def GetResults(self, request, context):
if request.comp_id >= len(self.results):
return hetr_pb2.GetResultsReply(status=False)
pb_results = []
for r in self.results[request.comp_id]:
pb_val = hetr_pb2.Value()
if is_scalar_type(r):
assign_scalar(pb_val.scalar, r)
else:
pb_val.tensor.CopyFrom(tensor_to_protobuf(r))
pb_results.append(pb_val)
return hetr_pb2.GetResultsReply(status=True, results=pb_results)
def feed_input(self, values):
logger.info("client: feed input")
pb_values = []
for v in values:
pb_val = hetr_pb2.Value()
if is_scalar_type(v):
assign_scalar(pb_val.scalar, v)
else:
pb_val.tensor.CopyFrom(tensor_to_protobuf(v))
pb_values.append(pb_val)
self.feed_input_response_future = self.RPC.FeedInput.future(
hetr_pb2.FeedInputRequest(comp_id=self.comp_id, values=pb_values),
_TIMEOUT_SECONDS)
def feed_input(self, values):
pb_values = []
for v in values:
pb_val = hetr_pb.Value()
if is_scalar_type(v):
assign_scalar(pb_val.scalar, v)
else:
pb_val.tensor.CopyFrom(tensor_to_protobuf(v))
pb_values.append(pb_val)
response = self.RPC.FeedInput(
hetr_pb2.FeedInputRequest(comp_id=self.comp_id, values=pb_values),
_TIMEOUT_SECONDS)
if not response.status:
raise RuntimeError("RPC feed_input request failed!")
def GetResults(self, request, context):
logger.debug("server: get_results")
if request.comp_id not in self.results:
message = 'unknown computation id {}'.format(request.comp_id)
return hetr_pb2.GetResultsReply(status=False, message=message)
try:
pb_results = []
for r in self.results[request.comp_id]:
pb_val = hetr_pb2.Value()
if is_scalar_type(r):
assign_scalar(pb_val.scalar, r)
else:
pb_val.tensor.CopyFrom(tensor_to_protobuf(r))
pb_results.append(pb_val)
return hetr_pb2.GetResultsReply(status=True, results=pb_results)
except Exception:
return hetr_pb2.GetResultsReply(status=False, message=traceback.format_exc())
def test_scalar_to_protobuf():
orig_tensor = np.float32(12)
pb_tensor = ser.tensor_to_protobuf(orig_tensor)
py_tensor = ser.pb_to_tensor(pb_tensor)
np.testing.assert_allclose(orig_tensor, py_tensor)
def test_tensor_to_protobuf():
orig_tensor = np.arange(12, dtype=np.float32).reshape(3, 4)
pb_tensor = ser.tensor_to_protobuf(orig_tensor)
py_tensor = ser.pb_to_tensor(pb_tensor)
np.testing.assert_allclose(orig_tensor, py_tensor)
