foo.py

def __init__(self, config):
        self.n_steps = self.config.hyperparams
        self.n_input, self.n_hidden =  4, 20
        self.lstm = tf.contrib.rnn.BasicLSTMCell(self.n_hidden, forget_bias=1.0, state_is_tuple=False)
    
def neural_search(self):
        state = tf.Variable(tf.zeros(shape=[4]))
        inp = tf.Variable(tf.random_normal(shape=[4]))
        output = list()
        for _ in range(self.n_steps):
            inp, state = self.lstm(inp, state)
            inp = tf.nn.softmax(tf.matmul(inp, self.Wc) + self.bc)
            output.append(inp)
        out = [utils.max(output[0]), utils.max(output[1]), utils.max(output[2]), utils.max(output[3]), utils.max(output[4]), utils.max(output[5])]
        return out, output[-1]