functional
cnn_dann_from_config(config, **trainer_kwargs)
Construct a CNN-DANN approach from a configuration.
The configuration can be created by calling get_cnn_dann_config.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
config |
DictConfig
|
The CNN-DANN configuration. |
required |
trainer_kwargs |
Any
|
Overrides for the trainer class. |
{}
|
Returns: dm: The data module for adaption of two CMAPSS sub-datasets. dann: The DANN approach with feature extractor, regressor and domain disc. trainer: The trainer object.
get_cnn_dann(source_fd, target_fd, **trainer_kwargs)
Construct an CNN-DANN approach for CMAPSS with the original hyperparameters.
The adaption tasks 1-->4, 2-->3, 3-->2 and 4-->1 are missing because they were not investigated in the paper.
Examples:
>>> import rul_adapt
>>> dm, dann, trainer = rul_adapt.construct.get_cnn_dann(3, 1)
>>> trainer.fit(dann, dm)
>>> trainer.test(dann, dm)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
source_fd |
int
|
The source FD of CMAPSS. |
required |
target_fd |
int
|
The target FD of CMAPSS. |
required |
trainer_kwargs |
Any
|
Overrides for the trainer class. |
{}
|
Returns: dm: The data module for adaption of two CMAPSS sub-datasets. dann: The DANN approach with feature extractor, regressor and domain disc. trainer: The trainer object.
get_cnn_dann_config(source_fd, target_fd)
Get a configuration for the CNN-DANN approach.
The adaption tasks 1-->4, 2-->3, 3-->2 and 4-->1 are missing because they were not investigated in the paper. The configuration can be modified and fed to cnn_dann_from_config to create the approach.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
source_fd |
int
|
The source FD of CMAPSS. |
required |
target_fd |
int
|
The target FD of CMAPSS. |
required |
Returns: The CNN-DANN configuration.