tf.config.experimental_connect_to_host

Connects to a single machine to enable remote execution on it.

View aliases

Main aliases

`tf.contrib.eager.connect_to_remote_host`

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.config.experimental_connect_to_host, `tf.compat.v2.config.experimental_connect_to_host`

tf.config.experimental_connect_to_host(
    remote_host=None, job_name='worker'
)

Will make devices on the remote host available to use. Note that calling this more than once will work, but will invalidate any tensor handles on the old remote devices.

Using the default job_name of worker, you can schedule ops to run remotely as follows:

# Enable eager execution, and connect to the remote host.
tf.compat.v1.enable_eager_execution()
tf.contrib.eager.connect_to_remote_host("exampleaddr.com:9876")

with ops.device("job:worker/replica:0/task:1/device:CPU:0"):
  # The following tensors should be resident on the remote device, and the op
  # will also execute remotely.
  x1 = array_ops.ones([2, 2])
  x2 = array_ops.ones([2, 2])
  y = math_ops.matmul(x1, x2)

Args
remote_host	a single or a list the remote server addr in host-port format.
job_name	The job name under which the new server will be accessible.

Raises
ValueError	if remote_host is None.