models/perception_agent.py

import torch
import torch.nn as nn

class PerceptionAgent(nn.Module):
    def __init__(self, config):
        super(PerceptionAgent, self).__init__()
        self.cnn_layers = nn.Sequential(
            nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2, stride=2),
            # Additional layers can be defined based on config
        )
        self.fc_layers = nn.Sequential(
            nn.Linear(16 * 32 * 32, 256),
            nn.ReLU(),
            nn.Linear(256, config["perception_output_size"])
        )

    def forward(self, x):
        x = self.cnn_layers(x)
        x = x.view(x.size(0), -1)
        x = self.fc_layers(x)
        return x