isl-org
AttributeError: 'ConfigDict' object has no attribute 'optimizer'
Traceback (most recent call last):
File "/usr/lib/python3.10/idlelib/run.py", line 578, in runcode
exec(code, self.locals)
File "/home/v3/Desktop/kitti/train1.py", line 12, in
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
My code is;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; #Import torch and the model to use for training import open3d.ml.torch as ml3d from open3d.ml.torch.models import RandLANet from open3d.ml.torch.pipelines import SemanticSegmentation
#Read a dataset by specifying the path. We are also providing the cache directory and training split. dataset = ml3d.datasets.SemanticKITTI(dataset_path='/home/v3/Desktop/kitti/dataset', cache_dir='./logs/cache',training_split=['00', '01', '02', '03', '04', '05', '06', '07', '09', '10']) #Initialize the RandLANet model with three layers. model = RandLANet(dim_input=3) pipeline = SemanticSegmentation(model=model, dataset=dataset, max_epoch=100) #Run the training pipeline.run_train()
\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\
Dataset is : sementicKITTI
Hey, I have the same problem.
Did you find any solution? Form my understanding, the SemanticSegmentation pipeline should be equipped with Adam optimizer by default...
Hey, i get the same error when i use custom dataset using CUSTOM3D. @raviS123-dot you found the solution to your problem. Will you please share
hey @raviS123-dot @RauchLukas @njakuschona @QasimMuhammad
The problem is in this line:
pipeline = SemanticSegmentation(model=model, dataset=dataset, max_epoch=100)
where the input is only dataset, model and max number of epochs, you need to add the pipeline configuration (cfg.pipeline)
use this:
pipeline = SemanticSegmentation(model=model, dataset=dataset, **cfg.pipeline)
this will call all the attributes in cfg_file instead of inserting them manually one by one
you can find the config file here:
"Open3D-ML/ml3d/configs/randlanet_semantickitti.yml"
