I am trying to implement an MLP network with the LBFGS optimizer to Solve a classification problem. I have implemented a network in the sklearn with following configuration:
MLPClassifier(activation='relu', alpha=1e-5,
             hidden_layer_sizes=(40,40,40), 
             max_fun=15000, max_iter=1500,
             solver='lbfgs', tol=0.0001,
             validation_fraction=0.1, verbose=False, warm_start=False)

But I don’t know how these hyperparameters should be configured in PyTorch. For example,  ‘max_iters’ stands for number of gradient steps, not for the number of epochs for “LBFGS” optimizer and I don’t know how should I interpret that in PyTorch!