MONAI Bundle Properties#
Train properties#
description |
required |
id |
|
---|---|---|---|
bundle_root |
root path of the bundle. |
True |
bundle_root |
device |
target device to execute the bundle workflow. |
True |
device |
dataset_dir |
directory path of the dataset. |
True |
dataset_dir |
trainer |
training workflow engine. |
True |
train::trainer |
network_def |
network module for the training. |
False |
network_def |
max_epochs |
max number of epochs to execute the training. |
True |
train::trainer::max_epochs |
train_dataset |
PyTorch dataset object for the training logic. |
True |
train::dataset |
train_inferer |
MONAI Inferer object to execute the model computation in training. |
True |
train::inferer |
train_dataset_data |
data source for the training dataset. |
False |
train::dataset::data |
train_handlers |
event-handlers for the training logic. |
False |
train::handlers |
train_preprocessing |
preprocessing for the training input data. |
False |
train::preprocessing |
train_postprocessing |
postprocessing for the training model output data. |
False |
train::postprocessing |
train_key_metric |
key metric to compute on the training data. |
False |
train::key_metric |
evaluator |
validation workflow engine. |
False |
validate::evaluator |
val_interval |
validation interval during the training. |
False |
val_interval |
val_handlers |
event-handlers for the validation logic. |
False |
validate::handlers |
val_dataset |
PyTorch dataset object for the validation logic. |
False |
validate::dataset |
val_dataset_data |
data source for the validation dataset. |
False |
validate::dataset::data |
val_inferer |
MONAI Inferer object to execute the model computation in validation. |
False |
validate::inferer |
val_preprocessing |
preprocessing for the validation input data. |
False |
validate::preprocessing |
val_postprocessing |
postprocessing for the validation model output data. |
False |
validate::postprocessing |
val_key_metric |
key metric to compute on the validation data. |
False |
validate::key_metric |
Infer properties#
description |
required |
id |
|
---|---|---|---|
bundle_root |
root path of the bundle. |
True |
bundle_root |
device |
target device to execute the bundle workflow. |
True |
device |
dataset_dir |
directory path of the dataset. |
True |
dataset_dir |
dataset |
PyTorch dataset object for the inference / evaluation logic. |
True |
dataset |
evaluator |
inference / evaluation workflow engine. |
True |
evaluator |
network_def |
network module for the inference. |
True |
network_def |
inferer |
MONAI Inferer object to execute the model computation in inference. |
True |
inferer |
dataset_data |
data source for the inference / evaluation dataset. |
False |
dataset::data |
handlers |
event-handlers for the inference / evaluation logic. |
False |
handlers |
preprocessing |
preprocessing for the input data. |
False |
preprocessing |
postprocessing |
postprocessing for the model output data. |
False |
postprocessing |
key_metric |
the key metric during evaluation. |
False |
key_metric |
Meta properties#
description |
required |
id |
|
---|---|---|---|
version |
bundle version |
True |
_meta_::version |
monai_version |
required monai version used for bundle |
True |
_meta_::monai_version |
pytorch_version |
required pytorch version used for bundle |
True |
_meta_::pytorch_version |
numpy_version |
required numpy version used for bundle |
True |
_meta_::numpy_version |
description |
description for bundle |
False |
_meta_::description |
spatial_shape |
spatial shape for the inputs |
False |
_meta_::network_data_format::inputs::image::spatial_shape |
channel_def |
channel definition for the prediction |
False |
_meta_::network_data_format::outputs::pred::channel_def |