Table Of Contents
Table Of Contents



Registers an optimizer with the kvstore.

When using a single machine, this function updates the local optimizer. If using multiple machines and this operation is invoked from a worker node, it will serialized the optimizer with pickle and send it to all servers. The function returns after all servers have been updated.

Parameters:optimizer (Optimizer) – The new optimizer for the store


>>> kv = mx.kv.create()
>>> shape = (2, 2)
>>> weight = mx.nd.zeros(shape)
>>> kv.init(3, weight)
>>> # set the optimizer for kvstore as the default SGD optimizer
>>> kv.set_optimizer(mx.optimizer.SGD())
>>> grad = mx.nd.ones(shape)
>>> kv.push(3, grad)
>>> kv.pull(3, out = weight)
>>> # weight is updated via gradient descent
>>> weight.asnumpy()
array([[-0.01, -0.01],
       [-0.01, -0.01]], dtype=float32)