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Description
Describe the bug
MONAI bundle instantiate fails when _target_ contains path attribute
The following error is thrown,
To Reproduce
I created a dataset.py file with the following
class MyDataset:
def __init__(self, path=None) -> None:
self.path = path
print(path)
and run the following code which throws an error
config = {
"dataset": {
"_target_": "dataset.MyDataset",
"path": "test.csv"
}
}
run("dataset", **config)
Error message:
Traceback (most recent call last):
File "/home/suraj/anaconda3/envs/lightningssl/lib/python3.8/site-packages/monai/bundle/config_item.py", line 283, in instantiate
return instantiate(modname, **args)
TypeError: instantiate() got multiple values for argument 'path'
Expected behavior
The dataset object should be instantiated.
Additional context
Seems like the issue is here:
Line 217 in 734d4ff
| def instantiate(path: str, **kwargs): |
where the instantiate uses has a
path attribute itself, causing the duplication when path is passed in kwargs as well.
Since path is a very common attribute used in datasets, it might be prudent to change the name of this argument to a non-conflicting name
Environment
Ensuring you use the relevant python executable, please paste the output of:
================================
Printing MONAI config...
================================
MONAI version: 1.1.0
Numpy version: 1.23.3
Pytorch version: 1.12.1+cu102
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: a2ec3752f54bfc3b40e7952234fbeb5452ed63e3
MONAI __file__: /home/suraj/anaconda3/envs/lightningssl/lib/python3.8/site-packages/monai/__init__.py
Optional dependencies:
Pytorch Ignite version: NOT INSTALLED or UNKNOWN VERSION.
Nibabel version: NOT INSTALLED or UNKNOWN VERSION.
scikit-image version: NOT INSTALLED or UNKNOWN VERSION.
Pillow version: 9.2.0
Tensorboard version: 2.11.0
gdown version: NOT INSTALLED or UNKNOWN VERSION.
TorchVision version: 0.13.1+cu102
tqdm version: 4.64.1
lmdb version: NOT INSTALLED or UNKNOWN VERSION.
psutil version: 5.9.3
pandas version: 1.5.0
einops version: NOT INSTALLED or UNKNOWN VERSION.
transformers version: NOT INSTALLED or UNKNOWN VERSION.
mlflow version: NOT INSTALLED or UNKNOWN VERSION.
pynrrd version: NOT INSTALLED or UNKNOWN VERSION.
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: Ubuntu 20.04.4 LTS
Platform: Linux-5.13.0-40-generic-x86_64-with-glibc2.10
Processor: x86_64
Machine: x86_64
Python version: 3.8.13
Process name: python
Command: ['python', '-c', 'import monai; monai.config.print_debug_info()']
Num physical CPUs: 12
Num logical CPUs: 12
Num usable CPUs: 12
CPU usage (%): [15.9, 16.2, 6.0, 9.1, 4.5, 8.9, 2.3, 2.2, 0.8, 3.0, 2.3, 100.0]
CPU freq. (MHz): 908
Load avg. in last 1, 5, 15 mins (%): [7.6, 8.9, 11.3]
Disk usage (%): 82.3
Avg. sensor temp. (Celsius): UNKNOWN for given OS
Total physical memory (GB): 250.6
Available memory (GB): 92.9
Used memory (GB): 5.8
================================
Printing GPU config...
================================
Num GPUs: 4
Has CUDA: True
CUDA version: 10.2
cuDNN enabled: True
cuDNN version: 7605
Current device: 0
Library compiled for CUDA architectures: ['sm_37', 'sm_50', 'sm_60', 'sm_70']
GPU 0 Name: Quadro RTX 8000
GPU 0 Is integrated: False
GPU 0 Is multi GPU board: False
GPU 0 Multi processor count: 72
GPU 0 Total memory (GB): 47.5
GPU 0 CUDA capability (maj.min): 7.5
GPU 1 Name: Quadro RTX 8000
GPU 1 Is integrated: False
GPU 1 Is multi GPU board: False
GPU 1 Multi processor count: 72
GPU 1 Total memory (GB): 47.5
GPU 1 CUDA capability (maj.min): 7.5
GPU 2 Name: Quadro RTX 8000
GPU 2 Is integrated: False
GPU 2 Is multi GPU board: False
GPU 2 Multi processor count: 72
GPU 2 Total memory (GB): 47.5
GPU 2 CUDA capability (maj.min): 7.5
GPU 3 Name: Quadro RTX 8000
GPU 3 Is integrated: False
GPU 3 Is multi GPU board: False
GPU 3 Multi processor count: 72
GPU 3 Total memory (GB): 47.5
GPU 3 CUDA capability (maj.min): 7.5