feed-forward neural networks nextlet' create dummy dataset for our neural network listing - illustrates the creation of toy (dummydataset for the exercise listing - creating toy dataset samples #let' divide the toy dataset into training ( %and rest for validation train_split int(samples* #create dummy classification dataset xy make_blobs(n_samples=samplescenters= n_features= cluster_std= random_state= reshape(- , #convert the numpy datasets to torch tensors , tch from_numpy( ),tch from_numpy(yx, = float(), float(#split the datasets inot train and test(validationx_trainx_test [:train_split] [train_split:y_trainy_test [:train_split] [train_split:#print shapes of each dataset print("x_train shape:",x_train shapeprint("x_test shape:",x_test shapeprint("y_train shape:",y_train shapeprint("y_test shape:",y_test shapeprint(" dtype", dtypeprint(" dtype", dtypeoutput[x_train shapetorch size([ ]x_test shapetorch size([ ]