jEyeRL/models.py at main · jIskCoder/jEyeRL · GitHub

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import torch
import torch.nn as nn
import torch.nn.functional as F


class Critic(nn.Module):

    def __init__(self, obs_dim, action_dim):
        super(Critic, self).__init__()

        self.obs_dim = obs_dim
        self.action_dim = action_dim

        self.linear1 = nn.Linear(self.obs_dim+ self.action_dim, 1024)
        self.linear2 = nn.Linear(1024,  512)
        self.linear3 = nn.Linear(512, 300)
        self.linear4 = nn.Linear(300, 1)

    def forward(self, x, a):
        #x = F.relu(self.linear1(x))
        xa_cat = torch.cat([x,a], 1)
        xa = F.relu(self.linear1(xa_cat))
        xa = F.relu(self.linear2(xa))
        xa = F.relu(self.linear3(xa))
        qval = self.linear4(xa)

        return qval

class Actor(nn.Module):

    def __init__(self, obs_dim, action_dim):
        super(Actor, self).__init__()

        self.obs_dim = obs_dim
        self.action_dim = action_dim

        self.linear1 = nn.Linear(self.obs_dim, 512)
        self.linear2 = nn.Linear(512, 128)
        self.linear3 = nn.Linear(128, self.action_dim)

    def forward(self, obs):
        x = F.relu(self.linear1(obs))
        x = F.relu(self.linear2(x))
        x = torch.tanh(self.linear3(x))

        return x