Description
Checklist
- I have searched for similar issues.
- I have tested with the latest development wheel.
- I have checked the release documentation and the latest documentation (for
mainbranch).
My Question
I am getting an error of "
AttributeError: 'ConfigDict' object has no attribute 'ckpt_path'" for the last line of the code. Here is my code: import open3d.ml as _ml3d
import open3d.ml.torch as ml3d # or open3d.ml.tf as ml3d
framework = "torch" # or tf
cfg_file = "/content/Open3D-ML/ml3d/configs/pvcnn_s3dis.yml"
cfg = _ml3d.utils.Config.load_from_file(cfg_file)
fetch the classes by the name
Pipeline = _ml3d.utils.get_module("pipeline", cfg.pipeline.name, framework)
Model = _ml3d.utils.get_module("model", cfg.model.name, framework)
Dataset = _ml3d.utils.get_module("dataset", cfg.dataset.name)
use the arguments in the config file to construct the instances
cfg.dataset['dataset_path'] = "/content/drive/MyDrive/S3DIS/Stanford3dDataset_v1.2_Aligned_Version-sample"
dataset = Dataset(cfg.dataset.pop('dataset_path', None), **cfg.dataset)
model = Model(**cfg.model)
pipeline = Pipeline(model, dataset, **cfg.pipeline)
import open3d.ml.torch as ml3d
from open3d.ml.torch.models import PVCNN
from open3d.ml.torch.pipelines import SemanticSegmentation
use a cache for storing the results of the preprocessing (default path is './logs/cache')
dataset = ml3d.datasets.S3DIS(dataset_path='/content/drive/MyDrive/S3DIS/Stanford3dDataset_v1.2_Aligned_Version-sample',ckpt_path="/content/drive/MyDrive/S3DIS/checkpoint", use_cache=True )
create the model with random initialization.
model = PVCNN()
pipeline = SemanticSegmentation(model=model, dataset=dataset, **cfg.pipeline)
prints training progress in the console.
pipeline.run_train()