human
Can you provide a the Python code you requested given the following:
2.3 Curiosity-driven Exploration
assistant
#Here is the Python code you requested.
class MLP(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super().__init__()
        self.layers = nn.Sequential(
            nn.Linear(input_size, hidden_size),
            nn.ReLU(),
            nn.Linear(hidden_size, output_size)
        )
        
        def init_weights(tensor):
            if isinstance(tensor, nn.Linear):
                nn.init.xavier_uniform_(tensor.weight)
        
        self.layers.apply(init_weights)
            
    
    def forward(self, x):
        return self.layers(x)