description will be provided once it's integrated into presubmit.

### test_import_api_packages

This Python test verifies whether the API v2 packages can be imported from the
current build. It utilizes the `_api/v2/api_packages.txt` list of packages from
the local wheel file specified in the `requirements_lock_<python_version>.txt`.

Packages are imported one by one in alphabetical order during runtime.

build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Prevent double-compilation of some TF code, ref. b/183279666 (internal)
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code

bool_flag(
    name = "enable_registration_v2",
    build_setting_default = False,
    visibility = ["//visibility:public"],
)

config_setting(
    name = "registration_v1",
    flag_values = {":enable_registration_v2": "False"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "registration_v2",
    flag_values = {":enable_registration_v2": "True"},

        *   (since v2.7) `tf.math.segment_mean`
        *   (since v2.7) `tf.math.segment_prod`
        *   (since v2.7) `tf.math.segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_mean`
        *   (since v2.7) `tf.math.unsorted_segment_prod`
        *   (since v2.7) `tf.math.unsorted_segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_sqrt`

build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Use lld as the linker
build --linkopt="-fuse-ld=lld"
build --linkopt="-lm"
build --linkopt="-Wl,--undefined-version"

and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

#     dynamic_kernels:  Try to link all kernels dynamically (experimental).
#     dbg:              Build with debug info
#
# TF version options;
#     v2: Build TF v2
#
# Feature and Third party library support options:
#     xla:          Build TF with XLA
#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.