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Hello, I am learning your significant repo, I succeeded to train your visual self-model and get the robot_state.json, but I have a problem when I run your command in "Training" part of "To use our pre-trained self-model to train a small network to predict end-effector position", it seems that there's no file named "robot_state_kinematic_val.json", and I'm new to learn Deep Learing, so could you help me how to generate that file?
logs:
(env-visual-selmodeling) $ CUDA_VISIBLE_DEVICES=0 python ../main.py ../configs/state_condition_kinematic/config1.yaml kinematic ./logs_state-condition_new-global-siren-sdf_1/lightning_logs/version_0/checkpoints/
{'coord_system': 'cartesian',
'data_filepath': '../saved_meshes',
'dof': 4,
'epochs': 1000,
'gamma': 0.5,
'if_cuda': True,
'log_dir': 'logs',
'loss_type': 'siren_sdf_kinematic',
'lr': 0.0009,
'lr_schedule': [10000000],
'model_name': 'state-condition-kinematic',
'num_gpus': 1,
'num_workers': 8,
'seed': 1,
'tag': 'new-global-siren-sdf',
'task_batch': 9600,
'test_batch': 4500,
'train_batch': 4500,
'val_batch': 4500}
Global seed set to 1
GPU available: True, used: True
TPU available: False, using: 0 TPU cores
Traceback (most recent call last):
File "../main.py", line 173, in
main_kinematic()
File "../main.py", line 118, in main_kinematic
trainer.fit(model)
File "/data/lwh22/anaconda3/envs/env-visual-selmodeling/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py", line 458, in fit
self.call_setup_hook(model)
File "/data/lwh22/anaconda3/envs/env-visual-selmodeling/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py", line 1066, in call_setup_hook
model.setup(stage_name)
File "/data/lwh22/hust_pj/visual-selfmodeling/models.py", line 204, in setup
pointcloud_folder=self.hparams.data_filepath)
File "/data/lwh22/hust_pj/visual-selfmodeling/dataset.py", line 97, in init
self.robot_state_dict = self.load_robot_state()
File "/data/lwh22/hust_pj/visual-selfmodeling/dataset.py", line 134, in load_robot_state
with open(robot_state_filepath, 'r') as file:
FileNotFoundError: [Errno 2] No such file or directory: '../saved_meshes/robot_state_kinematic_val.json'
The text was updated successfully, but these errors were encountered:
I am facing an issue with executing the following command "CUDA_VISIBLE_DEVICES=0 python ../main.py ../configs/state_condition_kinematic/config1.yaml kinematic ./logs_state-condition_new-global-siren-sdf_1/lightning_logs/version_0/checkpoints/;" as it required robot_state_kinematic_val.json as the following error "FileNotFoundError: [Errno 2] No such file or directory: '../saved_meshes/robot_state_kinematic_val.json'".
The robot_state_kinematic_val.json file is not generated or saved at the Saved_meshes folder. Please can you advise?
Hi, I am not sure but you may need to run the first command to generate "cd scripts;
CUDA_VISIBLE_DEVICES=0 python ../main.py ../configs/state_condition/config1.yaml NA;"
Hello, I am learning your significant repo, I succeeded to train your visual self-model and get the robot_state.json, but I have a problem when I run your command in "Training" part of "To use our pre-trained self-model to train a small network to predict end-effector position", it seems that there's no file named "robot_state_kinematic_val.json", and I'm new to learn Deep Learing, so could you help me how to generate that file?
logs:
(env-visual-selmodeling) $ CUDA_VISIBLE_DEVICES=0 python ../main.py ../configs/state_condition_kinematic/config1.yaml kinematic ./logs_state-condition_new-global-siren-sdf_1/lightning_logs/version_0/checkpoints/
{'coord_system': 'cartesian',
'data_filepath': '../saved_meshes',
'dof': 4,
'epochs': 1000,
'gamma': 0.5,
'if_cuda': True,
'log_dir': 'logs',
'loss_type': 'siren_sdf_kinematic',
'lr': 0.0009,
'lr_schedule': [10000000],
'model_name': 'state-condition-kinematic',
'num_gpus': 1,
'num_workers': 8,
'seed': 1,
'tag': 'new-global-siren-sdf',
'task_batch': 9600,
'test_batch': 4500,
'train_batch': 4500,
'val_batch': 4500}
Global seed set to 1
GPU available: True, used: True
TPU available: False, using: 0 TPU cores
Traceback (most recent call last):
File "../main.py", line 173, in
main_kinematic()
File "../main.py", line 118, in main_kinematic
trainer.fit(model)
File "/data/lwh22/anaconda3/envs/env-visual-selmodeling/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py", line 458, in fit
self.call_setup_hook(model)
File "/data/lwh22/anaconda3/envs/env-visual-selmodeling/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py", line 1066, in call_setup_hook
model.setup(stage_name)
File "/data/lwh22/hust_pj/visual-selfmodeling/models.py", line 204, in setup
pointcloud_folder=self.hparams.data_filepath)
File "/data/lwh22/hust_pj/visual-selfmodeling/dataset.py", line 97, in init
self.robot_state_dict = self.load_robot_state()
File "/data/lwh22/hust_pj/visual-selfmodeling/dataset.py", line 134, in load_robot_state
with open(robot_state_filepath, 'r') as file:
FileNotFoundError: [Errno 2] No such file or directory: '../saved_meshes/robot_state_kinematic_val.json'
The text was updated successfully, but these errors were encountered: