#
# config_setting(
#     name = "chromiumos_arm64",
#     constraint_values = ["//third_party/bazel_platforms/os:chromiumos"],
#     values = {"cpu": "arm"},
#     visibility = ["//visibility:public"],
# )
#
# config_setting(
#     name = "chromiumos_armv7",
#     constraint_values = ["//third_party/bazel_platforms/os:chromiumos"],
#     values = {"cpu": "armeabi-v7a"},
#     visibility = ["//visibility:public"],
# )

1.  `envs/*` are lists of variables made with bash syntax. A user must set a
    `TFCI` env param pointing to a list of `env` files.
2.  `utilities/setup.sh`, initialized by all top-level scripts, reads and sets
    values from those `TFCI` paths.
    -   `set -a` / `set -o allexport` exports the variables from `env` files so
        all scripts can use them.
    -   `utilities/setup_docker.sh` creates a container called `tf` with all

TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you
are working with. When loading untrusted checkpoints, the values of the traced
variables from your model are also going to be untrusted. That means that if
your code interacts with the filesystem, network, etc. and uses checkpointed

    dispatch to logical ops. This brings them more in line with Python and NumPy
    behavior.
*   Adds `tf.SparseTensor.with_values`. This returns a new SparseTensor with the
    same sparsity pattern, but with new provided values. It is similar to the
    `with_values` function of `RaggedTensor`.
*   Adds `StatelessCase` op, and uses it if none of case branches has stateful
    ops.