categorical_conv_policy.py 文件源码

def __init__(
            self,
            name,
            env_spec,
            conv_filters, conv_filter_sizes, conv_strides, conv_pads,
            hidden_sizes=[],
            hidden_nonlinearity=NL.rectify,
            output_nonlinearity=NL.softmax,
            prob_network=None,
    ):
        """
        :param env_spec: A spec for the mdp.
        :param hidden_sizes: list of sizes for the fully connected hidden layers
        :param hidden_nonlinearity: nonlinearity used for each hidden layer
        :param prob_network: manually specified network for this policy, other network params
        are ignored
        :return:
        """
        Serializable.quick_init(self, locals())

        assert isinstance(env_spec.action_space, Discrete)

        self._env_spec = env_spec

        if prob_network is None:
            prob_network = ConvNetwork(
                input_shape=env_spec.observation_space.shape,
                output_dim=env_spec.action_space.n,
                conv_filters=conv_filters,
                conv_filter_sizes=conv_filter_sizes,
                conv_strides=conv_strides,
                conv_pads=conv_pads,
                hidden_sizes=hidden_sizes,
                hidden_nonlinearity=hidden_nonlinearity,
                output_nonlinearity=NL.softmax,
                name="prob_network",
            )

        self._l_prob = prob_network.output_layer
        self._l_obs = prob_network.input_layer
        self._f_prob = ext.compile_function(
            [prob_network.input_layer.input_var],
            L.get_output(prob_network.output_layer)
        )

        self._dist = Categorical(env_spec.action_space.n)

        super(CategoricalConvPolicy, self).__init__(env_spec)
        LasagnePowered.__init__(self, [prob_network.output_layer])