RuntimeError: The size of tensor a (82) must match the size of tensor b (64) at non-singleton dimension 3 about raster-vision HOT 4 CLOSED

ValueError                                Traceback (most recent call last)
Cell In[35], [line 10](vscode-notebook-cell:?execution_count=35&line=10)
      [1](vscode-notebook-cell:?execution_count=35&line=1) from rastervision.core.data import SemanticSegmentationLabels
      [3](vscode-notebook-cell:?execution_count=35&line=3) predictions = learner.predict_dataset(
      [4](vscode-notebook-cell:?execution_count=35&line=4)     ds,
      [5](vscode-notebook-cell:?execution_count=35&line=5)     raw_out=True,
      [6](vscode-notebook-cell:?execution_count=35&line=6)     numpy_out=True,
      [7](vscode-notebook-cell:?execution_count=35&line=7)     predict_kw=dict(out_shape=(256, 256)),
      [8](vscode-notebook-cell:?execution_count=35&line=8)     progress_bar=True)
---> [10](vscode-notebook-cell:?execution_count=35&line=10) pred_labels = SemanticSegmentationLabels.from_predictions(
     [11](vscode-notebook-cell:?execution_count=35&line=11)     ds.windows,
     [12](vscode-notebook-cell:?execution_count=35&line=12)     predictions,
     [13](vscode-notebook-cell:?execution_count=35&line=13)     smooth=True,
     [14](vscode-notebook-cell:?execution_count=35&line=14)     extent=ds.scene.extent,
     [15](vscode-notebook-cell:?execution_count=35&line=15)     num_classes=len(class_config))

File [~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:210](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:210), in SemanticSegmentationLabels.from_predictions(cls, windows, predictions, extent, num_classes, smooth, crop_sz)
    [184](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:184) """Instantiate from windows and their corresponding predictions.
    [185](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:185) 
    [186](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:186) Args:
   (...)
    [207](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:207)     Otherwise, a SemanticSegmentationDiscreteLabels.
    [208](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:208) """
    [209](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:209) labels = cls.make_empty(extent, num_classes, smooth=smooth)
...
    [480](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:480) pixel_class_scores = pixel_class_scores[..., src_yslice, src_xslice]
--> [481](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:481) self.pixel_scores[..., dst_yslice, dst_xslice] += pixel_class_scores
    [482](https://file+.vscode-resource.vscode-cdn.net/media/lining/0BFD1A2A0BFD1A2A/mywork/rastervision/~/.local/lib/python3.10/site-packages/rastervision/core/data/label/semantic_segmentation_labels.py:482) self.pixel_hits[dst_yslice, dst_xslice] += 1


ValueError: operands could not be broadcast together with shapes (3,256,256) (2,256,256) (3,256,256)

from rastervision.pytorch_learner import SemanticSegmentationLearner

learner = SemanticSegmentationLearner.from_model_bundle(
    model_bundle_uri='./train-demo/model-bundle.zip',
    output_dir='./train/',
    model=model,
    training=False
)
image_uri = f'longjiangbouter.tif'
label_uri = f'longjiangbouter.geojson'
from rastervision.core.data import ClassConfig

class_config = ClassConfig(
    names=['building', 'background'],
    colors=['orange', 'black'])
class_config.ensure_null_class()
from rastervision.core.data import ClassConfig
from rastervision.pytorch_learner import SemanticSegmentationSlidingWindowGeoDataset

import albumentations as A

ds = SemanticSegmentationSlidingWindowGeoDataset.from_uris(
    class_config=class_config,
    image_uri=image_uri,
    size=256,
    stride=256,
    transform=A.Resize(256, 256))

from rastervision.core.data import SemanticSegmentationLabels

predictions = learner.predict_dataset(
    ds,
    raw_out=True,
    numpy_out=True,
    predict_kw=dict(out_shape=(256, 256)),
    progress_bar=True)

pred_labels = SemanticSegmentationLabels.from_predictions(
    ds.windows,
    predictions,
    smooth=True,
    extent=ds.scene.extent,
    num_classes=len(class_config))