tf.config.experimental_connect_to_cluster
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Connects to the given cluster.
tf.config.experimental_connect_to_cluster(
cluster_spec_or_resolver, job_name='localhost', task_index=0, protocol=None,
make_master_device_default=True
)
Will make devices on the cluster available to use. Note that calling this more
than once will work, but will invalidate any tensor handles on the old remote
devices.
If the given local job name is not present in the cluster specification, it
will be automatically added, using an unused port on the localhost.
Args |
|---|
cluster_spec_or_resolver
|
A ClusterSpec or ClusterResolver describing
the cluster.
|
job_name
|
The name of the local job.
|
task_index
|
The local task index.
|
protocol
|
The communication protocol, such as "grpc". If unspecified, will
use the default from python/platform/remote_utils.py.
|
make_master_device_default
|
If True and a cluster resolver is passed, will
automatically enter the master task device scope, which indicates the
master becomes the default device to run ops. It won't do anything if
a cluster spec is passed. Will throw an error if the caller is currently
already in some device scope.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.config.experimental_connect_to_cluster\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/config/experimental_connect_to_cluster) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.1.0/tensorflow/python/eager/remote.py#L80-L178) |\n\nConnects to the given cluster.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.config.experimental_connect_to_cluster`](/api_docs/python/tf/config/experimental_connect_to_cluster)\n\n\u003cbr /\u003e\n\n tf.config.experimental_connect_to_cluster(\n cluster_spec_or_resolver, job_name='localhost', task_index=0, protocol=None,\n make_master_device_default=True\n )\n\nWill make devices on the cluster available to use. Note that calling this more\nthan once will work, but will invalidate any tensor handles on the old remote\ndevices.\n\nIf the given local job name is not present in the cluster specification, it\nwill be automatically added, using an unused port on the localhost.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `cluster_spec_or_resolver` | A `ClusterSpec` or `ClusterResolver` describing the cluster. |\n| `job_name` | The name of the local job. |\n| `task_index` | The local task index. |\n| `protocol` | The communication protocol, such as `\"grpc\"`. If unspecified, will use the default from `python/platform/remote_utils.py`. |\n| `make_master_device_default` | If True and a cluster resolver is passed, will automatically enter the master task device scope, which indicates the master becomes the default device to run ops. It won't do anything if a cluster spec is passed. Will throw an error if the caller is currently already in some device scope. |\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub