#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".

build:android --dynamic_mode=off

# Sets the default Apple platform to macOS.
build:macos --apple_platform_type=macos

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
build:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64
build:macos_arm64 --macos_minimum_os=11.0

#
#   export TFCI=...
#   export TF_BISECT_SCRIPT=ci/official/any.sh
#   export TF_BISECT_GOOD=a_good_commit_sha
#   export TF_BISECT_BAD=a_failing_commit_sha
#   export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#   export TF_ANY_MODE=test
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/
export TFCI="$(echo $TFCI | sed 's/,nightly_upload/,public_cache,disk_cache/')"

#### Running sanity check

If you have Docker installed on your system, you can perform a sanity check on
your changes by running the command:

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

  system_specific_test_config(environ_cp)

  configure_ios(environ_cp)

  print('Preconfigured Bazel build configs. You can use any of the below by '
        'adding "--config=<>" to your build command. See .bazelrc for more '
        'details.')
  config_info_line('mkl', 'Build with MKL support.')
  config_info_line(
      'mkl_aarch64',

#
# 1. RUN, TEST, OR BUILD BAZEL TARGET(S) WITHIN A TFCI ENVIRONMENT
#    To use:
#       export TFCI=ci/official/envs/env_goes_here
#       export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#       export TF_ANY_MODE="test" or "build" or "run" (default: "test")
#       ./any.sh
#
# 2. RUN ANY OTHER SCRIPT AND ENV WITH NO SIDE EFFECTS (NO UPLOADS)
#    To use:

    *   Display summaries of numeric tensor values with the `-s` flag to command
        `print_tensor` or `pt`.
    *   Display feed values with the `print_feed` or `pf` command and clickable
        links in the curses UI.
    *   Runtime profiler at the op level and the Python source line level with
        the `run -p` command.
*   Initial release of the statistical distribution library `tf.distributions`.

# On Linux, tell the linker (-Wl,<option>) to use a version script that
# excludes all but a subset of function names.
# On MacOS, the linker does not support version_script, but has an
# an "-exported_symbols_list" command.  -z defs disallows undefined
# symbols in object files.

tf_cc_shared_object(
    name = "tensorflow",
    linkopts = select({
        "//tensorflow:macos": [

  alias realpath=grealpath
  alias stat=gstat
  # By default, aliases are only expanded in interactive shells, which means
  # that they are not substituted for their corresponding commands in shell
  # scripts. By setting "expand_aliases", we enable alias expansion in
  # non-interactive shells as well.
  shopt -s expand_aliases
else
  echo '==TFCI==: Error: Cannot find path to grealpath or gstat'