def __init__(self, layers, input_shape, output_shape):
super(DecomposedModel, self).__init__()
layer_modules, input_shape = generate_layers(input_shape, layers)
layer_modules["OutputLayer"] = nn.Linear(int(np.prod(input_shape)),
output_shape)
self.layers = nn.Sequential(layer_modules)
self.layers.apply(weights_initialize)
def __init__(self, network_config):
super(_DQNModel, self).__init__()
layer_modules, input_shape = generate_layers(
network_config.input_shape, network_config.layers)
layer_modules["OutputLayer"] = nn.Linear(int(np.prod(input_shape)),
network_config.output_shape)
self.layers = nn.Sequential(layer_modules)
self.layers.apply(weights_initialize)