tf.data.experimental.service.DispatchServer
An in-process tf.data service dispatch server.
tf.data.experimental.service.DispatchServer(
port, protocol=None, start=True
)
A tf.data.experimental.service.DispatchServer coordinates a cluster of tf.data.experimental.service.WorkerServers. When the workers start, they register themselves with the dispatcher.
dispatcher = tf.data.experimental.service.DispatchServer(port=0)
dispatcher_address = dispatcher.target.split("://")[1]
worker = tf.data.experimental.service.WorkerServer(
port=0, dispatcher_address=dispatcher_address)
dataset = tf.data.Dataset.range(10)
dataset = dataset.apply(tf.data.experimental.service.distribute(
processing_mode="parallel_epochs", service=dispatcher.target))
print(list(dataset.as_numpy_iterator()))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
When starting a dedicated tf.data dispatch process, use join() to block indefinitely after starting up the server.
dispatcher = tf.data.experimental.service.DispatchServer(port=5050)
dispatcher.join()
| Args | |
|---|---|
port |
Specifies the port to bind to. |
protocol |
(Optional.) Specifies the protocol to be used by the server. Acceptable values include "grpc", "grpc+local". Defaults to "grpc". |
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 | |
|---|---|
target |
Returns a target that can be used to connect to the server. The returned string will be in the form protocol://address, e.g. "grpc://localhost:5050". |
Methods
join
join()
Blocks until the server has shut down.
This is useful when starting a dedicated dispatch process.
dispatcher = tf.data.experimental.service.DispatchServer(port=5050)
dispatcher.join()
| Raises | |
|---|---|
tf.errors.OpError |
Or one of its subclasses if an error occurs while joining the server. |
start
start()
Starts this server.
dispatcher = tf.data.experimental.service.DispatchServer(port=0,
start=False)
dispatcher.start()
| Raises | |
|---|---|
tf.errors.OpError |
Or one of its subclasses if an error occurs while starting the server. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/data/experimental/service/DispatchServer