logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930abb0>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d5928f3d0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d5928f430>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube', '001_cube'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592fe130>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592e56a0>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592dd3a0>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_001_cube/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'sewcltuv', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_001_cube', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 98 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube not in memory ([])
Adding a new graph to memory.
init object model with id 001_cube
building graph from 15 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d5932cdc0>
Added new graph with id 001_cube to memory.
Model for 001_cube:
   Contains 15 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 99 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 15 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 30 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 98 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 15 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 45 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 98 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 15 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 60 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 98 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 15 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 75 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 98 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 15 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 90 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 115 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 41 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 131 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 115 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 42 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 173 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 47 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 219 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 44 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 261 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 44 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 303 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 47 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 349 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 42 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 391 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 001_cube
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---
001_cube already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 001_cube
adding 114 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 40 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 431 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '001_cube',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_001_cube/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930ac70>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d5928fd30>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d5928fd90>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk', '006_disk'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592fc790>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592df580>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592dfa60>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_006_disk/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'xf3k59ur', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_006_disk', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 99 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk not in memory ([])
Adding a new graph to memory.
init object model with id 006_disk
building graph from 16 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d59321cd0>
Added new graph with id 006_disk to memory.
Model for 006_disk:
   Contains 16 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 15 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 7 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 23 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 99 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 39 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 15 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 13 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 52 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 12 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 1 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 53 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 11 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 1 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 54 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 94 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 70 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 90 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 86 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 93 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 17 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 103 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 91 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 119 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 91 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 135 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 93 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 17 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 152 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 90 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 168 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 006_disk
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---
006_disk already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Updating existing graph for 006_disk
adding 94 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 16 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 184 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '006_disk',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_006_disk/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930adf0>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d5928ff10>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d5928ff70>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz', '002_cube_tbp_horz'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592fc970>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592df700>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592dfbe0>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_002_cube_tbp_horz/pretrained'), 'resume_wandb_run': False, 'wandb_id': '9k3zfkpm', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_002_cube_tbp_horz', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz not in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Adding a new graph to memory.
init object model with id 002_cube_tbp_horz
building graph from 112 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d576148b0>
Added new graph with id 002_cube_tbp_horz to memory.
Model for 002_cube_tbp_horz:
   Contains 112 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,


---Updating memory of learning_module_1---
002_cube_tbp_horz not in memory ([])
Adding a new graph to memory.
init object model with id 002_cube_tbp_horz
building graph from 50 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d57614ee0>
Added new graph with id 002_cube_tbp_horz to memory.
Model for 002_cube_tbp_horz:
   Contains 50 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 99 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 204 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 15 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 65 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 98 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 295 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 15 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 80 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 98 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 379 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 15 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 95 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 98 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 465 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 15 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 110 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 98 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 551 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 15 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 125 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 115 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 664 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 45 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 170 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 115 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 775 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 42 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 212 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 884 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 51 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 262 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 992 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 45 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 305 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1102 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 44 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 347 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1207 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 47 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 393 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1318 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 42 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 435 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 002_cube_tbp_horz
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---
002_cube_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 114 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1425 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 40 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 475 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '002_cube_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_002_cube_tbp_horz/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930ad30>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d5928fe20>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d5928fe80>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz', '004_cube_numenta_horz'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592fc880>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592e0640>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592e0b20>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_004_cube_numenta_horz/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'ca2qa9q2', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_004_cube_numenta_horz', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz not in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Adding a new graph to memory.
init object model with id 004_cube_numenta_horz
building graph from 112 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d57614760>
Added new graph with id 004_cube_numenta_horz to memory.
Model for 004_cube_numenta_horz:
   Contains 112 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,


---Updating memory of learning_module_1---
004_cube_numenta_horz not in memory ([])
Adding a new graph to memory.
init object model with id 004_cube_numenta_horz
building graph from 48 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d57614d90>
Added new graph with id 004_cube_numenta_horz to memory.
Model for 004_cube_numenta_horz:
   Contains 48 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 99 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 204 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 15 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 63 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 98 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 295 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 15 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 78 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 98 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 379 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 15 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 93 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 98 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 465 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 15 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 108 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 98 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 551 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 15 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 123 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 115 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 664 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 41 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 164 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 115 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 775 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 43 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 207 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 884 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 48 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 254 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 992 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 45 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 297 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1102 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 44 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 339 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1207 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 47 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 385 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1318 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 42 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 427 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 004_cube_numenta_horz
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---
004_cube_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 114 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1425 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 40 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 467 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '004_cube_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_004_cube_numenta_horz/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930aeb0>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d5928efa0>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d5928ef40>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz', '007_disk_tbp_horz'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592f4fd0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592e07c0>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592e0ca0>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_007_disk_tbp_horz/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'pybv3xps', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_007_disk_tbp_horz', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz not in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Adding a new graph to memory.
init object model with id 007_disk_tbp_horz
building graph from 115 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d57614b20>
Added new graph with id 007_disk_tbp_horz to memory.
Model for 007_disk_tbp_horz:
   Contains 115 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,


---Updating memory of learning_module_1---
007_disk_tbp_horz not in memory ([])
Adding a new graph to memory.
init object model with id 007_disk_tbp_horz
building graph from 51 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d5763a040>
Added new graph with id 007_disk_tbp_horz to memory.
Model for 007_disk_tbp_horz:
   Contains 51 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 15 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 130 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 7 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 58 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 99 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 229 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 16 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 74 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 15 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 244 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 13 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 87 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 12 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 256 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 1 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 88 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 11 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 267 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 1 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 89 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 102 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 368 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 34 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 122 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 96 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 461 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 29 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 151 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 102 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 550 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 34 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 182 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 96 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 635 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 33 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 213 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 91 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 725 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 16 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 229 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 93 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 815 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 17 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 246 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 90 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 897 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 16 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 262 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 007_disk_tbp_horz
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---
007_disk_tbp_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 94 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 984 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 16 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 278 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '007_disk_tbp_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_007_disk_tbp_horz/pretrained
logger initialized
{'do_eval': False, 'do_train': True, 'monty_config': {'monty_class': <class 'tbp.monty.frameworks.models.evidence_matching.model.MontyForEvidenceGraphMatching'>, 'monty_args': {'num_exploratory_steps': 1000, 'min_eval_steps': 3, 'min_train_steps': 3, 'max_total_steps': 2500}, 'motor_system_config': <tbp.monty.frameworks.models.motor_system.MotorSystem object at 0x7d1d5930af70>, 'learning_module_configs': {'learning_module_0': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_0': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}}, 'feature_weights': {}, 'max_graph_size': 0.3, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000, 'object_evidence_threshold': 20}}, 'learning_module_1': {'learning_module_class': <class 'tbp.monty.frameworks.models.evidence_matching.learning_module.EvidenceGraphLM'>, 'learning_module_args': {'max_match_distance': 0.001, 'tolerances': {'patch_1': {'hsv': array([0.1, 1. , 1. ]), 'principal_curvatures_log': array([1., 1.])}, 'learning_module_0': {'object_id': 1}}, 'feature_weights': {'learning_module_0': {'object_id': 1}}, 'max_graph_size': 0.4, 'num_model_voxels_per_dim': 200, 'max_nodes_per_graph': 2000}}}, 'sensor_module_configs': {'sensor_module_0': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_0', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'min_depth', 'mean_depth', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 20, 'hsv': [0.1, 0.1, 0.1], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [2, 2], 'distance': 0.01}, 'save_raw_obs': True}}, 'sensor_module_1': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.CameraSM'>, 'sensor_module_args': {'sensor_module_id': 'patch_1', 'features': ['pose_vectors', 'pose_fully_defined', 'on_object', 'object_coverage', 'hsv', 'principal_curvatures_log'], 'delta_thresholds': {'on_object': 0, 'n_steps': 100, 'hsv': [0.2, 0.2, 0.2], 'pose_vectors': [0.7853981633974483, 6.283185307179586, 6.283185307179586], 'principal_curvatures_log': [4, 4], 'distance': 0.05}, 'save_raw_obs': True}}, 'sensor_module_2': {'sensor_module_class': <class 'tbp.monty.frameworks.models.sensor_modules.Probe'>, 'sensor_module_args': {'sensor_module_id': 'view_finder', 'save_raw_obs': True}}}, 'sm_to_agent_dict': {'patch_0': 'agent_id_0', 'patch_1': 'agent_id_0', 'view_finder': 'agent_id_0'}, 'sm_to_lm_matrix': [[0], [1]], '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/rmounir/tbp/data/habitat/objects/compositional_objects', 'agents': {'agent_args': {'agent_id': 'agent_id_0', 'sensor_ids': ['patch_0', 'patch_1', 'view_finder'], 'height': 0.0, 'position': [0.0, 1.5, 0.2], 'resolutions': [[64, 64], [64, 64], [64, 64]], 'positions': [[0.0, 0.0, 0.0], [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], [1.0, 0.0, 0.0, 0.0]], 'semantics': [False, False, False], 'zooms': [10.0, 5.0, 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 0x7d1d59294130>, <tbp.monty.frameworks.environment_utils.transforms.DepthTo3DLocations object at 0x7d1d59294190>]}, 'train_env_interface_args': {'parent_to_child_mapping': None, 'object_names': ['009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz', '009_disk_numenta_horz'], 'object_init_sampler': <tbp.monty.frameworks.environments.object_init_samplers.Predefined object at 0x7d1d592fcaf0>, 'positioning_procedures': [<tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592df880>, <tbp.monty.frameworks.environments.positioning_procedures.GetGoodViewFactory object at 0x7d1d592dfd60>]}, 'train_env_interface_class': <class 'tbp.monty.frameworks.environments.embodied_data.EnvironmentInterfacePerObject'>, '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/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_009_disk_numenta_horz/pretrained'), 'resume_wandb_run': False, 'wandb_id': 'ergqc219', 'wandb_group': 'debugging', 'run_name': 'supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_009_disk_numenta_horz', 'log_parallel_wandb': False}, 'show_sensor_output': False, 'max_train_steps': 1000, 'max_eval_steps': 500, 'max_total_steps': 6000, 'n_train_epochs': 1, 'n_eval_epochs': 3, 'model_name_or_path': '/home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_logos_after_flat_objects/pretrained/', 'min_lms_match': 1, 'seed': 42, 'supervised_lm_ids': 'all'}
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1411 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 006_disk with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 006_disk:
   Contains 949 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 021_logo_tbp with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 021_logo_tbp:
   Contains 468 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading 022_logo_numenta with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 022_logo_numenta:
   Contains 377 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
} for patch_0
loading models
running train epoch 0
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz not in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta'])
Adding a new graph to memory.
init object model with id 009_disk_numenta_horz
building graph from 115 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d57614b50>
Added new graph with id 009_disk_numenta_horz to memory.
Model for 009_disk_numenta_horz:
   Contains 115 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,


---Updating memory of learning_module_1---
009_disk_numenta_horz not in memory ([])
Adding a new graph to memory.
init object model with id 009_disk_numenta_horz
building graph from 47 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7d1d5761b100>
Added new graph with id 009_disk_numenta_horz to memory.
Model for 009_disk_numenta_horz:
   Contains 47 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': [0, 90, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 15 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 130 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 7 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 54 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': [0, 180, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.000000e+00, 1.000000e+00, 0.000000e+00, 6.123234e-17]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 99 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 229 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 16 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 70 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': [0, 270, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 15 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 244 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 13 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 83 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': [90, 0, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 12 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 256 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 1 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 84 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': [90, 180, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 4.32978028e-17,  7.07106781e-01, -7.07106781e-01,  4.32978028e-17]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 11 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 267 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 1 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 85 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': [35, 45, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593,  0.36497168, -0.11507513,  0.88111957]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 97 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 363 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 25 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 109 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': [325, 45, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.27781593, -0.36497168, -0.11507513, -0.88111957]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 96 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 456 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 26 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 132 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': [35, 315, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593,  0.36497168, -0.11507513, -0.88111957]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 98 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 542 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 25 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 155 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': [325, 315, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.27781593, -0.36497168, -0.11507513,  0.88111957]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 97 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 628 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 31 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 186 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': [35, 135, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513,  0.88111957, -0.27781593,  0.36497168]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 91 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 718 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 16 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 202 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': [325, 135, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([ 0.11507513, -0.88111957, -0.27781593, -0.36497168]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 93 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 808 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 17 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 219 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': [35, 225, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513,  0.88111957, -0.27781593, -0.36497168]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 90 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 890 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 16 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 235 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': [325, 225, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([-0.11507513, -0.88111957, -0.27781593,  0.36497168]),
 '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: 009_disk_numenta_horz
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---
009_disk_numenta_horz already in memory (['001_cube', '006_disk', '021_logo_tbp', '022_logo_numenta', '009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 94 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 977 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 19])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           min_depth - 12:13,
           mean_depth - 13:14,
           hsv - 14:17,
           principal_curvatures_log - 17:19,
}

---Updating memory of learning_module_1---
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 16 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 251 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 17])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_coverage - 11:12,
           hsv - 12:15,
           principal_curvatures_log - 15:17,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': [0, 0, 0],
 'object': '009_disk_numenta_horz',
 'position': (0.0, 1.5, 0.0),
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': (1.0, 0.0, 0.0, 0.0),
 'scale': (1.0, 1.0, 1.0),
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/my_trained_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models/supervised_pre_training_objects_with_logos_lvl1_monolithic_models-parallel_train_episode_009_disk_numenta_horz/pretrained
