[requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater)
tool using the path to this wheel file.

### Hermetic Python

For details about hermetic Python and setting its toolchain version, see
[requirements updater readme](https://github.com/tensorflow/tensorflow/blob/master/ci/official/requirements_updater/README.md)

### Prerequisites for Local Testing

  tf_gcs_filesystem::ExpiringLRUCache<int> cache(
      1, 0, [&env]() { return env->NowSeconds(); });
  env->SetNowSeconds(1);
  // Verify that replacement of an existing element works, and updates the
  // timestamp of the entry.
  cache.Insert(key, 41);
  env->SetNowSeconds(2);
  cache.Insert(key, 42);
  // 1 second after the most recent insertion, the entry is still valid.
  env->SetNowSeconds(3);

*   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

#
#    - New environments like new CUDA versions, changes to manylinux,
#      compilers, etc. can cause undefined behavior such as build failures
#      or tests passing incorrectly.
#    - Automatic LLVM updates are known to extend build time even with
#      the cache; this is unavoidable.
export TFCI=py311,linux_x86,public_cache,disk_cache

# Recommended: Configure Docker. (Linux only)
#

# 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

  ASSERT_TRUE(worker_server1->Start().ok());

  // 5a. Update `ctx_0` with updated `server_def_0`.
  {
    server_def_0.set_task_index(0);
    string serialized_update = server_def_0.SerializeAsString();
    TF_Status* status = TF_NewStatus();
    TFE_ContextUpdateServerDefWithTimeout(ctx_0, 0, serialized_update.data(),
                                          serialized_update.size(),

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,

# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a
# nightly job. update_version.py affects TF_VER_SUFFIX, TF_VER_PYTHON, and
# TF_VER_FULL.

# Note: in awk, the command '/search/ {commands}' applies the commands to any line that

  ASSERT_TRUE(worker_server1->Start().ok());

  // 5a. Update `ctx_0` with updated `server_def_0`.
  {
    server_def_0.set_task_index(0);
    string serialized_update = server_def_0.SerializeAsString();
    TF_Status* status = TF_NewStatus();
    TFE_ContextUpdateServerDef(ctx_0, 0, serialized_update.data(),
                               serialized_update.size(), status);

    } else {
      // Remove the stale block and continue.
      RemoveFile_Locked(key.first);
    }
  }

  // Insert a new empty block, setting the bookkeeping to sentinel values
  // in order to update them as appropriate.
  auto new_entry = std::make_shared<Block>();
  lru_list_.push_front(key);
  lra_list_.push_front(key);
  new_entry->lru_iterator = lru_list_.begin();
  new_entry->lra_iterator = lra_list_.begin();