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AttributeError: 'list' object has no attribute 'ndim' with RandomTransplantation and batch with keys #2910

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robmarkcole opened this issue May 16, 2024 · 2 comments
Closed

AttributeError: 'list' object has no attribute 'ndim' with RandomTransplantation and batch with keys #2910

robmarkcole opened this issue May 16, 2024 · 2 comments
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help wanted Extra attention is needed

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@robmarkcole
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Describe the bug

I can run:

import torch
import kornia.augmentation as K
from kornia.augmentation.container import AugmentationSequential

# Example batch with correct shapes
batch = {
    "image": torch.randn(10, 3, 64, 64),  # [N, C, H, W]
    "mask": torch.randint(0, 2, (10, 64, 64))  # [N, H, W]
}
aug = AugmentationSequential(
    K.RandomTransplantation(p=1.0, excluded_labels=[0]), 
    data_keys=None
)

augmented_batch = aug(batch)

However when I use my own datamodule, I receive an error:

datamodule.setup(stage="fit")
aug = AugmentationSequential(
    ka.RandomTransplantation(p=1., excluded_labels=[0]),
    data_keys = None,
)

train_dataloader = datamodule.train_dataloader()
batch = next(iter(train_dataloader))
# where batch["image"].shape, batch["mask"].shape == (torch.Size([10, 3, 64, 64]), torch.Size([10, 64, 64]))
augmented_batch = aug(batch)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[17], [line 1](vscode-notebook-cell:?execution_count=17&line=1)
----> [1](vscode-notebook-cell:?execution_count=17&line=1) augmented_batch = aug(batch)

File [/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1518](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1518), in Module._wrapped_call_impl(self, *args, **kwargs)
   [1516](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1516)     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   [1517](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1517) else:
-> [1518](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1518)     return self._call_impl(*args, **kwargs)

File [/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1527](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1527), in Module._call_impl(self, *args, **kwargs)
   [1522](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1522) # If we don't have any hooks, we want to skip the rest of the logic in
   [1523](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1523) # this function, and just call forward.
   [1524](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1524) if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   [1525](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1525)         or _global_backward_pre_hooks or _global_backward_hooks
   [1526](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1526)         or _global_forward_hooks or _global_forward_pre_hooks):
-> [1527](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1527)     return forward_call(*args, **kwargs)
   [1529](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1529) try:
   [1530](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/torch/nn/modules/module.py:1530)     result = None

File [/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:421](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:421), in AugmentationSequential.forward(self, params, data_keys, *args)
    [419](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:419) for param in params:
    [420](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:420)     module = self.get_submodule(param.name)
--> [421](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:421)     outputs = self.transform_op.transform(  # type: ignore
    [422](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:422)         *outputs, module=module, param=param, extra_args=self.extra_args
    [423](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:423)     )
    [424](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:424)     if not isinstance(outputs, (list, tuple)):
    [425](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:425)         # Make sure we are unpacking a list whilst post-proc
    [426](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/augment.py:426)         outputs = [outputs]

File [/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:120](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:120), in AugmentationSequentialOps.transform(self, module, param, extra_args, data_keys, *arg)
    [114](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:114) _data_keys = self.preproc_datakeys(data_keys)
    [116](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:116) if isinstance(module, K.RandomTransplantation):
    [117](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:117)     # For transforms which require the full input to calculate the parameters (e.g. RandomTransplantation)
    [118](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:118)     param = ParamItem(
    [119](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:119)         name=param.name,
--> [120](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:120)         data=module.params_from_input(
    [121](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:121)             *arg,  # type: ignore[arg-type]
    [122](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:122)             data_keys=_data_keys,
    [123](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:123)             params=param.data,  # type: ignore[arg-type]
    [124](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:124)             extra_args=extra_args,
    [125](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:125)         ),
    [126](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:126)     )
    [128](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:128) outputs = []
    [129](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/container/ops.py:129) for inp, dcate in zip(arg, _data_keys):

File [/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:219](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:219), in RandomTransplantation.params_from_input(self, data_keys, params, extra_args, *input)
    [216](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:216) for _input, key in zip(input, data_keys):
    [217](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:217)     if key == DataKey.INPUT:
    [218](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:218)         KORNIA_CHECK(
--> [219](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:219)             _input.ndim == mask.ndim + 1,
    [220](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:220)             "Every image input must have one additional dimension (channel dimension) than the segmentation "
    [221](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:221)             f"mask, but got {_input.ndim} for the input image and {mask.ndim} for the segmentation mask.",
    [222](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:222)         )
    [223](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:223)         KORNIA_CHECK(
    [224](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:224)             mask.size() == torch.Size([s for i, s in enumerate(_input.size()) if i != self._channel_dim]),
    [225](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:225)             "The dimensions of the input image and segmentation mask must match except for the channel "
    [226](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:226)             f"dimension, but got {_input.size()} for the input image and {mask.size()} for the segmentation "
    [227](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:227)             "mask.",
    [228](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:228)         )
    [230](https://vscode-remote+vscode-002d01hkygqybbyxdgxvrbmrk03kmn-002estudio-002elightning-002eai.vscode-resource.vscode-cdn.net/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/kornia/augmentation/_2d/mix/transplantation.py:230) if "acceptor_indices" not in params:

AttributeError: 'list' object has no attribute 'ndim'

Reproduction steps

As shown

Expected behavior

As shown

Environment

⚡ ~ python collect_env.py 
Collecting environment information...
PyTorch version: 2.1.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-1058-aws-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A10G
Nvidia driver version: 535.161.08
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      48 bits physical, 48 bits virtual
CPU(s):                             32
On-line CPU(s) list:                0-31
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          AuthenticAMD
CPU family:                         23
Model:                              49
Model name:                         AMD EPYC 7R32
Stepping:                           0
CPU MHz:                            2799.998
BogoMIPS:                           5599.99
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          512 KiB
L1i cache:                          512 KiB
L2 cache:                           8 MiB
⚡ ~ python collect_env.py
Collecting environment information...
PyTorch version: 2.1.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-1058-aws-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A10G
Nvidia driver version: 535.161.08
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      48 bits physical, 48 bits virtual
CPU(s):                             32
On-line CPU(s) list:                0-31
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          AuthenticAMD
CPU family:                         23
Model:                              49
Model name:                         AMD EPYC 7R32
Stepping:                           0
CPU MHz:                            2799.998
BogoMIPS:                           5599.99
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          512 KiB
L1i cache:                          512 KiB
L2 cache:                           8 MiB
L3 cache:                           64 MiB
NUMA node0 CPU(s):                  0-31
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Not affected
Vulnerability Retbleed:             Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow: Mitigation; safe RET
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch topoext ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru wbnoinvd arat npt nrip_save rdpid

Versions of relevant libraries:
[pip3] efficientnet-pytorch==0.7.1
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.2
[pip3] pytorch-lightning==2.1.2
[pip3] segmentation-models-pytorch==0.3.3
[pip3] torch==2.1.1+cu121
[pip3] torchaudio==2.1.1+cu121
[pip3] torchgeo==0.6.0.dev0
[pip3] torchmetrics==1.2.0
[pip3] torchvision==0.16.1+cu121
[pip3] triton==2.1.0
[conda] efficientnet-pytorch      0.7.1                    pypi_0    pypi
[conda] numpy                     1.26.2                   pypi_0    pypi
[conda] pytorch-lightning         2.1.2                    pypi_0    pypi
[conda] segmentation-models-pytorch 0.3.3                    pypi_0    pypi
[conda] torch                     2.1.1+cu121              pypi_0    pypi
[conda] torchaudio                2.1.1+cu121              pypi_0    pypi
[conda] torchgeo                  0.6.0.dev0               pypi_0    pypi
[conda] torchmetrics              1.2.0                    pypi_0    pypi
[conda] torchvision               0.16.1+cu121             pypi_0    pypi
[conda] triton                    2.1.0                    pypi_0    pypi

Additional context

No response
@robmarkcole robmarkcole added the help wanted Extra attention is needed label May 16, 2024
@edgarriba
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you cannot cast to a dictionary the result of datamodule (which format they produce?) /cc @johnnv1 @shijianjian

@robmarkcole
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robmarkcole commented May 17, 2024 •
edited

OK I discovered the cause - my batch had a key which was a list of str, deleting this the issue is resolved

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