Traceback (most recent call last):
File "<frozen runpy>", line 198, in _run_module_as_main
File "<frozen runpy>", line 88, in _run_code
File "/workspace/app/MIPCandy/benchmark/__main__.py", line 35, in <module>
raise err
File "/workspace/app/MIPCandy/benchmark/prototype.py", line 28, in run
self.execute()
File "/workspace/app/MIPCandy/benchmark/training.py", line 53, in execute
return self["trainer"].train(self.num_epochs, note=f"Training test {self.resize}", compile_model=True,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/training.py", line 537, in train
raise e
File "/workspace/app/MIPCandy/mipcandy/training.py", line 493, in train
score, metrics = self.validate(toolbox)
^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/training.py", line 588, in validate
case_score, case_metrics, output = self.validate_case(idx, image, label, toolbox)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/presets/segmentation.py", line 171, in validate_case
loss, metrics = toolbox.criterion([mask_for_loss], [label])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/presets/segmentation.py", line 43, in forward
loss, metrics = self.loss(output, target)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/venv/main/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1787, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/common/optim/loss.py", line 59, in forward
metrics["dice"] = dice_similarity_coefficient_with_logits(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/app/MIPCandy/mipcandy/metrics.py", line 78, in dice_similarity_coefficient_with_logits
if volume_sum == 0:
^^^^^^^^^^^^^^^
RuntimeError: Boolean value of Tensor with more than one value is ambiguous
