Thanks for getting back. It is a little weird - I have dozens of models all running the same datasets and have never had a problem with it before. I even have ensembles of models with not prior problem. I am trying not to tunnel vision but the updates were substantial - system, applications, Python, etc.
So, if it is NOT the updates, any suggestions on where to look? Just for fun, here is a code snippet:
for epoch in range(epochs):
    for i, data in enumerate(train_loader,1):
        inputs, targets = data
        
        if use_cuda:             #Use this for all other optimizers
            y_pred=net_model(inputs)
            loss=loss_fn(y_pred, targets)
            time=str(datetime.now())  
            optimizer.zero_grad()
            loss.backward()
            optimizer.step()                   
        with torch.no_grad():
            counter=0
            for param in net_model.parameters():
                param-=alpha*param.grad

    loss_array[epoch]=loss.item()    #Un-comment these 6 lines if NOT using LBFGS
    if epoch%100==0:
        print(datetime.now(),"Loss for epoch:", epoch, loss.item())
    if loss.item() < 1e-8:
        print(datetime.now(),"Loss for epoch:", epoch, loss.item())
        break