dask_ml.tensorflow.start_tensorflow

dask_ml.tensorflow.start_tensorflow(client, **kwargs)

Start Tensorflow on Dask Cluster

This launches Tensorflow Servers alongside Dask workers

Examples

>>> client = Client('dask-scheduler-address:8786')
>>> tf_spec, dask_spec = start_tensorflow(client)
>>> tf_spec.as_dict()
{'worker': ['192.168.1.100:2222', '192.168.1.101:2222']}

Specify desired number of jobs types as keyword args

>>> tf_spec, dask_spec = start_tensorflow(client, ps=2, worker=4)
>>> tf_spec.as_dict()
{'worker': ['192.168.1.100:2222', '192.168.1.101:2222',
            '192.168.1.102:2222', '192.168.1.103:2222'],
 'ps': ['192.168.1.104:2222', '192.168.1.105:2222']}