model.py

import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import reduce

class QNetwork(nn.Module):
    """Actor (Policy) Model."""

    def __init__(self, state_size, action_size, seed, fc1_units=128, fc2_units=64):
        """Initialize parameters and build model.
        Params
        ======
            state_size (int): Dimension of each state
            action_size (int): Dimension of each action
            seed (int): Random seed
        """
        super(QNetwork, self).__init__()
        self.seed = torch.manual_seed(seed)
        
        self.fc = nn.Sequential(
            nn.Linear(state_size, fc1_units),
            nn.ReLU(),
            nn.Linear(fc1_units, fc2_units),
            nn.ReLU(),
            nn.Linear(fc2_units, action_size))
        
    def forward(self, state):
        """Build a network that maps state -> action values."""
        return self.fc(state)