rtn.py 文件源码

def __init__(self, output_dim,
                 init='glorot_uniform', inner_init='orthogonal',
                 activation='tanh', inner_activation='hard_sigmoid',
                 W_regularizer=None, U_regularizer=None, b_regularizer=None,
                 shape_key=None, dropout_W=0., dropout_U=0., **kwargs):
        self.output_dim = output_dim
        self.init = initializations.get(init)
        self.inner_init = initializations.get(inner_init)
        self.activation = activations.get(activation)
        self.inner_activation = activations.get(inner_activation)
        self.W_regularizer = regularizers.get(W_regularizer)
        self.U_regularizer = regularizers.get(U_regularizer)
        self.b_regularizer = regularizers.get(b_regularizer)
        self.dropout_W, self.dropout_U = dropout_W, dropout_U
        self.shape_key = shape_key or {}

        if self.dropout_W or self.dropout_U:
            self.uses_learning_phase = True
        kwargs['consume_less'] = 'gpu'
        super(RTTN, self).__init__(**kwargs)

        self.num_actions = 4