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thuhoainguyen / kits23

The official repository of the 2023 Kidney Tumor Segmentation Challenge (KiTS23)
MIT License
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Run nnUNet model #10

Open anhtuduong opened 3 months ago

anhtuduong commented 3 months ago

@thuhoainguyen We are ready to train the first model. Let's setup first: Note: Please observe any unexpected error during installing and let me know!

Setup optimus:

Go to hnguyen@optimus:/data/hnguyen/kits23_training in optimus. And if you use command ls, there should be nnUNet_preprocessed nnUNet_raw nnUNet_results presented.

Clone the git repository:

git clone https://github.com/thuhoainguyen/kits23.git

Go to kits23:

cd kits23

Update submodule nnUNet:

git submodule init
git submodule update

Create virtual environment:

python3 -m venv venv-kits23

Activate virtual environment:

source venv-kits23/bin/activate

Install libraries for kits23:

pip3 install -e .

Install Pytorch:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

Install libraries for nnUNet (note that only install nnUNet after installing Pytorch above)

pip3 install -e nnUNet/

Move the nnUNet_preprocessed, nnUNet_results and nnUNet_results inside kits23:

mv ../nnUNet_preprocessed/ .
mv ../nnUNet_results/ .
mv ../nnUNet_raw/ .

Done setting up! This need to be done only once.

Experimental traning

There are multile configurations in nnUNet. First let's try running nnUNet to train the Dataset079_KiTS2023_preprocessed (the one we dealed with preprocess.py, not the dataset with histology one, I still need to plan for this later). Do you notice that the ID of the dataset I set to 79? Because it's your birthday 🤗

In this experimental training, we will train with configuration 2D U-Net with fold number 0. Please observe the speed so we can plan for all configurations later!

Activate the virtual environment if not yet activated:

source venv-kits23/bin/activate

Setup paths (if it prints out the location of the paths, this means succeed):

source envar.zshrc

Run nnUNet preprocess and planning:

(reference)

nnUNetv2_plan_and_preprocess -d 79 --verify_dataset_integrity

Run the training with configuration 2D U-Net with fold number 0:

nnUNetv2_train 79 2d 0 --npz -device cuda

That's it! Let it run and observe the speed!

Reference: https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/how_to_use_nnunet.md#model-training

Reference: https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/installation_instructions.md

thuhoainguyen commented 3 months ago

@anhtuduong i have an error git clone the kits23 to optimus:

Image

anhtuduong commented 3 months ago

@thuhoainguyen I just fixed the type for cloning git using http, let's try:

git clone https://github.com/thuhoainguyen/kits23.git
thuhoainguyen commented 3 months ago

@anhtuduong I have error regarding the code to run nnUNet preprocess and planning. It said "only 3d images are supported by Nibabel I0"

Fingerprint extraction...
Dataset079_KiTS2023HistogramPreprocessed
Using <class 'nnunetv2.imageio.nibabel_reader_writer.NibabelIOWithReorient'> reader/writer
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
  File "/usr/lib/python3.10/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "/usr/lib/python3.10/multiprocessing/pool.py", line 51, in starmapstar
    return list(itertools.starmap(args[0], args[1]))
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/experiment_planning/verify_dataset_integrity.py", line 52, in check_cases
    images, properties_image = rw.read_images(image_files)
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/imageio/nibabel_reader_writer.py", line 121, in read_images
    assert nib_image.ndim == 3, 'only 3d images are supported by NibabelIO'
AssertionError: only 3d images are supported by NibabelIO
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/data/hnguyen/kits23/venv-kits23/bin/nnUNetv2_plan_and_preprocess", line 8, in <module>
    sys.exit(plan_and_preprocess_entry())
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/experiment_planning/plan_and_preprocess_entrypoints.py", line 184, in plan_and_preprocess_entry
    extract_fingerprints(args.d, args.fpe, args.npfp, args.verify_dataset_integrity, args.clean, args.verbose)
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 47, in extract_fingerprints
    extract_fingerprint_dataset(d, fingerprint_extractor_class, num_processes, check_dataset_integrity, clean,
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/experiment_planning/plan_and_preprocess_api.py", line 30, in extract_fingerprint_dataset
    verify_dataset_integrity(join(nnUNet_raw, dataset_name), num_processes)
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/experiment_planning/verify_dataset_integrity.py", line 213, in verify_dataset_integrity
    result = p.starmap(
  File "/usr/lib/python3.10/multiprocessing/pool.py", line 375, in starmap
    return self._map_async(func, iterable, starmapstar, chunksize).get()
  File "/usr/lib/python3.10/multiprocessing/pool.py", line 774, in get
    raise self._value
AssertionError: only 3d images are supported by NibabelIO

Image

anhtuduong commented 3 months ago

@thuhoainguyen Ok please standby, I will investigate this!

anhtuduong commented 3 months ago

@thuhoainguyen I wrote a script that convert 4D images to 3D images for this. Please:

In /data/hnguyen/kits23:

git pull

Activate the virtual environment if not yet activated:

source venv-kits23/bin/activate

Setup paths (if it prints out the location of the paths, this means succeed):

source envar.zshrc

Convert images:

python3 segmentation/convert_4d_to_3d.py

After the conversion, you can continue to run:

nnUNetv2_plan_and_preprocess -d 79 --verify_dataset_integrity

and train:

nnUNetv2_train 79 2d 0 --npz -device cuda
thuhoainguyen commented 3 months ago

@anhtuduong I'm running the code nnUNetv2_plan_and_preprocess -d 79 --verify_dataset_integrity But looks like they are running all the dataset ? Because I see "208/489". I don't quite understand.

image
thuhoainguyen commented 3 months ago

@anhtuduong After that code above, this info show up:

############################
INFO: You are using the old nnU-Net default planner. We have updated our recommendations. Please consider using those instead! Read more here: https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/resenc_presets.md
############################
thuhoainguyen commented 3 months ago

@anhtuduong I have error regarding the code: nnUNetv2_train 79 2d 0 --npz -device cuda

(venv-kits23) hnguyen@optimus:/data/hnguyen/kits23$ nnUNetv2_train 79 2d 0 --npz -device cuda

A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.0 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Traceback (most recent call last):  File "/data/hnguyen/kits23/venv-kits23/bin/nnUNetv2_train", line 5, in <module>
    from nnunetv2.run.run_training import run_training_entry
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/run/run_training.py", line 13, in <module>
    from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/nnUNetTrainer/nnUNetTrainer.py", line 25, in <module>
    from batchgeneratorsv2.transforms.nnunet.remove_connected_components import \
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/nnunet/remove_connected_components.py", line 5, in <module>
    from acvl_utils.morphology.morphology_helper import label_with_component_sizes
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/acvl_utils/morphology/morphology_helper.py", line 7, in <module>
    import cc3d
Traceback (most recent call last):
  File "/data/hnguyen/kits23/venv-kits23/bin/nnUNetv2_train", line 5, in <module>
    from nnunetv2.run.run_training import run_training_entry
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/run/run_training.py", line 13, in <module>
    from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/nnUNetTrainer/nnUNetTrainer.py", line 25, in <module>
    from batchgeneratorsv2.transforms.nnunet.remove_connected_components import \
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/nnunet/remove_connected_components.py", line 5, in <module>
    from acvl_utils.morphology.morphology_helper import label_with_component_sizes
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/acvl_utils/morphology/morphology_helper.py", line 7, in <module>
    import cc3d
  File "cc3d.pyx", line 1, in init cc3d
ImportError: numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it).
anhtuduong commented 3 months ago

@thuhoainguyen seems like a difficult one... Ok let me have some times with this

anhtuduong commented 3 months ago

@thuhoainguyen Let's try this:

Activate the virtual environment if not yet activated:

source venv-kits23/bin/activate

Setup paths (if it prints out the location of the paths, this means succeed):

source envar.zshrc

Update numpy version:

pip3 install --upgrade numpy==1.26.4

Run the training:

nnUNetv2_train 79 2d 0 --npz -device cuda

The problem is the conflict of numpy version. If the problem still shows up, please run this command and copy the output for me:

pip3 install -e nnUNet/
thuhoainguyen commented 3 months ago

@anhtuduong Still error.

(venv-kits23) hnguyen@optimus:/data/hnguyen/kits23$ pip3 install --upgrade numpy==1.26.4
Collecting numpy==1.26.4
  Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 19.7 MB/s eta 0:00:00
Installing collected packages: numpy
  Attempting uninstall: numpy
    Found existing installation: numpy 2.0.0
    Uninstalling numpy-2.0.0:
      Successfully uninstalled numpy-2.0.0
Successfully installed numpy-1.26.4
(venv-kits23) hnguyen@optimus:/data/hnguyen/kits23$ nnUNetv2_train 79 2d 0 --npz -device cuda

############################
INFO: You are using the old nnU-Net default plans. We have updated our recommendations. Please consider using those instead! Read more here: https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/resenc_presets.md
############################

Using device: cuda:0

#######################################################################
Please cite the following paper when using nnU-Net:
Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211.
#######################################################################

2024-06-17 18:33:02.567160: do_dummy_2d_data_aug: False
2024-06-17 18:33:02.578484: Creating new 5-fold cross-validation split...
2024-06-17 18:33:02.582555: Desired fold for training: 0
2024-06-17 18:33:02.582652: This split has 391 training and 98 validation cases.
using pin_memory on device 0
Exception in background worker 5:
Exception in background worker 7:
 local variable 'region_labels' referenced before assignment
 local variable 'region_labels' referenced before assignment
Exception in background worker 4:
 local variable 'region_labels' referenced before assignment
Traceback (most recent call last):
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/nondet_multi_threaded_augmenter.py", line 53, in producer
    item = next(data_loader)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/data_loader.py", line 126, in __next__
    return self.generate_train_batch()
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/dataloading/data_loader_2d.py", line 100, in generate_train_batch
    tmp = self.transforms(**{'image': data_all[b], 'segmentation': seg_all[b]})
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/compose.py", line 13, in apply
    data_dict = t(**data_dict)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 67, in apply
    data_dict['segmentation'] = self._apply_to_segmentation(data_dict['segmentation'], **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/seg_to_regions.py", line 17, in _apply_to_segmentation
    if isinstance(region_labels, int) or len(region_labels) == 1:
UnboundLocalError: local variable 'region_labels' referenced before assignment
Traceback (most recent call last):
Traceback (most recent call last):
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/nondet_multi_threaded_augmenter.py", line 53, in producer
    item = next(data_loader)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/data_loader.py", line 126, in __next__
    return self.generate_train_batch()
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/nondet_multi_threaded_augmenter.py", line 53, in producer
    item = next(data_loader)
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/dataloading/data_loader_2d.py", line 100, in generate_train_batch
    tmp = self.transforms(**{'image': data_all[b], 'segmentation': seg_all[b]})
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/data_loader.py", line 126, in __next__
    return self.generate_train_batch()
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/dataloading/data_loader_2d.py", line 100, in generate_train_batch
    tmp = self.transforms(**{'image': data_all[b], 'segmentation': seg_all[b]})
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/compose.py", line 13, in apply
    data_dict = t(**data_dict)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 67, in apply
    data_dict['segmentation'] = self._apply_to_segmentation(data_dict['segmentation'], **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/seg_to_regions.py", line 17, in _apply_to_segmentation
    if isinstance(region_labels, int) or len(region_labels) == 1:
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/compose.py", line 13, in apply
    data_dict = t(**data_dict)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 18, in __call__
    return self.apply(data_dict, **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/base/basic_transform.py", line 67, in apply
    data_dict['segmentation'] = self._apply_to_segmentation(data_dict['segmentation'], **params)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgeneratorsv2/transforms/utils/seg_to_regions.py", line 17, in _apply_to_segmentation
    if isinstance(region_labels, int) or len(region_labels) == 1:
UnboundLocalError: local variable 'region_labels' referenced before assignment
UnboundLocalError: local variable 'region_labels' referenced before assignment
Traceback (most recent call last):
  File "/data/hnguyen/kits23/venv-kits23/bin/nnUNetv2_train", line 8, in <module>
    sys.exit(run_training_entry())
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/run/run_training.py", line 275, in run_training_entry
    run_training(args.dataset_name_or_id, args.configuration, args.fold, args.tr, args.p, args.pretrained_weights,
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/run/run_training.py", line 211, in run_training
    nnunet_trainer.run_training()
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/nnUNetTrainer/nnUNetTrainer.py", line 1362, in run_training
    self.on_train_start()
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/nnUNetTrainer/nnUNetTrainer.py", line 903, in on_train_start
    self.dataloader_train, self.dataloader_val = self.get_dataloaders()
  File "/data/hnguyen/kits23/nnUNet/nnunetv2/training/nnUNetTrainer/nnUNetTrainer.py", line 696, in get_dataloaders
    _ = next(mt_gen_train)
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/nondet_multi_threaded_augmenter.py", line 196, in __next__
    item = self.__get_next_item()
  File "/data/hnguyen/kits23/venv-kits23/lib/python3.10/site-packages/batchgenerators/dataloading/nondet_multi_threaded_augmenter.py", line 181, in __get_next_item
    raise RuntimeError("One or more background workers are no longer alive. Exiting. Please check the "
RuntimeError: One or more background workers are no longer alive. Exiting. Please check the print statements above for the actual error message
(venv-kits23) hnguyen@optimus:/data/hnguyen/kits23$ pip3 install -e nnUNet/
Obtaining file:///data/hnguyen/kits23/nnUNet
  Installing build dependencies ... done
  Checking if build backend supports build_editable ... done
  Getting requirements to build editable ... done
  Installing backend dependencies ... done
  Preparing editable metadata (pyproject.toml) ... done
Requirement already satisfied: dynamic-network-architectures<0.4,>=0.3.1 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.3.1)
Requirement already satisfied: tqdm in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (4.66.4)
Requirement already satisfied: tifffile in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2024.5.22)
Requirement already satisfied: matplotlib in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (3.9.0)
Requirement already satisfied: einops in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.8.0)
Requirement already satisfied: acvl-utils<0.3,>=0.2 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.2)
Requirement already satisfied: scikit-image>=0.19.3 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.23.2)
Requirement already satisfied: batchgeneratorsv2 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.1.1)
Requirement already satisfied: dicom2nifti in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2.4.11)
Requirement already satisfied: pandas in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2.2.2)
Requirement already satisfied: seaborn in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.13.2)
Requirement already satisfied: requests in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2.32.3)
Requirement already satisfied: scikit-learn in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (1.5.0)
Requirement already satisfied: scipy in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (1.13.1)
Requirement already satisfied: batchgenerators>=0.25 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.25)
Requirement already satisfied: torch>=2.1.2 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2.3.1+cu118)
Requirement already satisfied: yacs in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.1.8)
Requirement already satisfied: graphviz in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (0.20.3)
Requirement already satisfied: imagecodecs in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2024.6.1)
Requirement already satisfied: SimpleITK>=2.2.1 in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (2.3.1)
Requirement already satisfied: numpy in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (1.26.4)
Requirement already satisfied: nibabel in ./venv-kits23/lib/python3.10/site-packages (from nnunetv2==2.5) (5.2.1)
Requirement already satisfied: connected-components-3d in ./venv-kits23/lib/python3.10/site-packages (from acvl-utils<0.3,>=0.2->nnunetv2==2.5) (3.16.0)
Requirement already satisfied: future in ./venv-kits23/lib/python3.10/site-packages (from batchgenerators>=0.25->nnunetv2==2.5) (1.0.0)
Requirement already satisfied: pillow>=7.1.2 in ./venv-kits23/lib/python3.10/site-packages (from batchgenerators>=0.25->nnunetv2==2.5) (10.3.0)
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Collecting argparse
  Using cached argparse-1.4.0-py2.py3-none-any.whl (23 kB)
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Building wheels for collected packages: nnunetv2
  Building editable for nnunetv2 (pyproject.toml) ... done
  Created wheel for nnunetv2: filename=nnunetv2-2.5-0.editable-py3-none-any.whl size=16624 sha256=723e2726c5955188d43e52980c0dad64c7794b4a50680ea5e8760969e5e0ff65
  Stored in directory: /tmp/pip-ephem-wheel-cache-dm9d9ux_/wheels/82/e6/77/681b0fcdb919f59fa77d2de0fa7b6e9d1ad1f7f33d246c5d74
Successfully built nnunetv2
Installing collected packages: argparse, nnunetv2
  Attempting uninstall: nnunetv2
    Found existing installation: nnunetv2 2.5
    Uninstalling nnunetv2-2.5:
      Successfully uninstalled nnunetv2-2.5
Successfully installed argparse-1.4.0 nnunetv2-2.5
anhtuduong commented 3 months ago

@thuhoainguyen oke we solved the numpy error! This is another error with the machine. Be patient, we are getting closer!

anhtuduong commented 3 months ago

@thuhoainguyen please ask Jacopo to let me access to your workspace in optimus. Let him know that I will help you on some difficult technicals. My email is aduong@fbk.eu, and I'm working at Software Engineering unit.