Cyclic computational graphs with Tensorflow or The

问题:

Both TensorFlow and Theano do not seem to support cyclic computational graphs, cyclic elements are implemented as recurrent cells with buffer and unrolling (RNN / LSTM cells), but this limitation is mostly related with the computation of back-propagation. I don't have a particular need for computing back-propagation but just the forward propagations.

Is there a way to ignore this limitation, or perhaps just to break down arbitrary computational graphs in acyclic components?

回答1:

TensorFlow does support cyclic computation graphs. The tf.while_loop() function allows you to specify a while loop with arbitrary subgraphs for the condition and the body of the loop, and the runtime will execute the loop in parallel. The tf.scan() function is a higher-level API that is similar to Theano's theano.scan() function. Both allow you to loop over tensors of dynamic size.