我运行示例代码recurrent_network.py。
我希望打印所有x,它是一个安置者。在函数中:RNN(x, weights, biases):
我该怎么办?
关键点:
x = tf.transpose(x, [1, 0, 2])
# Reshaping to (n_steps*batch_size, n_input)
x = tf.reshape(x, [-1, n_input])
# Split to get a list of 'n_steps' tensors of shape (batch_size, n_input)
x = tf.split(0, n_steps, x)