LSTM_model_1.py 文件源码

def RNN(x, weights, biases):
    x = tf.transpose(x, [1, 0, 2])
    x = tf.reshape(x, [-1, n_input])
    x = tf.split(axis=0, num_or_size_splits=n_steps, value=x)
    lstm_cell = rnn.BasicLSTMCell(n_hidden, forget_bias=1.0)
    outputs, states = rnn.static_rnn(lstm_cell, x, dtype=tf.float32)
    return tf.matmul(outputs[-1], weights['out']) + biases['out']