Networks.py 文件源码

def build(self, input_shape):
        self.input_spec = [InputSpec(shape=input_shape)]
        if self.stateful:
            self.reset_states()
        else:
            self.states = [K.random_normal(shape=(self.output_dim,), mean=0.5, std=0.5)]
        input_dim = input_shape[2]
        self.input_dim = input_dim
        self.W = self.init((input_dim, self.output_dim), name='{}_W'.format(self.name))
        self.U = self.inner_init((self.output_dim, self.output_dim), name='{}_U'.format(self.name))
        self.b = K.zeros((self.output_dim,), name='{}_b'.format(self.name))
        self.regularizers = []
        if self.W_regularizer:
            self.W_regularizer.set_param(self.W)
            self.regularizers.append(self.W_regularizer)
        if self.U_regularizer:
            self.U_regularizer.set_param(self.U)
            self.regularizers.append(self.U_regularizer)
        if self.b_regularizer:
            self.b_regularizer.set_param(self.b)
            self.regularizers.append(self.b_regularizer)
        self.trainable_weights = [self.W, self.U]
        if self.dale_ratio:
            self.non_trainable_weights = [self.Dale]
        if self.initial_weights is not None:
            self.set_weights(self.initial_weights)
            del self.initial_weights