advanced use cases can also write their own custom
      `tf.train.experimental.ShardingCallback`s.

* `tf.train.CheckpointOptions`
    * Added `experimental_skip_slot_variables` (a boolean option) to skip
    restoring of optimizer slot variables in a checkpoint.

*   `tf.saved_model.SaveOptions`

    * `SaveOptions` now takes a new argument called

# END TF TEST SUITE OPTIONS

# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction

TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=
TFCI_NVIDIA_SMI_ENABLE=
TFCI_OUTPUT_DIR=
TFCI_PYCPP_SWAP_TO_BUILD_ENABLE=
TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS=
TFCI_PYTHON_VERSION=
TFCI_WHL_AUDIT_ENABLE=
TFCI_WHL_AUDIT_PLAT=
TFCI_WHL_BAZEL_TEST_ENABLE=
TFCI_WHL_IMPORT_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=