logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fa87d90>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9faf65b0>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa8faf0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fa6ca60>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f24c0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f2520>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug', 'mug'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa026d0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f999c10>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f999b50>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mug/pretrained'), 'resume_wandb_run': False, 'wandb_id': '8bjymvla', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mug', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug not in memory ([])
Adding a new graph to memory.
init object model with id mug
built graph Data(
  x=[89, 18],
  pos=[89, 3],
  norm=[89, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 979],
  edge_attr=[979, 3]
)
Added new graph with id mug to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[177, 18],
  pos=[177, 3],
  norm=[177, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1947],
  edge_attr=[1947, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[265, 18],
  pos=[265, 3],
  norm=[265, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2915],
  edge_attr=[2915, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[322, 18],
  pos=[322, 3],
  norm=[322, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3542],
  edge_attr=[3542, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[393, 18],
  pos=[393, 3],
  norm=[393, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4323],
  edge_attr=[4323, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[457, 18],
  pos=[457, 3],
  norm=[457, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5027],
  edge_attr=[5027, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[537, 18],
  pos=[537, 3],
  norm=[537, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5907],
  edge_attr=[5907, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[616, 18],
  pos=[616, 3],
  norm=[616, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6776],
  edge_attr=[6776, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[664, 18],
  pos=[664, 3],
  norm=[664, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7304],
  edge_attr=[7304, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[735, 18],
  pos=[735, 3],
  norm=[735, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8085],
  edge_attr=[8085, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[809, 18],
  pos=[809, 3],
  norm=[809, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8899],
  edge_attr=[8899, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[882, 18],
  pos=[882, 3],
  norm=[882, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9702],
  edge_attr=[9702, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[950, 18],
  pos=[950, 3],
  norm=[950, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10450],
  edge_attr=[10450, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mug
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mug already in memory (['mug'])
Updating existing graph for mug
building graph
Extended graph mug with new points. New model:
Data(
  x=[1022, 18],
  pos=[1022, 3],
  norm=[1022, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 11242],
  edge_attr=[11242, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'mug',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mug/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fa88e50>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa88a60>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa5cb20>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9faf7d60>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f3730>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f3790>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl', 'bowl'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa02940>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f99be80>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f99bdc0>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_bowl/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'rx5pqbud', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_bowl', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl not in memory ([])
Adding a new graph to memory.
init object model with id bowl
built graph Data(
  x=[80, 18],
  pos=[80, 3],
  norm=[80, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 880],
  edge_attr=[880, 3]
)
Added new graph with id bowl to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[159, 18],
  pos=[159, 3],
  norm=[159, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1749],
  edge_attr=[1749, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[243, 18],
  pos=[243, 3],
  norm=[243, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2673],
  edge_attr=[2673, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[327, 18],
  pos=[327, 3],
  norm=[327, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3597],
  edge_attr=[3597, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[417, 18],
  pos=[417, 3],
  norm=[417, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4587],
  edge_attr=[4587, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[488, 18],
  pos=[488, 3],
  norm=[488, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5368],
  edge_attr=[5368, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[578, 18],
  pos=[578, 3],
  norm=[578, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6358],
  edge_attr=[6358, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[669, 18],
  pos=[669, 3],
  norm=[669, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7359],
  edge_attr=[7359, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[758, 18],
  pos=[758, 3],
  norm=[758, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8338],
  edge_attr=[8338, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[843, 18],
  pos=[843, 3],
  norm=[843, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9273],
  edge_attr=[9273, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[922, 18],
  pos=[922, 3],
  norm=[922, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10142],
  edge_attr=[10142, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[1006, 18],
  pos=[1006, 3],
  norm=[1006, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 11066],
  edge_attr=[11066, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[1091, 18],
  pos=[1091, 3],
  norm=[1091, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 12001],
  edge_attr=[12001, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: bowl
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
bowl already in memory (['bowl'])
Updating existing graph for bowl
building graph
Extended graph bowl with new points. New model:
Data(
  x=[1182, 18],
  pos=[1182, 3],
  norm=[1182, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 13002],
  edge_attr=[13002, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'bowl',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_bowl/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fa88f10>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa88a90>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa5dbe0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9faf76d0>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f27f0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f2850>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can', 'potted_meat_can'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa02a00>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f99bf40>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f99be80>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_potted_meat_can/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'nav036f4', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_potted_meat_can', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can not in memory ([])
Adding a new graph to memory.
init object model with id potted_meat_can
built graph Data(
  x=[81, 18],
  pos=[81, 3],
  norm=[81, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 891],
  edge_attr=[891, 3]
)
Added new graph with id potted_meat_can to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[150, 18],
  pos=[150, 3],
  norm=[150, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1650],
  edge_attr=[1650, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[228, 18],
  pos=[228, 3],
  norm=[228, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2508],
  edge_attr=[2508, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[297, 18],
  pos=[297, 3],
  norm=[297, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3267],
  edge_attr=[3267, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[363, 18],
  pos=[363, 3],
  norm=[363, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3993],
  edge_attr=[3993, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[425, 18],
  pos=[425, 3],
  norm=[425, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4675],
  edge_attr=[4675, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[489, 18],
  pos=[489, 3],
  norm=[489, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5379],
  edge_attr=[5379, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[547, 18],
  pos=[547, 3],
  norm=[547, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6017],
  edge_attr=[6017, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[606, 18],
  pos=[606, 3],
  norm=[606, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6666],
  edge_attr=[6666, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[672, 18],
  pos=[672, 3],
  norm=[672, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7392],
  edge_attr=[7392, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[738, 18],
  pos=[738, 3],
  norm=[738, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8118],
  edge_attr=[8118, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[791, 18],
  pos=[791, 3],
  norm=[791, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8701],
  edge_attr=[8701, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[861, 18],
  pos=[861, 3],
  norm=[861, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9471],
  edge_attr=[9471, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: potted_meat_can
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
potted_meat_can already in memory (['potted_meat_can'])
Updating existing graph for potted_meat_can
building graph
Extended graph potted_meat_can with new points. New model:
Data(
  x=[918, 18],
  pos=[918, 3],
  norm=[918, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10098],
  edge_attr=[10098, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'potted_meat_can',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_potted_meat_can/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fa88fd0>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa88a60>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa5dca0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fae6070>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f2ca0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f2d00>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon', 'spoon'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa030a0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1e50>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1d90>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_spoon/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'sat7l92q', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_spoon', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon not in memory ([])
Adding a new graph to memory.
init object model with id spoon
built graph Data(
  x=[66, 18],
  pos=[66, 3],
  norm=[66, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 726],
  edge_attr=[726, 3]
)
Added new graph with id spoon to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[142, 18],
  pos=[142, 3],
  norm=[142, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1562],
  edge_attr=[1562, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[212, 18],
  pos=[212, 3],
  norm=[212, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2332],
  edge_attr=[2332, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[266, 18],
  pos=[266, 3],
  norm=[266, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2926],
  edge_attr=[2926, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[331, 18],
  pos=[331, 3],
  norm=[331, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3641],
  edge_attr=[3641, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[389, 18],
  pos=[389, 3],
  norm=[389, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4279],
  edge_attr=[4279, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[463, 18],
  pos=[463, 3],
  norm=[463, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5093],
  edge_attr=[5093, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[525, 18],
  pos=[525, 3],
  norm=[525, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5775],
  edge_attr=[5775, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[593, 18],
  pos=[593, 3],
  norm=[593, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6523],
  edge_attr=[6523, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[639, 18],
  pos=[639, 3],
  norm=[639, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7029],
  edge_attr=[7029, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[718, 18],
  pos=[718, 3],
  norm=[718, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7898],
  edge_attr=[7898, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[786, 18],
  pos=[786, 3],
  norm=[786, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8646],
  edge_attr=[8646, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[840, 18],
  pos=[840, 3],
  norm=[840, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9240],
  edge_attr=[9240, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: spoon
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
spoon already in memory (['spoon'])
Updating existing graph for spoon
building graph
Extended graph spoon with new points. New model:
Data(
  x=[899, 18],
  pos=[899, 3],
  norm=[899, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9889],
  edge_attr=[9889, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'spoon',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_spoon/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fa87fa0>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa87b50>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa73d60>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fae5910>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f8730>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f8790>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry', 'strawberry'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9f9f8ee0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a7220>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a7160>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_strawberry/pretrained'), 'resume_wandb_run': False, 'wandb_id': '0ch01c1o', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_strawberry', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry not in memory ([])
Adding a new graph to memory.
init object model with id strawberry
built graph Data(
  x=[59, 18],
  pos=[59, 3],
  norm=[59, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 649],
  edge_attr=[649, 3]
)
Added new graph with id strawberry to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[119, 18],
  pos=[119, 3],
  norm=[119, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1309],
  edge_attr=[1309, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[187, 18],
  pos=[187, 3],
  norm=[187, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2057],
  edge_attr=[2057, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[252, 18],
  pos=[252, 3],
  norm=[252, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2772],
  edge_attr=[2772, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[312, 18],
  pos=[312, 3],
  norm=[312, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3432],
  edge_attr=[3432, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[370, 18],
  pos=[370, 3],
  norm=[370, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4070],
  edge_attr=[4070, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[420, 18],
  pos=[420, 3],
  norm=[420, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4620],
  edge_attr=[4620, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[470, 18],
  pos=[470, 3],
  norm=[470, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5170],
  edge_attr=[5170, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[530, 18],
  pos=[530, 3],
  norm=[530, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5830],
  edge_attr=[5830, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[594, 18],
  pos=[594, 3],
  norm=[594, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6534],
  edge_attr=[6534, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[661, 18],
  pos=[661, 3],
  norm=[661, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7271],
  edge_attr=[7271, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[706, 18],
  pos=[706, 3],
  norm=[706, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7766],
  edge_attr=[7766, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[761, 18],
  pos=[761, 3],
  norm=[761, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8371],
  edge_attr=[8371, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: strawberry
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
strawberry already in memory (['strawberry'])
Updating existing graph for strawberry
building graph
Extended graph strawberry with new points. New model:
Data(
  x=[812, 18],
  pos=[812, 3],
  norm=[812, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8932],
  edge_attr=[8932, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'strawberry',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_strawberry/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9faf8190>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa87c10>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa73e20>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fae50a0>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f3be0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f3c40>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle', 'mustard_bottle'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa03fa0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a2d90>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a2cd0>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mustard_bottle/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'pcd0frb3', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mustard_bottle', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle not in memory ([])
Adding a new graph to memory.
init object model with id mustard_bottle
built graph Data(
  x=[92, 18],
  pos=[92, 3],
  norm=[92, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1012],
  edge_attr=[1012, 3]
)
Added new graph with id mustard_bottle to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[187, 18],
  pos=[187, 3],
  norm=[187, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2057],
  edge_attr=[2057, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[282, 18],
  pos=[282, 3],
  norm=[282, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3102],
  edge_attr=[3102, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[376, 18],
  pos=[376, 3],
  norm=[376, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4136],
  edge_attr=[4136, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[450, 18],
  pos=[450, 3],
  norm=[450, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4950],
  edge_attr=[4950, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[535, 18],
  pos=[535, 3],
  norm=[535, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5885],
  edge_attr=[5885, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[623, 18],
  pos=[623, 3],
  norm=[623, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6853],
  edge_attr=[6853, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[715, 18],
  pos=[715, 3],
  norm=[715, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7865],
  edge_attr=[7865, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[808, 18],
  pos=[808, 3],
  norm=[808, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8888],
  edge_attr=[8888, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[901, 18],
  pos=[901, 3],
  norm=[901, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9911],
  edge_attr=[9911, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[997, 18],
  pos=[997, 3],
  norm=[997, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10967],
  edge_attr=[10967, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[1084, 18],
  pos=[1084, 3],
  norm=[1084, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 11924],
  edge_attr=[11924, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[1172, 18],
  pos=[1172, 3],
  norm=[1172, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 12892],
  edge_attr=[12892, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: mustard_bottle
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
mustard_bottle already in memory (['mustard_bottle'])
Updating existing graph for mustard_bottle
building graph
Extended graph mustard_bottle with new points. New model:
Data(
  x=[1253, 18],
  pos=[1253, 3],
  norm=[1253, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 13783],
  edge_attr=[13783, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'mustard_bottle',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_mustard_bottle/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fafc250>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa87cd0>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa6fee0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fae5160>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f3ca0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f3d00>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice', 'dice'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa040a0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1e50>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1d90>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_dice/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'n3rs7kji', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_dice', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice not in memory ([])
Adding a new graph to memory.
init object model with id dice
built graph Data(
  x=[39, 18],
  pos=[39, 3],
  norm=[39, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 429],
  edge_attr=[429, 3]
)
Added new graph with id dice to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[83, 18],
  pos=[83, 3],
  norm=[83, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 913],
  edge_attr=[913, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[122, 18],
  pos=[122, 3],
  norm=[122, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1342],
  edge_attr=[1342, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[163, 18],
  pos=[163, 3],
  norm=[163, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1793],
  edge_attr=[1793, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[193, 18],
  pos=[193, 3],
  norm=[193, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2123],
  edge_attr=[2123, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[232, 18],
  pos=[232, 3],
  norm=[232, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2552],
  edge_attr=[2552, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[264, 18],
  pos=[264, 3],
  norm=[264, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2904],
  edge_attr=[2904, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[306, 18],
  pos=[306, 3],
  norm=[306, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3366],
  edge_attr=[3366, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[349, 18],
  pos=[349, 3],
  norm=[349, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3839],
  edge_attr=[3839, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[395, 18],
  pos=[395, 3],
  norm=[395, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4345],
  edge_attr=[4345, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[444, 18],
  pos=[444, 3],
  norm=[444, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4884],
  edge_attr=[4884, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[472, 18],
  pos=[472, 3],
  norm=[472, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5192],
  edge_attr=[5192, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[507, 18],
  pos=[507, 3],
  norm=[507, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5577],
  edge_attr=[5577, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: dice
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
dice already in memory (['dice'])
Updating existing graph for dice
building graph
Extended graph dice with new points. New model:
Data(
  x=[531, 18],
  pos=[531, 3],
  norm=[531, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5841],
  edge_attr=[5841, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'dice',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_dice/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fafc310>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fa87d90>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa5dfa0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fae51f0>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f3d60>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f3dc0>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball', 'golf_ball'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa04160>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1f10>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1e50>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_golf_ball/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'wmv4io29', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_golf_ball', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball not in memory ([])
Adding a new graph to memory.
init object model with id golf_ball
built graph Data(
  x=[59, 18],
  pos=[59, 3],
  norm=[59, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 649],
  edge_attr=[649, 3]
)
Added new graph with id golf_ball to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[123, 18],
  pos=[123, 3],
  norm=[123, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1353],
  edge_attr=[1353, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[194, 18],
  pos=[194, 3],
  norm=[194, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2134],
  edge_attr=[2134, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[262, 18],
  pos=[262, 3],
  norm=[262, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2882],
  edge_attr=[2882, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[324, 18],
  pos=[324, 3],
  norm=[324, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3564],
  edge_attr=[3564, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[393, 18],
  pos=[393, 3],
  norm=[393, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4323],
  edge_attr=[4323, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[460, 18],
  pos=[460, 3],
  norm=[460, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5060],
  edge_attr=[5060, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[516, 18],
  pos=[516, 3],
  norm=[516, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5676],
  edge_attr=[5676, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[580, 18],
  pos=[580, 3],
  norm=[580, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6380],
  edge_attr=[6380, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[632, 18],
  pos=[632, 3],
  norm=[632, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6952],
  edge_attr=[6952, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[686, 18],
  pos=[686, 3],
  norm=[686, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7546],
  edge_attr=[7546, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[737, 18],
  pos=[737, 3],
  norm=[737, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8107],
  edge_attr=[8107, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[798, 18],
  pos=[798, 3],
  norm=[798, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8778],
  edge_attr=[8778, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: golf_ball
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
golf_ball already in memory (['golf_ball'])
Updating existing graph for golf_ball
building graph
Extended graph golf_ball with new points. New model:
Data(
  x=[847, 18],
  pos=[847, 3],
  norm=[847, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9317],
  edge_attr=[9317, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'golf_ball',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_golf_ball/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fafd400>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fafdbb0>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa7bf10>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9faa3610>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f972eb0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f972f10>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo', 'c_lego_duplo'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9f972dc0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a19d0>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a1940>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_c_lego_duplo/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'g2vl9x46', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_c_lego_duplo', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo not in memory ([])
Adding a new graph to memory.
init object model with id c_lego_duplo
built graph Data(
  x=[64, 18],
  pos=[64, 3],
  norm=[64, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 704],
  edge_attr=[704, 3]
)
Added new graph with id c_lego_duplo to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[135, 18],
  pos=[135, 3],
  norm=[135, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1485],
  edge_attr=[1485, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[190, 18],
  pos=[190, 3],
  norm=[190, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2090],
  edge_attr=[2090, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[261, 18],
  pos=[261, 3],
  norm=[261, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2871],
  edge_attr=[2871, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[338, 18],
  pos=[338, 3],
  norm=[338, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3718],
  edge_attr=[3718, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[394, 18],
  pos=[394, 3],
  norm=[394, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4334],
  edge_attr=[4334, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[469, 18],
  pos=[469, 3],
  norm=[469, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5159],
  edge_attr=[5159, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[537, 18],
  pos=[537, 3],
  norm=[537, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5907],
  edge_attr=[5907, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[613, 18],
  pos=[613, 3],
  norm=[613, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6743],
  edge_attr=[6743, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[691, 18],
  pos=[691, 3],
  norm=[691, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7601],
  edge_attr=[7601, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[769, 18],
  pos=[769, 3],
  norm=[769, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8459],
  edge_attr=[8459, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[840, 18],
  pos=[840, 3],
  norm=[840, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9240],
  edge_attr=[9240, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[902, 18],
  pos=[902, 3],
  norm=[902, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9922],
  edge_attr=[9922, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: c_lego_duplo
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
c_lego_duplo already in memory (['c_lego_duplo'])
Updating existing graph for c_lego_duplo
building graph
Extended graph c_lego_duplo with new points. New model:
Data(
  x=[973, 18],
  pos=[973, 3],
  norm=[973, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10703],
  edge_attr=[10703, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'c_lego_duplo',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_c_lego_duplo/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.graph_matching.MontyForGraphMatching'>, 'monty_args': {'num_exploratory_steps': 100, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7a8d9fb094f0>, 'learning_modules': {'learning_module_0': <tbp.monty.frameworks.models.displacement_matching.DisplacementGraphLM object at 0x7a8d9fb09cd0>}, 'sensor_modules': {'sensor_module_0': <tbp.monty.frameworks.models.sensor_modules.CameraSM object at 0x7a8d9fa86ca0>, 'sensor_module_1': <tbp.monty.frameworks.models.salience.sensor_module.SalienceSM object at 0x7a8d9fa683a0>}, 'sm_to_agent_dict': {'patch': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0]], 'lm_to_lm_matrix': None, 'lm_to_lm_vote_matrix': None}, 'environment': {'env_init_args': {'objects': [{'name': 'coneSolid', 'position': [0.0, 1.5, -0.1]}], 'scene_id': None, 'seed': 42, 'data_path': '/home/sknudstrup/tbp/data/habitat/objects/ycb', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [256, 256]], 'positions': [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], 'rotations': [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False], 'zooms': [10.0, 1.0]}, 'agent_type': <class 'tbp.monty.simulators.habitat.agents.MultiSensorAgent'>}}, 'env_init_func': <class 'tbp.monty.simulators.habitat.environment.HabitatEnvironment'>, 'transform': [<tbp.monty.frameworks.environment_utils.transforms.MissingToMaxDepth object at 0x7a8d9f9f7490>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7a8d9f9f74f0>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana', 'banana'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7a8d9fa086a0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a0be0>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7a8d9f9a0b20>]}, 'train_env_interface_class': <class 'tbp.monty.experiment.environment.OneObjectPerEpisodeInterface'>, 'logging': {'monty_log_level': 'SILENT', 'monty_handlers': [], 'wandb_handlers': [], 'python_log_level': 'INFO', 'python_log_to_file': True, 'python_log_to_stderr': True, 'output_dir': PosixPath('/home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_banana/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'f4eek7x9', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_banana', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 100, 'max_eval_steps': 0, 'max_total_steps': 100, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 0
resetting RNG to seed 1060955053
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana not in memory ([])
Adding a new graph to memory.
init object model with id banana
built graph Data(
  x=[88, 18],
  pos=[88, 3],
  norm=[88, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 968],
  edge_attr=[968, 3]
)
Added new graph with id banana to memory.


Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.70710678, 0.        ]),
 'rotation': (0.7071067811865476, 0.0, 0.7071067811865475, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 1
resetting RNG to seed 1260428609
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[172, 18],
  pos=[172, 3],
  norm=[172, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 1892],
  edge_attr=[1892, 3]
)


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([6.123234e-17, 0.000000e+00, 1.000000e+00, 0.000000e+00]),
 'rotation': (6.123233995736766e-17, 0.0, 1.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 2
resetting RNG to seed 3997959863
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[247, 18],
  pos=[247, 3],
  norm=[247, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 2717],
  edge_attr=[2717, 3]
)


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.70710678,  0.        ,  0.70710678,  0.        ]),
 'rotation': (-0.7071067811865475, 0.0, 0.7071067811865476, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 3
resetting RNG to seed 99937259
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[331, 18],
  pos=[331, 3],
  norm=[331, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 3641],
  edge_attr=[3641, 3]
)


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.70710678, 0.        , 0.        ]),
 'rotation': (0.7071067811865476, 0.7071067811865475, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 4
resetting RNG to seed 560786102
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[420, 18],
  pos=[420, 3],
  norm=[420, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 4620],
  edge_attr=[4620, 3]
)


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  4.32978028e-17,  7.07106781e-01, -7.07106781e-01]),
 'rotation': (4.329780281177467e-17,
              4.329780281177466e-17,
              0.7071067811865476,
              -0.7071067811865475),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 5
resetting RNG to seed 1953320932
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[513, 18],
  pos=[513, 3],
  norm=[513, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 5643],
  edge_attr=[5643, 3]
)


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957,  0.27781593,  0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              0.27781593346944056,
              0.36497167621709875,
              -0.11507512748638375),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 6
resetting RNG to seed 2492039860
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[597, 18],
  pos=[597, 3],
  norm=[597, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 6567],
  edge_attr=[6567, 3]
)


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957,  0.27781593, -0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              0.2778159334694408,
              -0.3649716762170987,
              -0.11507512748638384),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 7
resetting RNG to seed 2201955992
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[661, 18],
  pos=[661, 3],
  norm=[661, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 7271],
  edge_attr=[7271, 3]
)


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.88111957, -0.27781593,  0.36497168, -0.11507513]),
 'rotation': (-0.8811195706053617,
              -0.27781593346944056,
              0.36497167621709886,
              -0.11507512748638378),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 8
resetting RNG to seed 306583017
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[735, 18],
  pos=[735, 3],
  norm=[735, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8085],
  edge_attr=[8085, 3]
)


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.88111957, -0.27781593, -0.36497168, -0.11507513]),
 'rotation': (0.8811195706053617,
              -0.2778159334694408,
              -0.3649716762170988,
              -0.11507512748638386),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 9
resetting RNG to seed 583356519
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[809, 18],
  pos=[809, 3],
  norm=[809, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 8899],
  edge_attr=[8899, 3]
)


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168,  0.11507513,  0.88111957, -0.27781593]),
 'rotation': (0.3649716762170988,
              0.11507512748638377,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 10
resetting RNG to seed 1177517334
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[891, 18],
  pos=[891, 3],
  norm=[891, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 9801],
  edge_attr=[9801, 3]
)


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168,  0.11507513, -0.88111957, -0.27781593]),
 'rotation': (-0.36497167621709875,
              0.11507512748638385,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 11
resetting RNG to seed 111915506
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[973, 18],
  pos=[973, 3],
  norm=[973, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 10703],
  edge_attr=[10703, 3]
)


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.36497168, -0.11507513,  0.88111957, -0.27781593]),
 'rotation': (-0.3649716762170987,
              -0.11507512748638374,
              0.8811195706053617,
              -0.27781593346944056),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 12
resetting RNG to seed 1538901097
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[1059, 18],
  pos=[1059, 3],
  norm=[1059, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 11649],
  edge_attr=[11649, 3]
)


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.36497168, -0.11507513, -0.88111957, -0.27781593]),
 'rotation': (0.3649716762170987,
              -0.11507512748638382,
              -0.8811195706053617,
              -0.2778159334694408),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
Running a simulation to model object: banana
running train epoch 0 train episode 13
resetting RNG to seed 678633877
Going into exploratory mode after 0 steps

---Updating memory of learning_module_0---
banana already in memory (['banana'])
Updating existing graph for banana
building graph
Extended graph banana with new points. New model:
Data(
  x=[1125, 18],
  pos=[1125, 3],
  norm=[1125, 3],
  feature_mapping={
    node_ids=[2],
    pose_vectors=[2],
    pose_fully_defined=[2],
    on_object=[2],
    object_coverage=[2],
    hsv=[2],
    principal_curvatures_log=[2]
  },
  edge_index=[2, 12375],
  edge_attr=[12375, 3]
)


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': 'banana',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([1., 0., 0., 0.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/sknudstrup/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_10distinctobj_vocus2_100/supervised_pre_training_10distinctobj_vocus2_100-parallel_train_episode_banana/pretrained
