public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }
  bool UseFunction() const { return std::get<2>(GetParam()); }
};

TEST_P(CppGradients, TestReluGrad) {
  status_ = registry_.Register("Relu", ReluRegisterer);
  ASSERT_EQ(errors::OK, status_.code()) << status_.message();

  auto ReluGradModel = BuildGradModel(ReluModel, registry_);

  REGISTER_OP("CApiAttributesTestOpList" #type)               \
      .Attr("v: list(" #type ")")                             \
      .SetShapeFn(tensorflow::shape_inference::UnknownShape)
ATTR_TEST_REGISTER_OP(string);
ATTR_TEST_REGISTER_OP(int);
ATTR_TEST_REGISTER_OP(float);
ATTR_TEST_REGISTER_OP(bool);
ATTR_TEST_REGISTER_OP(type);
ATTR_TEST_REGISTER_OP(shape);
ATTR_TEST_REGISTER_OP(tensor);

)

updater_config_repository(name = "updater_config_repository")

python_register_multi_toolchains(
    name = "python",
    default_version = default_python_version,
    ignore_root_user_error = True,
    python_versions = [
        "3.9",
        "3.10",
        "3.11",
        "3.12",
    ],
    register_coverage_tool = True,
)

)

python_repository(name = "python_version_repo")

load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION")

# 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,
)

py_repositories()

load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load
load(
    "//tensorflow/tools/toolchains/python:python_repo.bzl",
    "python_repository",
)

python_repository(name = "python_version_repo")

load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION")

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,

#include "tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Register the POSIX filesystems statically.
// Return value will be unused
bool StaticallyRegisterLocalFilesystems() {
  TF_FilesystemPluginInfo info;
  TF_InitPlugin(&info);

   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.

   ```
      load("@python//3.11:defs.bzl",

        immediate_execution_ctx_.get(), 1.0f, &x2_raw);
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();
    x2.reset(x2_raw);
  }

  status_ = registry_.Register("IdentityN", IdentityNRegisterer);
  ASSERT_EQ(errors::OK, status_.code()) << status_.message();
  auto IdentityNGradModel = BuildGradModel(IdentityNModel, registry_);

  std::vector<AbstractTensorHandle*> outputs(2);

  string name_;
};

static TracingContext* GraphTracingFactory(const char* name, TF_Status* s) {
  return new GraphContext(name);
}

// Register the tracing implemented in this file as the default tracing engine.
static bool register_tracing = [] {
  RegisterTracingEngineFactory("graphdef", GraphTracingFactory);
  SetDefaultTracingEngine("graphdef").IgnoreError();
  return true;
}();

# When cross-compiling with RBE, we need to copy the macOS sysroot to be
# inside the TensorFlow root directory. We then define them as a filegroup
# target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel
# can register it as an input to compile/link actions and send it to the remote
# VMs when needed.
# TODO(b/316932689): Avoid copying and replace with a local repository rule.
if [[ "$TFCI_MACOS_CROSS_COMPILE_ENABLE" == 1 ]]; then