Source code for algorithms.policy.MLP

import torch.nn as nn


[docs]class MLP(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        '''

        :param input_size: input feature dimension
        :param hidden_size: hidden layer dimension
        :param output_size: output dimension
        '''
        super(MLP, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size[0])
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(hidden_size[0], hidden_size[1])
        self.fc3 = nn.Linear(hidden_size[1], output_size)

[docs]    def forward(self, x):
        out = self.fc1(x)
        out = self.relu(out)
        out = self.fc2(out)
        out = self.relu(out)
        out = self.fc3(out)
        return out