An in-process TensorFlow server, for use in distributed training.
tf.distribute.Server(
server_or_cluster_def, job_name=None, task_index=None, protocol=None,
config=None, start=True
)
Used in the notebooks
A tf.distribute.Server instance encapsulates a set of devices and a
tf.compat.v1.Session target that
can participate in distributed training. A server belongs to a
cluster (specified by a tf.train.ClusterSpec), and
corresponds to a particular task in a named job. The server can
communicate with any other server in the same cluster.
Args |
|---|
server_or_cluster_def
|
A tf.train.ServerDef or tf.train.ClusterDef
protocol buffer, or a tf.train.ClusterSpec object, describing the
server to be created and/or the cluster of which it is a member.
|
job_name
|
(Optional.) Specifies the name of the job of which the server is
a member. Defaults to the value in server_or_cluster_def, if
specified.
|
task_index
|
(Optional.) Specifies the task index of the server in its job.
Defaults to the value in server_or_cluster_def, if specified.
Otherwise defaults to 0 if the server's job has only one task.
|
protocol
|
(Optional.) Specifies the protocol to be used by the server.
Acceptable values include "grpc", "grpc+verbs". Defaults to the value
in server_or_cluster_def, if specified. Otherwise defaults to
"grpc".
|
config
|
(Options.) A tf.compat.v1.ConfigProto that specifies default
configuration options for all sessions that run on this server.
|
start
|
(Optional.) Boolean, indicating whether to start the server after
creating it. Defaults to True.
|
Raises |
|---|
tf.errors.OpError
|
Or one of its subclasses if an error occurs while
creating the TensorFlow server.
|
Attributes |
|---|
server_def
|
Returns the tf.train.ServerDef for this server.
|
target
|
Returns the target for a tf.compat.v1.Session to connect to this server.
To create a
tf.compat.v1.Session that
connects to this server, use the following snippet:
server = tf.distribute.Server(...)
with tf.compat.v1.Session(server.target):
# ...
|
Methods
create_local_server
View source
@staticmethod
create_local_server(
config=None, start=True
)
Creates a new single-process cluster running on the local host.
This method is a convenience wrapper for creating a
tf.distribute.Server with a tf.train.ServerDef that specifies a
single-process cluster containing a single task in a job called
"local".
| Args |
|---|
config
|
(Options.) A tf.compat.v1.ConfigProto that specifies default
configuration options for all sessions that run on this server.
|
start
|
(Optional.) Boolean, indicating whether to start the server after
creating it. Defaults to True.
|
join
View source
join()
Blocks until the server has shut down.
This method currently blocks forever.
| Raises |
|---|
tf.errors.OpError
|
Or one of its subclasses if an error occurs while
joining the TensorFlow server.
|
start
View source
start()
Starts this server.
| Raises |
|---|
tf.errors.OpError
|
Or one of its subclasses if an error occurs while
starting the TensorFlow server.
|
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TensorFlow 1 version
View source on GitHub