfig
2189
+ delta_indices:
2190
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2191
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2192
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2193
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2194
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2219
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2220
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2221
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2222
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2223
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2224
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2225
+ modality_keys:
2226
+ - video.top_camera-images-rgb
2227
+ - video.left_camera-images-rgb
2228
+ - video.right_camera-images-rgb
2229
+ state:
2230
+ _target_: groot.vla.data.dataset.ModalityConfig
2231
+ delta_indices:
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2233
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2234
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2235
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2238
+ action:
2239
+ _target_: groot.vla.data.dataset.ModalityConfig
2240
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2261
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2262
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2263
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2264
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2265
+ modality_keys:
2266
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2267
+ - action.left_gripper_pos
2268
+ - action.right_joint_pos
2269
+ - action.right_gripper_pos
2270
+ language:
2271
+ _target_: groot.vla.data.dataset.ModalityConfig
2272
+ delta_indices:
2273
+ - 0
2274
+ modality_keys:
2275
+ - annotation.task
2276
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2277
+ _target_: groot.vla.data.transform.ComposedModalityTransform
2278
+ transforms:
2279
+ - _target_: groot.vla.data.transform.VideoToTensor
2280
+ apply_to:
2281
+ - video.top_camera-images-rgb
2282
+ - video.left_camera-images-rgb
2283
+ - video.right_camera-images-rgb
2284
+ - _target_: groot.vla.data.transform.VideoCrop
2285
+ apply_to:
2286
+ - video.top_camera-images-rgb
2287
+ - video.left_camera-images-rgb
2288
+ - video.right_camera-images-rgb
2289
+ scale: 0.95
2290
+ mode: random
2291
+ - _target_: groot.vla.data.transform.VideoResize
2292
+ apply_to:
2293
+ - video.top_camera-images-rgb
2294
+ - video.left_camera-images-rgb
2295
+ - video.right_camera-images-rgb
2296
+ height: 176
2297
+ width: 320
2298
+ interpolation: linear
2299
+ - _target_: groot.vla.data.transform.VideoColorJitter
2300
+ apply_to:
2301
+ - video.top_camera-images-rgb
2302
+ - video.left_camera-images-rgb
2303
+ - video.right_camera-images-rgb
2304
+ brightness: 0.3
2305
+ contrast: 0.4
2306
+ saturation: 0.5
2307
+ hue: 0.08
2308
+ - _target_: groot.vla.data.transform.VideoToNumpy
2309
+ apply_to:
2310
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2311
+ - video.left_camera-images-rgb
2312
+ - video.right_camera-images-rgb
2313
+ - _target_: groot.vla.data.transform.StateActionToTensor
2314
+ apply_to:
2315
+ - state.left_joint_pos
2316
+ - state.left_gripper_pos
2317
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2318
+ - state.right_gripper_pos
2319
+ - _target_: groot.vla.data.transform.StateActionTransform
2320
+ apply_to:
2321
+ - state.left_joint_pos
2322
+ - state.left_gripper_pos
2323
+ - state.right_joint_pos
2324
+ - state.right_gripper_pos
2325
+ normalization_modes:
2326
+ state.left_joint_pos: q99
2327
+ state.left_gripper_pos: q99
2328
+ state.right_joint_pos: q99
2329
+ state.right_gripper_pos: q99
2330
+ - _target_: groot.vla.data.transform.StateActionToTensor
2331
+ apply_to:
2332
+ - action.left_joint_pos
2333
+ - action.left_gripper_pos
2334
+ - action.right_joint_pos
2335
+ - action.right_gripper_pos
2336
+ - _target_: groot.vla.data.transform.StateActionTransform
2337
+ apply_to:
2338
+ - action.left_joint_pos
2339
+ - action.left_gripper_pos
2340
+ - action.right_joint_pos
2341
+ - action.right_gripper_pos
2342
+ normalization_modes:
2343
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2344
+ action.left_gripper_pos: q99
2345
+ action.right_joint_pos: q99
2346
+ action.right_gripper_pos: q99
2347
+ - _target_: groot.vla.data.transform.ConcatTransform
2348
+ video_concat_order:
2349
+ - video.top_camera-images-rgb
2350
+ - video.left_camera-images-rgb
2351
+ - video.right_camera-images-rgb
2352
+ state_concat_order:
2353
+ - state.left_joint_pos
2354
+ - state.left_gripper_pos
2355
+ - state.right_joint_pos
2356
+ - state.right_gripper_pos
2357
+ action_concat_order:
2358
+ - action.left_joint_pos
2359
+ - action.left_gripper_pos
2360
+ - action.right_joint_pos
2361
+ - action.right_gripper_pos
2362
+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
2363
+ default_instruction: Perform the default behavior.
2364
+ language_dropout_prob: 0.0
2365
+ always_use_default_instruction: false
2366
+ max_state_dim: 64
2367
+ max_action_dim: 32
2368
+ max_length: 512
2369
+ state_horizon: 1
2370
+ action_horizon: 24
2371
+ embodiment_tag_mapping:
2372
+ real_gr1_arms_only: 0
2373
+ real_gr1_arms_only_annotated: 1
2374
+ real_gr1_arms_waist: 2
2375
+ real_gr1_arms_waist_annotated: 3
2376
+ dexmg_gr1_arms_only_inspire: 4
2377
+ dexmg_gr1_arms_only_fourier: 5
2378
+ dexmg_gr1_arms_waist_fourier: 6
2379
+ robocasa_single_arm: 7
2380
+ onex_eve_gripper: 8
2381
+ robocasa_gr1_arms_only_inspire_hands: 9
2382
+ robocasa_gr1_arms_only_fourier_hands: 10
2383
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
2384
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
2385
+ robocasa_panda_omron: 13
2386
+ robocasa_bimanual_panda_parallel_gripper: 15
2387
+ robocasa_bimanual_panda_inspire_hand: 16
2388
+ oxe_droid: 17
2389
+ oxe_fractal: 18
2390
+ oxe_language_table: 19
2391
+ oxe_bridge: 20
2392
+ real_panda_single_arm: 21
2393
+ hot3d_hands_only: 23
2394
+ gr1_unified: 24
2395
+ robocasa_gr1_arms_waist_fourier_hands: 25
2396
+ agibot: 26
2397
+ bimanual_ur3: 26
2398
+ lapa: 27
2399
+ oxe_mutex: 28
2400
+ oxe_roboset: 29
2401
+ oxe_plex: 30
2402
+ dream: 31
2403
+ yam: 32
2404
+ xdof: 22
2405
+ gr1_unified_segmentation: 14
2406
+ language_table_sim: 7
2407
+ gr1_isaac: 0
2408
+ sim_behavior_r1_pro: 31
2409
+ mecka_hands: 27
2410
+ real_r1_pro_sharpa: 28
2411
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
2412
+ modality_configs:
2413
+ bimanual_ur3:
2414
+ video:
2415
+ _target_: groot.vla.data.dataset.ModalityConfig
2416
+ delta_indices:
2417
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2418
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2419
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2420
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2446
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2447
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2448
+ - 31
2449
+ - 32
2450
+ eval_delta_indices:
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+ - 0
2452
+ modality_keys:
2453
+ - video.top_head
2454
+ - video.hand_left
2455
+ - video.hand_right
2456
+ state:
2457
+ _target_: groot.vla.data.dataset.ModalityConfig
2458
+ delta_indices:
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+ - 0
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+ - state.right_joint_pos
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+ - state.right_gripper_pos
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+ _target_: groot.vla.data.dataset.ModalityConfig
2467
+ delta_indices:
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2492
+ modality_keys:
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+ - action.left_joint_pos
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+ - action.left_gripper_pos
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+ - action.right_joint_pos
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+ - action.right_gripper_pos
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+ language:
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+ _target_: groot.vla.data.dataset.ModalityConfig
2499
+ delta_indices:
2500
+ - 0
2501
+ modality_keys:
2502
+ - annotation.task
2503
+ oxe_droid:
2504
+ video:
2505
+ _target_: groot.vla.data.dataset.ModalityConfig
2506
+ delta_indices:
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2536
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2540
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+ - video.exterior_image_1_left
2544
+ - video.exterior_image_2_left
2545
+ - video.wrist_image_left
2546
+ state:
2547
+ _target_: groot.vla.data.dataset.ModalityConfig
2548
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2555
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2574
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2575
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2576
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2578
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2579
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2580
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2899
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2914
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2927
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2929
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2931
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2932
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2935
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2949
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2952
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2955
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2966
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2971
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2975
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2981
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2986
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2993
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3004
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3005
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3007
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3008
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3009
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3010
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3013
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3015
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+ real_gr1_arms_waist_annotated: 3
3017
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3018
+ dexmg_gr1_arms_only_fourier: 5
3019
+ dexmg_gr1_arms_waist_fourier: 6
3020
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3021
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3022
+ robocasa_gr1_arms_only_inspire_hands: 9
3023
+ robocasa_gr1_arms_only_fourier_hands: 10
3024
+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
3025
+ robocasa_gr1_fixed_lower_body_fourier_hands: 12
3026
+ robocasa_panda_omron: 13
3027
+ robocasa_bimanual_panda_parallel_gripper: 15
3028
+ robocasa_bimanual_panda_inspire_hand: 16
3029
+ oxe_droid: 17
3030
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3031
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3032
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3033
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3034
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3035
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3036
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3037
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3038
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3039
+ lapa: 27
3040
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3041
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3042
+ oxe_plex: 30
3043
+ dream: 31
3044
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3045
+ xdof: 22
3046
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3047
+ language_table_sim: 7
3048
+ gr1_isaac: 0
3049
+ sim_behavior_r1_pro: 31
3050
+ mecka_hands: 27
3051
+ real_r1_pro_sharpa: 28
3052
+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
3053
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3055
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3057
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3062
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3067
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3068
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3069
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3072
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3073
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3074
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3075
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3076
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3077
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3079
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3080
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3081
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3083
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3085
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3086
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3091
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3095
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3096
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3097
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3098
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3099
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3101
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3105
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3112
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3114
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3118
+ - action.right_effector_position
3119
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3120
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3121
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3122
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3123
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3125
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3128
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3129
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3130
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3131
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3134
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3135
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3136
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3137
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3138
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3139
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3140
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3144
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3147
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3150
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3151
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3154
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3155
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3158
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+ - _target_: groot.vla.model.dreamzero.transform.dreamzero_cotrain.DreamTransform
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+ default_instruction: Perform the default behavior.
3161
+ language_dropout_prob: 0.0
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+ always_use_default_instruction: false
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+ max_state_dim: 64
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+ robocasa_bimanual_panda_inspire_hand: 16
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+ robocasa_gr1_arms_waist_fourier_hands: 25
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+ tokenizer_path: /root/WAM/checkpoints/umt5-xxl
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+ apply_to:
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+ default_instruction: Perform the default behavior.
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+ robocasa_gr1_fixed_lower_body_inspire_hands: 11
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+ robocasa_panda_omron: 13
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+ robocasa_gr1_arms_waist_fourier_hands: 25
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+ lapa: 27
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+ metadata_versions:
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+ dataset_shard_sampling_rate: 0.1
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+ mixture_dataset_cls: groot.vla.data.dataset.lerobot_sharded.ShardedLeRobotMixtureDataset.from_mixture_spec
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+ single_dataset_cls: groot.vla.data.dataset.lerobot_sharded.ShardedLeRobotSubLangSingleActionChunkDatasetDROID
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+ bimanual_ur3_data_root: /root/WAM/datasets/bimanual-ur3-dreamzero-v2
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+ total_training_steps: 1048576000000
experiment_cfg/metadata.json ADDED
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