75cba1be3373908e6a1a971778a14e40b240ce4f,softqlearning/misc/nn.py,MLPFunction,__init__,#MLPFunction#Any#Any#Any#,213

Before Change

        self._name = name
        self._input_pls = input_pls
        self._layer_sizes = list(hidden_layer_sizes) + [1]

        self._output_t = self.get_output_for(*self._input_pls)

    def get_output_for(self, *inputs, reuse=False):

After Change

    def bias(n_units):
        return tf.get_variable(
            name="bias",
            shape=n_units,
            initializer=tf.zeros_initializer())

    def linear(x, n_units, postfix=None):
        input_size = x.shape[-1].value
        weight_name = "weight" + "_" + str(postfix) if postfix else "weight"
        weight = tf.get_variable(
            name=weight_name,

Instances