[2022-10-25T01:51:33.989Z] ======================================================================
[2022-10-25T01:51:33.989Z] ERROR: test_shape_0 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:33.989Z] ----------------------------------------------------------------------
[2022-10-25T01:51:33.989Z] Traceback (most recent call last):
[2022-10-25T01:51:33.989Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:33.989Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:33.989Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:33.989Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:33.989Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.989Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.989Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:33.989Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:33.989Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.989Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:33.990Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:33.990Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:33.990Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:33.990Z] 
[2022-10-25T01:51:33.990Z] ======================================================================
[2022-10-25T01:51:33.990Z] ERROR: test_shape_1 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:33.990Z] ----------------------------------------------------------------------
[2022-10-25T01:51:33.990Z] Traceback (most recent call last):
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:33.990Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:33.990Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:33.990Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:33.990Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:33.990Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:33.990Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:33.990Z] 
[2022-10-25T01:51:33.990Z] ======================================================================
[2022-10-25T01:51:33.990Z] ERROR: test_shape_2 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:33.990Z] ----------------------------------------------------------------------
[2022-10-25T01:51:33.990Z] Traceback (most recent call last):
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:33.990Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:33.990Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:33.990Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:33.990Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:33.990Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:33.990Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:33.990Z] 
[2022-10-25T01:51:33.990Z] ======================================================================
[2022-10-25T01:51:33.990Z] ERROR: test_shape_3 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:33.990Z] ----------------------------------------------------------------------
[2022-10-25T01:51:33.990Z] Traceback (most recent call last):
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:33.990Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:33.990Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:33.990Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:33.990Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2811, in cross_entropy
[2022-10-25T01:51:33.990Z]     return handle_torch_function(
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/overrides.py", line 1252, in handle_torch_function
[2022-10-25T01:51:33.990Z]     result = overloaded_arg.__torch_function__(public_api, types, args, kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/data/meta_tensor.py", line 249, in __torch_function__
[2022-10-25T01:51:33.990Z]     ret = super().__torch_function__(func, types, args, kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/_tensor.py", line 1023, in __torch_function__
[2022-10-25T01:51:33.990Z]     ret = func(*args, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:33.990Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:33.990Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:33.990Z] 
[2022-10-25T01:51:33.990Z] ======================================================================
[2022-10-25T01:51:33.990Z] ERROR: test_shape_4 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:33.990Z] ----------------------------------------------------------------------
[2022-10-25T01:51:33.990Z] Traceback (most recent call last):
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:33.990Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:33.990Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:33.990Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:33.990Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:33.990Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2811, in cross_entropy
[2022-10-25T01:51:33.990Z]     return handle_torch_function(
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/overrides.py", line 1252, in handle_torch_function
[2022-10-25T01:51:33.990Z]     result = overloaded_arg.__torch_function__(public_api, types, args, kwargs)
[2022-10-25T01:51:33.990Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/data/meta_tensor.py", line 249, in __torch_function__
[2022-10-25T01:51:33.990Z]     ret = super().__torch_function__(func, types, args, kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/_tensor.py", line 1023, in __torch_function__
[2022-10-25T01:51:33.990Z]     ret = func(*args, **kwargs)
[2022-10-25T01:51:33.990Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:33.990Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:33.990Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:34.248Z] 
[2022-10-25T01:51:34.248Z] ======================================================================
[2022-10-25T01:51:34.248Z] ERROR: test_shape_5 (tests.test_hovernet_loss.TestHoverNetLoss)
[2022-10-25T01:51:34.248Z] ----------------------------------------------------------------------
[2022-10-25T01:51:34.248Z] Traceback (most recent call last):
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/parameterized/parameterized.py", line 533, in standalone_func
[2022-10-25T01:51:34.248Z]     return func(*(a + p.args), **p.kwargs)
[2022-10-25T01:51:34.248Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/tests/test_hovernet_loss.py", line 177, in test_shape
[2022-10-25T01:51:34.248Z]     result = loss(**input_param).to(device)
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:34.248Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:34.248Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/apps/pathology/losses/hovernet_loss.py", line 124, in forward
[2022-10-25T01:51:34.248Z]     ce_loss_np = self.ce(prediction[HoVerNetBranch.NP.value], target[HoVerNetBranch.NP.value]) * self.lambda_np_ce
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1051, in _call_impl
[2022-10-25T01:51:34.248Z]     return forward_call(*input, **kwargs)
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/loss.py", line 1120, in forward
[2022-10-25T01:51:34.248Z]     return F.cross_entropy(input, target, weight=self.weight,
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2811, in cross_entropy
[2022-10-25T01:51:34.248Z]     return handle_torch_function(
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/overrides.py", line 1252, in handle_torch_function
[2022-10-25T01:51:34.248Z]     result = overloaded_arg.__torch_function__(public_api, types, args, kwargs)
[2022-10-25T01:51:34.248Z]   File "/home/jenkins/agent/workspace/Monai-pytorch-versions/monai/data/meta_tensor.py", line 249, in __torch_function__
[2022-10-25T01:51:34.248Z]     ret = super().__torch_function__(func, types, args, kwargs)
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/_tensor.py", line 1023, in __torch_function__
[2022-10-25T01:51:34.248Z]     ret = func(*args, **kwargs)
[2022-10-25T01:51:34.248Z]   File "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py", line 2824, in cross_entropy
[2022-10-25T01:51:34.248Z]     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
[2022-10-25T01:51:34.248Z] RuntimeError: only batches of spatial targets supported (3D tensors) but got targets of dimension: 4
[2022-10-25T01:51:34.248Z] 
[2022-10-25T01:51:34.248Z] ----------------------------------------------------------------------

[2022-10-25T01:22:05.326Z] MONAI version: 1.0.0+65.g06dc983c
[2022-10-25T01:22:05.326Z] Numpy version: 1.23.4
[2022-10-25T01:22:05.326Z] Pytorch version: 1.9.1+cu102
[2022-10-25T01:22:05.326Z] MONAI flags: HAS_EXT = True, USE_COMPILED = True, USE_META_DICT = False
[2022-10-25T01:22:05.326Z] MONAI rev id: 06dc983c64ad7242a11714bd3a98d6d0564c63ba
[2022-10-25T01:22:05.326Z] MONAI __file__: /home/jenkins/agent/workspace/Monai-pytorch-versions/monai/__init__.py
[2022-10-25T01:22:05.326Z] 
[2022-10-25T01:22:05.326Z] Optional dependencies:
[2022-10-25T01:22:05.326Z] Pytorch Ignite version: 0.4.10
[2022-10-25T01:22:05.326Z] Nibabel version: 4.0.2
[2022-10-25T01:22:05.326Z] scikit-image version: 0.19.3
[2022-10-25T01:22:05.326Z] Pillow version: 9.2.0
[2022-10-25T01:22:05.326Z] Tensorboard version: 2.10.1
[2022-10-25T01:22:05.326Z] gdown version: 4.5.3
[2022-10-25T01:22:05.326Z] TorchVision version: 0.10.1+cu102
[2022-10-25T01:22:05.326Z] tqdm version: 4.64.1
[2022-10-25T01:22:05.326Z] lmdb version: 1.3.0
[2022-10-25T01:22:05.326Z] psutil version: 5.9.3
[2022-10-25T01:22:05.326Z] pandas version: 1.5.1
[2022-10-25T01:22:05.326Z] einops version: 0.5.0
[2022-10-25T01:22:05.326Z] transformers version: 4.21.3
[2022-10-25T01:22:05.326Z] mlflow version: 1.30.0
[2022-10-25T01:22:05.326Z] pynrrd version: 1.0.0