logger initialized
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '001_cube',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 110 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d958b51f0>
Added new graph with id 001_cube to memory.
Model for 001_cube:
   Contains 18 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,

001_cube not in memory (['001_cube'])
Adding a new graph to memory.
init object model with id 001_cube
building graph from 17 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d958b50d0>
Added new graph with id 001_cube to memory.
Model for 001_cube:
   Contains 17 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 0, 90,  0]),
 'object': '001_cube',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 'rotation': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 109 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 36 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,
, 'learning_module_0': Model for 001_cube:
   Contains 17 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 17 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 36 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,
, 'learning_module_0': Model for 001_cube:
   Contains 34 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 109 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   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,
, 'learning_module_0': Model for 001_cube:
   Contains 34 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 17 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   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,
, 'learning_module_0': Model for 001_cube:
   Contains 51 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  0, 270,   0]),
 'object': '001_cube',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 'rotation': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 110 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 72 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,
, 'learning_module_0': Model for 001_cube:
   Contains 51 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 17 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 72 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,
, 'learning_module_0': Model for 001_cube:
   Contains 68 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([90,  0,  0]),
 'object': '001_cube',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 'rotation': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 109 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 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,
, 'learning_module_0': Model for 001_cube:
   Contains 68 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 17 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,
, 'learning_module_0': Model for 001_cube:
   Contains 85 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 111 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 18 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   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,
, 'learning_module_0': Model for 001_cube:
   Contains 85 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 17 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   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,
, 'learning_module_0': Model for 001_cube:
   Contains 102 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 45 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 153 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,
, 'learning_module_0': Model for 001_cube:
   Contains 102 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 153 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,
, 'learning_module_0': Model for 001_cube:
   Contains 145 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 197 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,
, 'learning_module_0': Model for 001_cube:
   Contains 145 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 43 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 197 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,
, 'learning_module_0': Model for 001_cube:
   Contains 186 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 123 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 45 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 242 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,
, 'learning_module_0': Model for 001_cube:
   Contains 186 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 242 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,
, 'learning_module_0': Model for 001_cube:
   Contains 228 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 50 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 290 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,
, 'learning_module_0': Model for 001_cube:
   Contains 228 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 49 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 290 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,
, 'learning_module_0': Model for 001_cube:
   Contains 276 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 50 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 340 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,
, 'learning_module_0': Model for 001_cube:
   Contains 276 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 49 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 340 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,
, 'learning_module_0': Model for 001_cube:
   Contains 324 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 45 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 383 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,
, 'learning_module_0': Model for 001_cube:
   Contains 324 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 383 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,
, 'learning_module_0': Model for 001_cube:
   Contains 367 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 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,
, 'learning_module_0': Model for 001_cube:
   Contains 367 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
001_cube already in memory (['001_cube'])
Updating existing graph for 001_cube
adding 43 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   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,
, 'learning_module_0': Model for 001_cube:
   Contains 408 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 001_cube
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 122 observations
Extended graph 001_cube with new points. New model:
{'patch_0': Model for 001_cube:
   Contains 1614 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 43 observations
Extended graph 001_cube with new points. New model:
{'patch_1': Model for 001_cube:
   Contains 469 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,
, 'learning_module_0': Model for 001_cube:
   Contains 408 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 469 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,
, 'learning_module_0': Model for 001_cube:
   Contains 447 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '001_cube',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '006_disk',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 109 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 18 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d958b7fd0>
Added new graph with id 006_disk to memory.
Model for 006_disk:
   Contains 18 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,

006_disk not in memory (['006_disk'])
Adding a new graph to memory.
init object model with id 006_disk
building graph from 17 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d958b7d30>
Added new graph with id 006_disk to memory.
Model for 006_disk:
   Contains 17 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 0, 90,  0]),
 'object': '006_disk',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0.        , 0.70710678, 0.        , 0.70710678]),
 'rotation': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 17 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 12 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 17 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 11 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 28 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 109 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 18 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 28 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 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,
, 'learning_module_0': Model for 006_disk:
   Contains 45 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  0, 270,   0]),
 'object': '006_disk',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([ 0.        ,  0.70710678,  0.        , -0.70710678]),
 'rotation': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 17 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 12 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 45 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 11 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 55 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([90,  0,  0]),
 'object': '006_disk',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0.70710678, 0.        , 0.        , 0.70710678]),
 'rotation': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 1047 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 2 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 55 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 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,
, 'learning_module_0': Model for 006_disk:
   Contains 56 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 1047 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 61 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,
, 'learning_module_0': Model for 006_disk:
   Contains 56 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 1047 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 24 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 56 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 79 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 96 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 107 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,
, 'learning_module_0': Model for 006_disk:
   Contains 79 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 22 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 107 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,
, 'learning_module_0': Model for 006_disk:
   Contains 101 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 103 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 26 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 133 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,
, 'learning_module_0': Model for 006_disk:
   Contains 101 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 25 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 133 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,
, 'learning_module_0': Model for 006_disk:
   Contains 126 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 100 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 24 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 126 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   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,
, 'learning_module_0': Model for 006_disk:
   Contains 149 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 101 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 24 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 179 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,
, 'learning_module_0': Model for 006_disk:
   Contains 149 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 179 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,
, 'learning_module_0': Model for 006_disk:
   Contains 172 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 104 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 26 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 203 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,
, 'learning_module_0': Model for 006_disk:
   Contains 172 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 25 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 203 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,
, 'learning_module_0': Model for 006_disk:
   Contains 197 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 97 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 226 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,
, 'learning_module_0': Model for 006_disk:
   Contains 197 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 22 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 226 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,
, 'learning_module_0': Model for 006_disk:
   Contains 219 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 006_disk
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 101 observations
Extended graph 006_disk with new points. New model:
{'patch_0': Model for 006_disk:
   Contains 1047 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 24 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 249 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,
, 'learning_module_0': Model for 006_disk:
   Contains 219 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
006_disk already in memory (['006_disk'])
Updating existing graph for 006_disk
adding 23 observations
Extended graph 006_disk with new points. New model:
{'patch_1': Model for 006_disk:
   Contains 249 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,
, 'learning_module_0': Model for 006_disk:
   Contains 242 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '006_disk',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '002_cube_tbp_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 117 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d93266d00>
Added new graph with id 002_cube_tbp_horz to memory.
Model for 002_cube_tbp_horz:
   Contains 117 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 36 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928cb3d0>
Added new graph with id 002_cube_tbp_horz to memory.
Model for 002_cube_tbp_horz:
   Contains 36 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,

002_cube_tbp_horz not in memory (['002_cube_tbp_horz'])
Adding a new graph to memory.
init object model with id 002_cube_tbp_horz
building graph from 35 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928cb670>
Added new graph with id 002_cube_tbp_horz to memory.
Model for 002_cube_tbp_horz:
   Contains 35 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 109 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 226 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 18 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 35 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 17 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 52 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 109 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 335 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 18 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 72 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 52 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 17 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 72 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 69 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  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': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 110 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 445 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 18 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 69 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 17 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 86 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 109 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 552 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 18 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 86 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 17 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 103 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 111 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 661 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 18 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 126 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 103 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 17 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 126 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 120 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 780 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 48 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 174 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 120 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 174 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 166 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 901 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 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 166 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 208 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 123 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1024 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 48 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 267 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 208 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 267 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 253 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1146 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 316 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 253 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 50 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 316 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 302 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1265 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 50 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 366 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 302 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 49 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 366 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 350 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1385 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 409 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 350 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 409 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 393 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1504 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 453 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 393 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
002_cube_tbp_horz already in memory (['002_cube_tbp_horz'])
Updating existing graph for 002_cube_tbp_horz
adding 43 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 453 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 434 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 002_cube_tbp_horz
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 122 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_0': Model for 002_cube_tbp_horz:
   Contains 1621 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 43 observations
Extended graph 002_cube_tbp_horz with new points. New model:
{'patch_1': Model for 002_cube_tbp_horz:
   Contains 495 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 434 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 495 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,
, 'learning_module_0': Model for 002_cube_tbp_horz:
   Contains 473 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '002_cube_tbp_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '004_cube_numenta_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 120 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d929ddf70>
Added new graph with id 004_cube_numenta_horz to memory.
Model for 004_cube_numenta_horz:
   Contains 120 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 41 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928c1670>
Added new graph with id 004_cube_numenta_horz to memory.
Model for 004_cube_numenta_horz:
   Contains 41 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,

004_cube_numenta_horz not in memory (['004_cube_numenta_horz'])
Adding a new graph to memory.
init object model with id 004_cube_numenta_horz
building graph from 40 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928c1910>
Added new graph with id 004_cube_numenta_horz to memory.
Model for 004_cube_numenta_horz:
   Contains 40 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 109 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_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---
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 18 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 59 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 40 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 17 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 59 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 57 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 109 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 338 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 18 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 77 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 57 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 17 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 77 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 74 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  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': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 110 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 448 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 18 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 74 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 17 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 91 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 109 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 555 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 18 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 113 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 91 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 17 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 113 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 108 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 111 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 18 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 108 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 17 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 125 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 782 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 176 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 125 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 176 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 167 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 903 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 221 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 167 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 221 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 209 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 123 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1026 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 266 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 209 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 266 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 251 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1148 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 51 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 315 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 251 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 50 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 315 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 300 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1267 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 50 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 365 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 300 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
004_cube_numenta_horz already in memory (['004_cube_numenta_horz'])
Updating existing graph for 004_cube_numenta_horz
adding 49 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_1': Model for 004_cube_numenta_horz:
   Contains 365 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 348 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1387 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 408 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 348 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 408 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 391 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1506 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 452 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 391 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 452 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 432 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 004_cube_numenta_horz
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 122 observations
Extended graph 004_cube_numenta_horz with new points. New model:
{'patch_0': Model for 004_cube_numenta_horz:
   Contains 1623 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 494 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 432 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 494 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,
, 'learning_module_0': Model for 004_cube_numenta_horz:
   Contains 471 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '004_cube_numenta_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '007_disk_tbp_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 121 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d9297c160>
Added new graph with id 007_disk_tbp_horz to memory.
Model for 007_disk_tbp_horz:
   Contains 121 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 37 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928c65e0>
Added new graph with id 007_disk_tbp_horz to memory.
Model for 007_disk_tbp_horz:
   Contains 37 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,

007_disk_tbp_horz not in memory (['007_disk_tbp_horz'])
Adding a new graph to memory.
init object model with id 007_disk_tbp_horz
building graph from 36 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d928c6880>
Added new graph with id 007_disk_tbp_horz to memory.
Model for 007_disk_tbp_horz:
   Contains 36 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 17 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 138 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 12 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 49 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 36 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['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_1': Model for 007_disk_tbp_horz:
   Contains 49 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 47 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 109 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 247 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 18 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 66 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 47 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 66 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 64 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  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': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 17 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 264 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 12 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 77 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 64 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['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_1': Model for 007_disk_tbp_horz:
   Contains 77 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 74 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 276 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 2 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 79 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 74 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 79 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 75 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 288 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 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 75 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 390 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 35 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 115 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 75 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 115 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 107 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 101 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 486 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 142 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 107 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 28 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 142 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 135 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 106 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 588 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 175 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 135 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 175 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 167 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 105 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 686 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 38 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 209 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 167 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 37 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 209 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 204 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 101 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 787 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 24 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 233 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 204 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 23 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 233 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 227 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 104 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 887 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 26 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 257 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 227 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 25 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 257 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 252 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 97 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 979 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 23 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 280 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 252 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 22 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   Contains 280 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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 274 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 007_disk_tbp_horz
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 101 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_0': Model for 007_disk_tbp_horz:
   Contains 1074 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 24 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 274 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
007_disk_tbp_horz already in memory (['007_disk_tbp_horz'])
Updating existing graph for 007_disk_tbp_horz
adding 23 observations
Extended graph 007_disk_tbp_horz with new points. New model:
{'patch_1': Model for 007_disk_tbp_horz:
   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,
, 'learning_module_0': Model for 007_disk_tbp_horz:
   Contains 297 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '007_disk_tbp_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
loading models
loading 001_cube with features from dict_keys(['patch_0'])
Loaded {'patch_0': Model for 001_cube:
   Contains 1614 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 1047 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 148 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 103 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
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '009_disk_numenta_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 120 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d92972fa0>
Added new graph with id 009_disk_numenta_horz to memory.
Model for 009_disk_numenta_horz:
   Contains 120 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 41 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d9293d8b0>
Added new graph with id 009_disk_numenta_horz to memory.
Model for 009_disk_numenta_horz:
   Contains 41 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,

009_disk_numenta_horz not in memory (['009_disk_numenta_horz'])
Adding a new graph to memory.
init object model with id 009_disk_numenta_horz
building graph from 40 observations
built graph <tbp.monty.frameworks.utils.object_model_utils.NumpyGraph object at 0x7a1d9293db50>
Added new graph with id 009_disk_numenta_horz to memory.
Model for 009_disk_numenta_horz:
   Contains 39 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,



Going from 0 to 1 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.707106781186548, 0, 0.707106781186547, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 17 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 137 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 12 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 39 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['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_1': Model for 009_disk_numenta_horz:
   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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 50 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 1 to 2 of 14
New primary target: {'euler_rotation': array([  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': quaternion(6.12323399573677e-17, 0, 1, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 109 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 246 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 18 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 50 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 67 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 2 to 3 of 14
New primary target: {'euler_rotation': array([  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': quaternion(-0.707106781186547, 0, 0.707106781186548, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 17 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 263 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 12 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 81 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 67 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['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_1': Model for 009_disk_numenta_horz:
   Contains 81 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 77 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 3 to 4 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.707106781186548, 0.707106781186547, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 275 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 2 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 77 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 78 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 4 to 5 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(4.32978028117747e-17, 4.32978028117747e-17, 0.707106781186548, -0.707106781186547),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 287 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 78 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 5 to 6 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, 0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 102 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 389 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 28 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 111 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 78 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 27 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 111 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 105 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 6 to 7 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.881119570605362, 0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 102 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 486 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 140 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 105 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 30 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 140 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 135 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 7 to 8 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.881119570605362, -0.277815933469441, 0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 104 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 587 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 171 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 135 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 30 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 171 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 163 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 8 to 9 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.881119570605362, -0.277815933469441, -0.364971676217099, -0.115075127486384),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 105 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 685 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 36 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 204 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 163 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 35 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 204 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 198 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 9 to 10 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(0.364971676217099, 0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 101 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 786 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 24 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 228 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 198 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 23 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 228 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 221 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 10 to 11 of 14
New primary target: {'euler_rotation': array([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': quaternion(-0.364971676217099, 0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 104 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 886 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 252 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 221 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
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 252 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 246 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 11 to 12 of 14
New primary target: {'euler_rotation': array([ 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': quaternion(-0.364971676217099, -0.115075127486384, 0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 978 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 23 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 275 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 246 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 22 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 275 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 268 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 12 to 13 of 14
New primary target: {'euler_rotation': array([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': quaternion(0.364971676217099, -0.115075127486384, -0.881119570605362, -0.277815933469441),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
Running a simulation to model object: 009_disk_numenta_horz
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 101 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_0': Model for 009_disk_numenta_horz:
   Contains 1073 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 24 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 298 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 268 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}
009_disk_numenta_horz already in memory (['009_disk_numenta_horz'])
Updating existing graph for 009_disk_numenta_horz
adding 23 observations
Extended graph 009_disk_numenta_horz with new points. New model:
{'patch_1': Model for 009_disk_numenta_horz:
   Contains 298 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,
, 'learning_module_0': Model for 009_disk_numenta_horz:
   Contains 291 points in graph.
   Feature grid shape: torch.Size([200, 200, 200, 12])
   Stored features and their indexes:
           pose_vectors - 0:9,
           pose_fully_defined - 9:10,
           on_object - 10:11,
           object_id - 11:12,
}


Going from 13 to 0 of 14
New primary target: {'euler_rotation': array([0, 0, 0]),
 'object': '009_disk_numenta_horz',
 'position': [0.0, 1.5, 0.0],
 'quat_rotation': array([0., 0., 0., 1.]),
 'rotation': quaternion(1, 0, 0, 0),
 'scale': [1.0, 1.0, 1.0],
 'semantic_id': 1}
saving model to /home/rmounir/tbp/results/monty/pretrained_models/pretrained_ycb_v11/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
