Error on training Toronto3d On RandlaNet

I am training the toronto3d dataset on the Randlanet model.But on training I am getting this error

**RuntimeError: weight tensor should be defined either for all 8 classes or no classes but got weight tensor of shape: [1, 8]**

I have not changed anything from the code and config file. What Could be the problem
I will attach the config file and training code

**Config**

dataset:
name: Toronto3D
cache_dir: ./logs/cache
class_weights: [41697357, 1745448, 6572572, 19136493, 674897, 897825, 4634634, 374721]
ignored_label_inds:
- 0
num_classes: 8
num_points: 65536
test_files:
- L002.ply
test_result_folder: ./test
train_files:
- L001.ply
- L003.ply
- L004.ply
use_cache: true
val_files:
- L002.ply
steps_per_epoch_train: 100
steps_per_epoch_valid: 10
model:
name: RandLANet
batcher: DefaultBatcher
ckpt_path: ./logs/randlanet_toronto3d_202201071330utc.pth
num_neighbors: 16
num_layers: 5
num_points: 65536
num_classes: 8
ignored_label_inds: [0]
sub_sampling_ratio: [4, 4, 4, 4, 2]
in_channels: 6
dim_features: 8
dim_output: [16, 64, 128, 256, 512]
grid_size: 0.05
augment:
recenter:
dim: [0, 1, 2]
normalize:
points:
method: linear
pipeline:
name: SemanticSegmentation
optimizer:
lr: 0.001
batch_size: 2
main_log_dir: ./logs
max_epoch: 200
save_ckpt_freq: 5
scheduler_gamma: 0.99
test_batch_size: 1
train_sum_dir: train_log
val_batch_size: 2
summary:
record_for: []
max_pts:
use_reference: false
max_outputs: 1

**Training Code**

```
import os
import open3d.ml as _ml3d
import open3d.ml.torch as ml3d

cfg_file = "Config/randlanet_toronto3d.yml"
cfg = _ml3d.utils.Config.load_from_file(cfg_file)

dataset = ml3d.datasets.Toronto3D(dataset_path='./TrainingData/Toronto3d/',**cfg.dataset)
model = ml3d.models.RandLANet(**cfg.model)

pipeline = ml3d.pipelines.SemanticSegmentation(model=model, dataset=dataset,**cfg.pipeline)
pipeline.run_train()
```