def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
scenes = list(map(lambda s: s.to_proto(), self.scenes))
analyzers = list(map(lambda a: a.to_proto(), self.analyzers))
msg.MergeFrom(
CommandConfigMsg(analyze_config=CommandConfigMsg.AnalyzeConfig(
task=task, scenes=scenes, analyzers=analyzers)))
return msg
def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
scenes = list(map(lambda s: s.to_proto(), self.scenes))
evaluators = list(map(lambda e: e.to_proto(), self.evaluators))
msg.MergeFrom(
CommandConfigMsg(eval_config=CommandConfigMsg.EvalConfig(
task=task, scenes=scenes, evaluators=evaluators)))
return msg
def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
backend = self.backend.to_proto()
scenes = list(map(lambda s: s.to_proto(), self.scenes))
msg.MergeFrom(
CommandConfigMsg(predict_config=CommandConfigMsg.PredictConfig(
task=task, backend=backend, scenes=scenes)))
return msg
def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
backend = self.backend.to_proto()
msg.MergeFrom(
CommandConfigMsg(
train_config=CommandConfigMsg.TrainConfig(
task=task, backend=backend)))
return msg
def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
backend = self.backend.to_proto()
train_scenes = list(map(lambda s: s.to_proto(), self.train_scenes))
val_scenes = list(map(lambda s: s.to_proto(), self.val_scenes))
msg.MergeFrom(
CommandConfigMsg(chip_config=CommandConfigMsg.ChipConfig(
task=task,
backend=backend,
train_scenes=train_scenes,
val_scenes=val_scenes)))
return msg
def to_proto(self):
msg = super().to_proto()
task = self.task.to_proto()
backend = self.backend.to_proto()
scene = self.scene.to_proto()
analyzers = list(map(lambda a: a.to_proto(), self.analyzers))
b = CommandConfigMsg.BundleConfig(task=task,
backend=backend,
scene=scene,
analyzers=analyzers)
msg.MergeFrom(CommandConfigMsg(bundle_config=b))
return msg