# and also repacks libtensorflow-src.jar into a standardized format.

# Helper function to copy a srcjar after moving any source files
# directly under the root to the "maven-style" src/main/java layout
#
# Source files generated by annotation processors appear directly
# under the root of srcjars jars created by bazel, rather than under
# the maven-style src/main/java subdirectory.
#
# Bazel manages annotation generated source as follows: First, it

    $zulu_extracted_path = \"c:/temp/\" + [IO.Path]::GetFileNameWithoutExtension($zulu_url); \
    $zulu_root = \"c:/openjdk\"; \
    (New-Object Net.WebClient).DownloadFile($zulu_url, $zulu_zip); \
    [System.IO.Compression.ZipFile]::ExtractToDirectory($zulu_zip, \"c:/temp\"); \
    Move-Item $zulu_extracted_path -Destination $zulu_root; \
    Remove-Item $zulu_zip; \
    $old_path = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\"); \

  """
  makefile_download_dir = os.path.join(_TF_WORKSPACE_ROOT, 'tensorflow',
                                       'contrib', 'makefile', 'downloads')
  if os.path.isdir(makefile_download_dir):
    for root, _, filenames in os.walk(makefile_download_dir):
      for f in filenames:
        if f.endswith('BUILD'):
          os.remove(os.path.join(root, f))


def get_var(environ_cp,
            var_name,

# Register multi toolchains
load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "pip_parse")

pip_parse(
    name = "pypi",

load(
    "//tensorflow:tensorflow.bzl",
    "if_libtpu",
    "tf_cuda_cc_test",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup")
load(
    "//tensorflow/core/platform:build_config_root.bzl",
    "tf_cuda_tests_tags",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

# Library of gradient functions.
package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],

# Please note that MKL on MacOS is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl --define=build_with_openmp=true
build:mkl -c opt

# copybara:comment_begin(oss-only)
copy_file(
    name = "root_init_gen",
    src = select({
        "api_version_2": "_api/v2/v2.py",
        "//conditions:default": "_api/v1/v1.py",
    }),
    out = "__init__.py",
)

genrule(
    name = "virtual_root_init_gen",
    srcs = select({
        "api_version_2": [":virtual_root_template_v2.__init__.py"],

// TFE_ContextUpdateServerDefWithTimeout to be simple wrappers around the same
// C++ function.
// Retries are used for CreateContext calls, which is used in
// ParameterServerStrategy initialization to be robust to worker preemption.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeoutAndRetries(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,

        didn't have the keys sorted, the keys and values were not being printed
        in accordance with their correct mapping.
*   `tf.train.Checkpoint`:
    *   Now accepts a `root` argument in the initialization, which generates a
        checkpoint with a root object. This allows users to create a
        `Checkpoint` object that is compatible with Keras `model.save_weights()`