def call(self,
method_name: str,
args: Optional[Sequence[core_tf_types.Tensor]] = None,
output_specs=None,
timeout_in_ms=0):
"""Method to invoke remote registered functions on the connected server.
Server should be started before making an RPC Call.
Args:
method_name: Registered method to invoke on Server.
args: Input arguments for the method.
output_specs: Output specs for the output from method.
timeout_in_ms: Timeout for this call. If 0, default client timeout will be
used.
Returns:
StatusOrResult object. This function issues the RPC call to server, it
does not block for the duration of RPC. Please call is_ok, get_error or
get_value methods on the returned object to blocked till RPC finishes.
"""
if args is None:
args = []
status_or, deleter = gen_rpc_ops.rpc_call(
self._client_handle,
args=nest.flatten(args),
method_name=method_name,
timeout_in_ms=timeout_in_ms)
return StatusOrResult(status_or, deleter, output_specs)
def call_wrapper(*args, timeout_in_ms=0):
status_or, deleter = gen_rpc_ops.rpc_call(
client_handle,
args=validate_and_get_flat_inputs(*args),
method_name=method_name,
timeout_in_ms=timeout_in_ms)
return StatusOrResult(status_or, deleter, output_specs)
def call_blocking_wrapper(*args, timeout_in_ms=0):
status_or, deleter = gen_rpc_ops.rpc_call(
client_handle,
args=validate_and_get_flat_inputs(*args),
method_name=method_name,
timeout_in_ms=timeout_in_ms)
status_or = StatusOrResult(status_or, deleter, output_specs)
if status_or.is_ok():
return status_or.get_value()
else:
error_code, error_msg = status_or.get_error()
raise errors.exception_type_from_error_code(
error_code.numpy())(None, None, error_msg.numpy())
def call(self,
method_name: str,
args: Optional[Sequence[core_tf_types.Tensor]] = None,
output_specs=None):
"""Method to invoke remote registered functions on the connected server.
Server should be started before making an RPC Call.
Args:
method_name: Registered method to invoke on Server.
args: Input arguments for the method.
output_specs: Output specs for the output from method.
For example, if tf function is:
@tf.function(input_signature=[
tensor_spec.TensorSpec([], tf.int32),
tensor_spec.TensorSpec([], tf.int32)
])
def multiply_fn(a, b):
return tf.math.multiply(a, b)
output_spec is: tf.TensorSpec((), tf.int32)
If you have access to TF Function, the output specs can be generated
from tf.function by calling:
output_specs = tf.nest.map_structure(tf.type_spec_from_value,
tf_function.get_concrete_function().structured_outputs)
Returns:
StatusOrResult object. This function issues the RPC call to server, it
does not block for the duration of RPC. Please call is_ok, get_error or
get_value methods on the returned object to blocked till RPC finishes.
"""
if args is None:
args = []
status_or, deleter = gen_rpc_ops.rpc_call(self._client_handle,
args=nest.flatten(args),
method_name=method_name)
return StatusOrResult(status_or, deleter, output_specs)