Unable to use the DataIQ_MAPS_Torch class

[overseek944]

Description

I am trying to use DataIQ_MAPS_Torch class with the following piece of code -

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=0)
X_train = std_scaler.fit_transform(X_train)
X_test = std_scaler.transform(X_test)

datahander = DataHandler(X_train, y_train, batch_size=32)
dataloader_ = DataLoader(datahander.dataloader,batch_size=32)

model = DataIQ_MAPS_Torch(dataloader_)

# creating our optimizer and loss function objects
learning_rate = 0.01
criterion = nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(<unknown>,lr=learning_rate)

I am not able to understand what should I put in the <unkown> field in the last of above provided code.

I tried to same thing with SimpleMLP but I didn't got issue there because class is defined with SimpleMLP(nn.module)
so there model.parameters() is not failing while defining optimizer but while using the same code with DataIQ_MAPS_Torch class its not able to understand model.parameters() because its not a nn.module class.

My ask is how can I use DataIQ_MAPS_Torch similar to SimpleMLP?
Can you share a sample code for the same?