I am developing a RNN and am using Tensorflow 1.1. I got the following error:
tensorflow.python.framework.errors_impl.InvalidArgumentError: The node 'model/att_seq2seq/encode/pocmru_rnn_encoder/rnn/while/Variable/Assign' has inputs from different frames. The input 'model/att_seq2seq/encode/pocmru_rnn_encoder/rnn/while/Identity_3' is in frame 'model/att_seq2seq/encode/pocmru_rnn_encoder/rnn/while/model/att_seq2seq/encode/pocmru_rnn_encoder/rnn/while/'. The input 'model/att_seq2seq/encode/pocmru_rnn_encoder/rnn/while/Variable' is in frame ''.
The error is caused by the lambda function in dynamic rnn method and a piece of code in my RNN.
- tensorflow rnn.py "dynamic_rnn / _dynamic_rnn_loop / _time_step" that using a lambda function to call RNN.call method to loop through all inputs.
- my code :
if type(myObject) != tf.Variable: tp = tf.Variable(myObject, validate_shape=False) else: tp = myObject
Logically, i repeatedly use tf.scatter_nd_update to update myObject. The pseudo code would be like myObject = scatter_nd_update(myObject, indices, updates). Since tf.scatter_nd_update requires Variable as argument and returns tensor, I need to wrap tensor into Variable. Hence the code above (test variable and then wrap). How should I modify my code to make it work? Thanks!
