Custom Model

Users can independently add models according to the inheritance scheme. The user model should be described by a class that inherits from one of the base classes of the task model: BaseAnomalyDetection, BaseFaultDiagnosis, BaseHealthIndexEstimation, BaseRemainingUsefulLifeEstimation. The class should implement two methods: __init__ and _create_model.

The __init__ method should include parameters of the base task class, as well as parameters specific to this model, such as hidden_dim for an MLP model. The method should call the __init__ method of the parent class, passing all necessary parameters.

The _create_model method should include the parameters input_dim and output_dim, which define the number of sensors and the number of output values, respectively. For Fault diagnosis tasks, the number of output values corresponds to the number of faults, while for other tasks, this number equals 1. The method should assign an object of the PyTorch neural network model of type torch.nn.Module to the model attribute of the class.

The source code of the user model should be located in the directory ice/task_name/models, where task_name should be replaced with the specific task being solved, for example, fault_diagnosis.