g4dn.xlarge) when installing Cortex.
gpufield in the
computeconfiguration for your API. One unit of GPU corresponds to one virtual GPU. Fractional requests are not allowed.
processes_per_replica> 1, TensorFlow-based models, and Python Predictor
processes_per_replica> 1 with TensorFlow-based models (including Keras) in the Python Predictor, loading the model in separate processes at the same time will throw a
CUDA_ERROR_OUT_OF_MEMORY: out of memoryerror. This is because the first process that loads the model will allocate all of the GPU's memory and leave none to other processes. To prevent this from happening, the per-process GPU memory usage can be limited. There are two methods: