I am trying to build a software that runs Deepspeech inference along with another Tensorflow-based network.
However, when I ran my software, I find that the two tasks are simutaneously trying to allocate large chunks of memory on all 4 of my GPUs, starving each other of memory and cause cuDNN runtime errors.
But run the two models on two separate processes, each having 2 visible GPUs, they run just fine.
deepspeech-gpu pip package doesn’t depend on
tensorflow-gpu, I assume that
deepspeech-gpu has Tensorflow runtimes integrated, and the integrated Tensorflow runtime is conflicting with the Tensorflow that I manually installed via pip.
Is my assumption correct? If it is, is there a way to run Deepspeech on my existing Tensorflow installation?