Currently in rollout worker, we call restore_checkpoint repeatedly to load the latest model in memory. The restore checkpoint functions calls checkpoint_saver. Checkpoint saver uses GlobalVariablesSaver which does not release the references of the previous model variables. This leads to the situation where the memory keeps on growing before crashing the rollout worker.
This change avoid using the checkpoint saver in the rollout worker as I believe it is not needed in this code path.
Also added a test to easily reproduce the issue using CartPole example. We were also seeing this issue with the AWS DeepRacer implementation and the current implementation avoid the memory leak there as well.
NOTE: tensorflow framework works fine if mxnet is not installed in env, but mxnet will not work if tensorflow is not installed because of the code in network_wrapper.
