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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_configurations(netG, netD):
 """Get configurations for net"""

    # loss
    loss = gluon.loss.SoftmaxCrossEntropyLoss()

    # initialize the generator and the discriminator
    netG.initialize(mx.init.Normal(0.02), ctx=ctx)
    netD.initialize(mx.init.Normal(0.02), ctx=ctx)

    # trainer for the generator and the discriminator
    trainerG = gluon.Trainer(netG.collect_params(), 'adam', {'learning_rate': opt.lr, 'beta1': opt.beta1})
    trainerD = gluon.Trainer(netD.collect_params(), 'adam', {'learning_rate': opt.lr, 'beta1': opt.beta1})

    return loss, trainerG, trainerD