chronize()
    print(&quot;Start timing ...&quot;)
    timings = []
    with torch.no_grad():
        for i in range(1, nruns+1):
            start_time = time.time()
            features = model(input_data)
            torch.cuda.synchronize()
            end_time = time.time()
            timings.append(end_time - start_time)
            if i%10==0:
                print(&#39;Iteration %d/%d, ave batch time %.2f ms&#39;%(i, nruns, np.mean(timings)*1000))

    print(&quot;Input shape:&quot;, input_data.siz