Perceptual loss with medicalnet_resnet50_23datasets errors due to a typo. #7547
Description
Describe the bug
When trying to use network_type=medicalnet_resnet50_23datasets, I got the following error:
ValueError: Unrecognised criterion entered for Adversarial Loss. Must be one in: alex, vgg, squeeze, radimagenet_resnet50, medicalnet_resnet10_23datasets, medical_resnet50_23datasets, resnet50
Using medical_resnet50_23datasets raises
RuntimeError: Cannot find callable medical_resnet50_23datasets in hubconf
The documentation mentions medicalnet_resnet50_23datasets correctly (as in warvito's hubconf.py in the MedicalNet repo, however in the PerceptualNetworkType Enum, the "net" is missing in the identifier and the string as seen in the error ('medical_resnet50_23datasets') message which is generated from the enum.
To Reproduce
Use the PerceptualLoss class with network_type=medicalnet_resnet50_23datasets or network_type=medical_resnet50_23datasets.
Expected behavior
The class/methods download the specified model from the given repos and calculate the loss accordingly.
Screenshots
Environment
Ensuring you use the relevant python executable, please paste the output of:
python -c "import monai; monai.config.print_debug_info()"
MONAI config
================================
Printing MONAI config...
MONAI version: 1.3.0+88.g95f69dea
Numpy version: 1.26.4
Pytorch version: 2.2.1+cu121
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: 95f69de
MONAI file: /home//workspace/MONAI/monai/init.py
Optional dependencies:
Pytorch Ignite version: 0.4.11
ITK version: 5.3.0
Nibabel version: 5.2.1
scikit-image version: 0.22.0
scipy version: 1.12.0
Pillow version: 10.2.0
Tensorboard version: 2.16.2
gdown version: 4.7.3
TorchVision version: 0.17.1+cu121
tqdm version: 4.66.2
lmdb version: 1.4.1
psutil version: 5.9.8
pandas version: 2.2.1
einops version: 0.7.0
transformers version: 4.38.2
mlflow version: 2.11.1
pynrrd version: 1.0.0
clearml version: 1.14.5rc0
For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies
================================
Printing system config...
System: Linux
Linux version: Arch Linux
Platform: Linux-6.7.4-zen1-1-zen-x86_64-with-glibc2.39
Processor:
Machine: x86_64
Python version: 3.11.7
Process name: python
Command: ['python', '-c', 'import monai; monai.config.print_debug_info()']
Open files: []
Num physical CPUs: 24
Num logical CPUs: 32
Num usable CPUs: 32
CPU usage (%): [9.1, 3.9, 8.2, 9.6, 6.9, 3.0, 4.7, 5.7, 92.3, 7.9, 97.0, 3.0, 4.7, 15.1, 6.8, 4.9, 4.7, 4.9, 4.4, 4.6, 3.6, 4.1, 3.6, 3.3, 3.6, 3.6, 3.3, 3.8, 3.3, 3.3, 3.3, 3.3]
CPU freq. (MHz): 1174
Load avg. in last 1, 5, 15 mins (%): [24.7, 25.0, 24.2]
Disk usage (%): 45.2
Avg. sensor temp. (Celsius): UNKNOWN for given OS
Total physical memory (GB): 62.6
Available memory (GB): 45.1
Used memory (GB): 16.6
================================
Printing GPU config...
Num GPUs: 1
Has CUDA: True
CUDA version: 12.1
cuDNN enabled: True
NVIDIA_TF32_OVERRIDE: None
TORCH_ALLOW_TF32_CUBLAS_OVERRIDE: None
cuDNN version: 8902
Current device: 0
Library compiled for CUDA architectures: ['sm_50', 'sm_60', 'sm_70', 'sm_75', 'sm_80', 'sm_86', 'sm_90']
GPU 0 Name: NVIDIA GeForce RTX 4090 Laptop GPU
GPU 0 Is integrated: False
GPU 0 Is multi GPU board: False
GPU 0 Multi processor count: 76
GPU 0 Total memory (GB): 15.7
GPU 0 CUDA capability (maj.min): 8.9