Can JetRacer_ROS Kit run yolo and DQN simultanteously?

I bought JetRacer ROS KIT.
JetRacer use JETSON NANO B01 and Rasberi PI 2090 controller.

I want to run two network at the same time.
So, Can Jetracer run two network at a time?

Yolo → JetRacer → Run

DQN → JetRacer → run

Yolo and DQN → JetRacer → Run

Not A and B case, I want C case.
Yolo does not matter which version.

DQN network is
class Qnet(nn.Module):

def init(self):
super(Qnet, self).init()

self.fc1 = nn.Linear(4, 128) # 4 input states
self.fc2 = nn.Linear(128, 128)
self.fc3 = nn.Linear(128, 128)
self.fc4 = nn.Linear(128, 128)
self.fc5 = nn.Linear(128, 7)

def forward(self, x):

x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = F.relu(self.fc3(x))
x = F.relu(self.fc4(x))

x = self. fc5(x)

return x

Hi @dlwogns0207, seeing as JetRacer doesn’t support these out-of-the-box, I’m guessing you mean if you were to add them - in which case, is the DQN reinforcement learning model doing training at runtime, or inference only? Due to the simplicitly of the Qnet model you’ve defined, I think inference should be okay there in combination with YOLO (albeit at a reduced framerate perhaps). You can find some YOLOv3 benchmarks for Jetson Nano in this post:

I would start by attempting to run both the YOLO model you want and your DQN model at the same on your Nano and see what the performance is.

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