Refactor how GPU and CPU environments are configured for TensorFlow 2.0
Please refer to the documentation to understand which environment variables to set in what scenarios. A couple of examples are shown below as well:
# This specifies to use 1024 MB of memory from GPU with logical ID 0 and 2048 MB of memory from GPU with logical ID 1
TF_GPU_MEMORY_ALLOC="0:1024, 1:2048"
# Specifies that at most 3 CPU threads can be used to parallelize multiple non-blocking operations
TF_INTER_OP_PARALLELISM_THREADS="3"
# Specifies that at most 2 CPU threads can be used to parallelize a particular operation.
TF_INTRA_OP_PARALLELISM_THREADS="2"