# buildifier: disable=load-on-top

workspace(name = "requirements_updater")

# buildifier: disable=load-on-top

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [

#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

load("@//tensorflow:workspace2.bzl", "tf_workspace2")

tf_workspace2()

# buildifier: disable=load-on-top

workspace(name = "wheel_test")

# buildifier: disable=load-on-top

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [
        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",

licenses(["notice"])  # Apache 2.0

filegroup(
    name = "model_files",
    srcs = glob(
        [
            "**/*",
        ],
        exclude = [
            "**/BUILD",
            "**/WORKSPACE",
            "**/LICENSE",
            "**/*.zip",
        ],
    ),

  if is_windows():
    set_windows_build_flags(environ_cp)

  if get_var(environ_cp, 'TF_SET_ANDROID_WORKSPACE', 'android workspace', False,
             ('Would you like to interactively configure ./WORKSPACE for '
              'Android builds?'), 'Searching for NDK and SDK installations.',
             'Not configuring the WORKSPACE for Android builds.'):
    create_android_ndk_rule(environ_cp)
    create_android_sdk_rule(environ_cp)

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# The requirements updater has its own WORKSPACE file

   `tensorflow/tools/toolchains/python/python_repo.bzl`. \
   While this isn't necessary for running the updater, it is required for
   actually using the new version with Tensorflow.

2) In the `WORKSPACE` file, add the new version to the `python_versions`
   parameter of the `python_register_multi_toolchains` function.

3) In the `BUILD.bazel` file, add a load statement for the new version, e.g.

   ```

build:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc
try-import %workspace%/xla_configure.bazelrc

# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user

# Here are bazelrc configs for release builds
# Build TensorFlow v2.
test:release_base --test_size_filters=small,medium

/tensorflow/lite/tools/make/gen/**
/api_init_files_list.txt
/estimator_api_init_files_list.txt
*.whl

# Android
.gradle
.idea
*.iml
local.properties
gradleBuild

# iOS
*.pbxproj
*.xcworkspace
/*.podspec
/tensorflow/lite/**/coreml/**/BUILD
/tensorflow/lite/**/ios/BUILD
/tensorflow/lite/**/objc/BUILD
/tensorflow/lite/**/swift/BUILD
/tensorflow/lite/examples/ios/simple/data/*.tflite

    which case remember to change the directory from `/root` to `/tensorflow`
    once you get into the running container so `bazel` can find the `tensorflow`
    workspace).

    you can do this by using the following command. As an example-

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
    ```