您好，我正在对 lstm rnn 单元使用以下函数。
def LSTM_RNN(_X, _istate, _weights, _biases):
# Function returns a tensorflow LSTM (RNN) artificial neural network from given parameters.
# Note, some code of this notebook is inspired from an slightly different
# RNN architecture used on another dataset:
# https://tensorhub.com/aymericdamien/tensorflow-rnn
# (NOTE: This step could be greatly optimised by shaping the dataset once
# input shape: (batch_size, n_steps, n_input)
_X = tf.transpose(_X, [1, 0, 2]) # permute n_steps and batch_size
# Reshape to prepare input to hidden activation
_X = tf.reshape(_X, [-1, n_input]) # (n_steps*batch_size, n_input)
# Linear activation
_X = tf.matmul(_X, _weights['hidden']) + _biases['hidden']
# Define a lstm cell with tensorflow
lstm_cell = rnn_cell.BasicLSTMCell(n_hidden, forget_bias=1.0)
# Split data because rnn cell needs a list of inputs for the RNN inner loop
_X = tf.split(0, n_steps, _X) # n_steps * (batch_size, n_hidden)
# Get lstm cell output
outputs, states = rnn.rnn(lstm_cell, _X, initial_state=_istate)
# Linear activation
# Get inner loop last output
return tf.matmul(outputs[-1], _weights['out']) + _biases['out']
该函数的输出存储在 pred 变量下。
pred = LSTM_RNN(x, istate, weights, biases)
但它显示以下错误。 （这表明张量对象是不可迭代的。）
这是错误图像链接 -https://i.stack.imgur.com/eXLjz.jpg https://i.stack.imgur.com/eXLjz.jpg
请帮助我解决这个问题，如果这个问题看起来很愚蠢，我深表歉意，因为我对 lstm 和张量流库相当陌生。
Thanks.
