g = get_loss_grad([x_vec.reshape(*batch_shape)]) return l.astype(np.float64), g.flatten().astype(np.float64) *#Function to minimize loss and iteratively generate the image* def min_loss(fn,epochs,batch_shape): t0 = datetime.now() losses = [] ...