- r2.**
permissions:
  contents: read

jobs:
  build:
    # Don't do this in forks, and if labeled, only for 'kokoro:force-run'
    if: github.repository == 'tensorflow/tensorflow' && (github.event.action != 'labeled' || (github.event.action == 'labeled' && github.event.label.name == 'kokoro:force-run'))
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      matrix:
        pyver: ['3.10']
    steps:

config_setting(
    name = "no_default_logger",
    define_values = {"no_default_logger": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "force_rtti",
    define_values = {
        "tf_force_rtti": "true",
    },
    visibility = ["//visibility:public"],
)

# Config setting for determining if we are building for Android.
config_setting(
    name = "android",

          (std::min)(n - copy_size, gcs_file->buffer.size());
      memcpy(buffer + copy_size, gcs_file->buffer.data(), remaining_copy);
      copy_size += remaining_copy;
    }
    if (copy_size < n) {
      // Forget the end-of-file flag to allow for clients that poll on the
      // same file.
      gcs_file->buffer_end_is_past_eof = false;
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read less bytes than requested");

*   TensorFlow Debugger (tfdbg) CLI: ncurses-based CLI for tfdbg v1 was removed.

*   TensorFlow now supports C++ RTTI on mobile and Android. To enable this feature, pass the flag `--define=tf_force_rtti=true` to Bazel when building TensorFlow. This may be needed when linking TensorFlow into RTTI-enabled programs since mixing RTTI and non-RTTI code can cause ABI issues.

  TF_DeleteTensor(value);
}

TEST_F(CApiAttributesTest, StringTensor) {
  // Create the string-Tensor "attribute" value.
  const char test_string[] =
      "borkborkborkborkborkborkborkbork";  // >24bytes to force heap alloc
  TF_TString tstr[1];
  TF_TString_Init(&tstr[0]);
  TF_TString_Copy(&tstr[0], test_string, sizeof(test_string) - 1);

  auto deallocator = [](void* data, size_t len, void* arg) {};

//   In C++ bool is a keyword while in C99 bool is a macro defined
//   in stdbool.h. It is possible for the two to be inconsistent.
//   For example, neither the C99 nor the C++11 standard force a byte
//   size on the bool type, so the macro defined in stdbool.h could
//   be inconsistent with the bool keyword in C++. Thus, the use
//   of stdbool.h is avoided and unsigned char is used instead.

-   we have to use the name `__mempcpy'.  */
-#   define mempcpy(dest, src, n) __mempcpy (dest, src, n)
-#  endif
-
-#  if !__GNUC_PREREQ (3, 0) || defined _FORCE_INLINES
-#   if _STRING_ARCH_unaligned
-#    ifndef _FORCE_INLINES
-#     define __mempcpy_args(src) \
-     ((const char *) (src))[0], ((const char *) (src))[2],		      \
-     ((const char *) (src))[4], ((const char *) (src))[6],		      \

  console.log(domain);
  return domain;
};

/** For trusted parters like Intel, we want to auto-run tests
    This allows us to reduce the delay to external partners
    Add Labels - kokoro:force-run
    The PR is also assigned to specific teams to fast track review
    Additional reviewers can be added manually based on PR contents
  @param {!object}

build:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --compiler=clang-cl
build:win_clang --linkopt=/FORCE:MULTIPLE
build:win_clang --host_linkopt=/FORCE:MULTIPLE
test:win_clang --linkopt=/FORCE:MULTIPLE
test:win_clang --host_linkopt=/FORCE:MULTIPLE

# Same config as above but for XLA, which has different toolchain paths
build:win_clang_xla --copt=/clang:-Weverything

      answer = raw_input(question)
    except NameError:
      answer = input(question)  # pylint: disable=bad-builtin
  except EOFError:
    answer = ''
  return answer


def symlink_force(target, link_name):
  """Force symlink, equivalent of 'ln -sf'.

  Args:
    target: items to link to.
    link_name: name of the link.
  """
  try:
    os.symlink(target, link_name)
  except OSError as e: