load("@python//3.12:defs.bzl", compile_pip_requirements_3_12 = "compile_pip_requirements")
load("@python//3.9:defs.bzl", compile_pip_requirements_3_9 = "compile_pip_requirements")
load("@updater_config_repository//:updater_config_repository.bzl", "REQUIREMENTS_FILE_NAME")

compile_pip_requirements_3_9(
    name = "requirements_3_9",
    extra_args = ["--allow-unsafe"],
    requirements_in = REQUIREMENTS_FILE_NAME,

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  NodeDef node_def_neg;
  ASSERT_TRUE(GetNodeDef(neg, &node_def_neg));
  EXPECT_EQ(string("add"), node_def_neg.input(0));

  // update edge of neg
  TF_UpdateEdge(graph, TF_Output{one, 0}, TF_Input{neg, 0}, s);

  ASSERT_TRUE(GetNodeDef(neg, &node_def_neg));
  EXPECT_EQ(string("one:0"), node_def_neg.input(0));

  // Clean up

load("@rules_python//python/pip_install:repositories.bzl", "pip_install_dependencies")

default_python_version = "3.10"

load(
    "//:updater_config_repository.bzl",
    "updater_config_repository",  # @unused
)

updater_config_repository(name = "updater_config_repository")

python_register_multi_toolchains(
    name = "python",
    default_version = default_python_version,
    ignore_root_user_error = True,

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.

      "ApiDefMap is not supported on mobile.");
  return nullptr;
#else
  mutex_lock l(api_def_map->lock);
  if (!api_def_map->update_docs_called) {
    api_def_map->api_def_map.UpdateDocs();
    api_def_map->update_docs_called = true;
  }
  string name_str(name, name_len);
  const auto* api_def = api_def_map->api_def_map.GetApiDef(name_str);
  if (api_def == nullptr) {

# This Workflow updates tensorflow/tools/toolchains/remote_config/configs.bzl
# to reference the most recent versions of the SIG Build Docker images.
name: Update RBE Configs
on:
  workflow_dispatch:

permissions:
  contents: read

jobs:
  rbe:
    name: Update RBE Configs
    runs-on: ubuntu-latest

// Dynamic cluster API.

// Update an existing context with a new set of servers defined in a ServerDef
// proto. Servers can be added to and removed from the list of remote workers
// in the context. A New set of servers identified by the ServerDef must be up
// when the context is updated.
//
// This API is for experimental usage and may be subject to change.

*   Solves an OOM issue on TPUs when XLA contexts use fused average updates
*   Updates `libjpeg-turbo` to `2.0.5` to handle
    [CVE-2020-13790](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-13790).
*   Updates `junit` to `4.13.1` to handle
    [CVE-2020-15250](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15250).
*   Updates `PCRE` to `8.44` to handle

    python tf_doctest.py --file=<file_path>
    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from
        [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch.

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
  # replace tensorflow to tf_nightly in the wheel name