'''
 Repository rule to set some environment variables.
 Can be set via build parameter "--repo_env=<VARIABLE_NAME>=<value>"
 e.g "--repo_env=REQUIREMENTS_FILE_NAME=requirements.in"

 List of variables:
 REQUIREMENTS_FILE_NAME
'''

def _updater_config_repository_impl(repository_ctx):
    repository_ctx.file("BUILD", "")
    requirements_file_name = repository_ctx.os.environ.get("REQUIREMENTS_FILE_NAME", "requirements.in")
    repository_ctx.file(

# variables in it, OR may be left empty if the user has already exported the
# relevant variables in their environment. Because of 'set -o allexport' above
# (which is equivalent to "set -a"), every variable in the file is exported
# for other files to use.
#
# Separately, if TFCI is set *and* there are also additional TFCI_ variables

# Note: this file gets sourced in utilities/setup.sh, which has "set -u"
# (error on undefined variables). This ensures that (a) every TFCI variable
# has an explicit default value, and (b) no script can accidentally use a
# variable that doesn't exist. Please keep this list in alphabetical order.
#
# Find usage in scripts with e.g.:
#   cd ci/official

        with:
          registry: gcr.io
          username: _json_key
          password: ${{ secrets.GCP_CREDS }}
      -
        name: Generate variables for cache busting and tag naming
        run: |
          echo "DATE=$(date +'%Y-%m-%d')" >> "$GITHUB_OUTPUT"
          # Converts r2.9 to just 2.9
          echo "REF=$(echo $GITHUB_REF_NAME | sed 's/r//g')" >> "$GITHUB_OUTPUT"

  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  // Create one variable per task.
  TFE_TensorHandle* h0 = TestVariable(ctx, 1.0, task1_name);
  TFE_TensorHandle* h1 = TestVariable(ctx, 2.0, task2_name);
  TFE_TensorHandle* h2 = TestVariable(ctx, 3.0, task0_name);

  // Add a sync point to make sure that variables have been initialized
  // before the function execution starts.

namespace tensorflow {
namespace parallel_device {

// A helper for performing common operations on variables. A much more
// restricted stand-in for tf.Variable in Python.
class Variable {
 public:
  // Construct a Variable from a resource-dtype TFE_TensorHandle and an
  // indication of the dtype of the variable's value.
  //
  // Note that creating this resource-dtype handle can fail, so `Create` is a

          uint64_t stat_cache_max_age, size_t stat_cache_max_entries);
} GCSFile;

// This function is used to initialize a filesystem without the need of setting
// manually environement variables.
void InitTest(TF_Filesystem* filesystem, bool compose, uint64_t block_size,
              size_t max_bytes, uint64_t max_staleness,
              uint64_t stat_cache_max_age, size_t stat_cache_max_entries,

  // Create a variable handle (uninitialized to start) placed on the parallel
  // device.
  std::function<void(Variable*)> variable_deleter = [&](Variable* to_delete) {
    to_delete->Destroy(context, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
    delete to_delete;
  };
  std::unique_ptr<Variable, decltype(variable_deleter)> variable(

// MakeCleanup(f) returns an RAII cleanup object that calls 'f' in its
// destructor. The easiest way to use MakeCleanup is with a lambda argument,
// capturing the return value in an 'auto' local variable. Most users will not
// need more sophisticated syntax than that.
//
// Example:
//   void func() {
//     FILE* fp = fopen("data.txt", "r");
//     if (fp == nullptr) return;

# limitations under the License.
# ==============================================================================
# Variables containing version strings extracted from the canonical sources:
# 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