feed-forward neural networks #caculate loss loss loss_function(output_datalabels#backpropogate loss backward(#update weights optimizer step(train_loss +loss item(batch_size print("epoch{loss:{ }format(epoch+ ,train_ loss )loss_across_epochs extend([train_loss]#predict y_test_pred model(x_testa =np where(y_test_pred> , , return(loss_across_epochs###end of function#create an object of the neural network class model neuralnetwork(#define loss function loss_function nn bceloss(#binary crosss entropy loss #define optimizer adam_optimizer tch optim adam(model parameters(),lr #define epochs and batch size num_epochs batch_size= #calling the function for training and pass modeloptimizerloss and related paramters