将TensorFlow中的变量重新初始化为自定义值

Question

I want to initialize a w_gate tensor with a custom np.array as in the code below:

    w_init = np.ones(shape=(dim, self.config.nmodels)) / self.config.nmodels

    w_gate = tf.Variable(
        name="W",
        initial_value=w_init,
        dtype=tf.float32)

Every a certain number of train iterations, I want w_gate to be re-initialized again to the w_init array. For this, and based on Re-initialize variables in Tensorflow , I tried

sess.run(tf.variables_initializer([w_gate]))

inside my training loop. This line is executed every certain number of iterations. Although, w_gate doesn't seem to be re-initialized. What am I missing here?

Answer 1

Could you try this and check ?

w_gate_assign = tf.assign(w_gate, w_init)
sess.run(w_gate_assign)