Tensorflowonspark

- Allow use with `tensorflow-cpu` package.
- Dependency updates
- Minor fixes.

- Added option to defer releasing temporary socket/port to user map_function for cases where user code may not bind to the assigned port soon enough to avoid other processes binding to the same port, e.g. extensive pre-processing before invoking TF APIs.
- Updated screwdriver.cd build template.
- Trigger documentation publish after PyPI push.

- Added ability to disable spark barrier execution in TFParallel
- Updated with spark 3 + scala 2.12 dependencies
- Fixed documentation build

- Migrated build from travis-ci to screwdriver.cd

- Added support for port ranges in `TFOS_SERVER_PORT` environment variable.
- Updated `mnist/keras/mnist_tf.py` example with workaround for tensorflow datasets issue.
- Added more detailed error message for missing `executor_id`.
- Added unit tests for gpu allocation variants.

- Added support for Spark 3.0 GPU resources
- Updated to support Spark 2.4.5
- Fixed dataset ordering in `mnist_inference.py` examples (thanks to qsbao)
- Added optional environment variables to configure TF server/grpc ports and TensorBoard ports on executors
- Fixed bug with `TFNode.start_cluster_server` in backwards-compatibility code for TF1.x
- Fixed file conflict issue with `compat.export_saved_model` in TF2.1
- Removed support for Python 2.x