4ef810643f162aebb1d9efd153a82e0dc9e9094e,garage/tf/policies/categorical_conv_policy.py,CategoricalConvPolicy,__init__,#CategoricalConvPolicy#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,16

Before Change

        self._l_prob = prob_network.output_layer
        self._l_obs = prob_network.input_layer
        self._f_prob = tensor_utils.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)

After Change

        self._name = name
        self._env_spec = env_spec
        self._prob_network_name = "prob_network"

        with tf.variable_scope(name, "CategoricalConvPolicy"):
            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=output_nonlinearity,
                    name="conv_prob_network",
                )

            with tf.name_scope(self._prob_network_name):
                out_prob = L.get_output(prob_network.output_layer)

            self._l_prob = prob_network.output_layer
            self._l_obs = prob_network.input_layer
            self._f_prob = tensor_utils.compile_function(
                [prob_network.input_layer.input_var], [out_prob])

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

            super(CategoricalConvPolicy, self).__init__(env_spec)

Instances