tf.distribute.experimental.rpc.Server
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A Server base class for accepting RPCs for registered tf.functions.
Functions can be registered on the server and are exposed via RPCs.
Methods
create
View source
@staticmethod
create(
rpc_layer, address
)
Create TF RPC server at given address.
Args |
rpc_layer
|
Communication layer between client and server. Only "grpc" rpc
layer is supported at the moment.
|
address
|
Address where RPC server is hosted.
|
Raises |
A ValueError if rpc_layer other than "grpc" is used. Only GRPC
is supported at the moment.
|
Example usage |
>>> import portpicker
>>> @tf.function(input_signature=[
... tf.TensorSpec([], tf.int32),
... tf.TensorSpec([], tf.int32)])
... def remote_fn(a, b):
... return tf.add(a, b)
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = tf.distribute.experimental.rpc.Server.create("grpc", address)
server.register("addition", remote_fn)
server.start()
|
register
View source
register(
method_name: str,
func: Union[def_function.Function, tf_function.ConcreteFunction]
)
Method for registering tf.function on server.
Registered methods can be invoked remotely from clients.
Args |
method_name
|
Name of the tf.function. Clients use this method_name to make
RPCs.
|
func
|
A tf.function or ConcreteFunction to register.
|
start
View source
start()
Starts the RPC server on provided address.
Server listens for new requests from client, once it is started.
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Last updated 2023-10-06 UTC.
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