Right, I should clarify.
I’m comparing with NumPy serialization. The picture below times serialization for NumPy and PyTorch with pickle.dumps on a Macbook Pro 2015.

Screen Shot 2017-12-19 at 5.04.59 PM.png1260×798 86.4 KB

The core of my code was
def stat(x, serialize=pickle.dumps):
    start = time.time()
    msg = serialize(x)
    return {'time': time.time() - start, 'bytes': len(msg)}

# ... other functions, for-loops, etc
x = np.random.randn(n).astype('float32')
y = torch.Tensor(x)

This is with torch.__version__ == 0.3.0.post4.