std::string dir = path;
  MaybeAppendSlash(&dir);
  for (const std::string& children : childrens) {
    const std::string& full_path = dir + children;
    DeleteFile(filesystem, full_path.c_str(), status);
    if (TF_GetCode(status) != TF_OK) {
      if (IsDirectory(filesystem, full_path.c_str(), status))
        // The object is a directory marker.
        (*undeleted_dirs)++;
      else

  if (undeleted_files == nullptr || undeleted_dirs == nullptr)
    return errors::FailedPrecondition(
        "DeleteRecursively must not be called with `undeleted_files` or "
        "`undeleted_dirs` set to NULL");

  if (ops_->delete_recursively == nullptr)
    return FileSystem::DeleteRecursively(dirname, token, undeleted_files,
                                         undeleted_dirs);

  TF_SessionOptions* opt = TF_NewSessionOptions();
  TF_Status* s = TF_NewStatus();
  const char* tags[] = {tensorflow::kSavedModelTagServe};
  TF_Graph* graph = TF_NewGraph();
  // NULL run_options and meta_graph_def should work.
  TF_Session* session = TF_LoadSessionFromSavedModel(
      opt, nullptr, saved_model_dir.c_str(), tags, 1, graph, nullptr, s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/tsl/c/tsl_status_internal.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"

  fi
fi

# Mac builds have some specific setup needs. See setup_macos.sh for details
if [[ "${OSTYPE}" =~ darwin* ]]; then
  source ./ci/official/utilities/setup_macos.sh
fi

# Create and expand to the full path of TFCI_OUTPUT_DIR
export TFCI_OUTPUT_DIR=$(realpath "$TFCI_OUTPUT_DIR")
mkdir -p "$TFCI_OUTPUT_DIR"

# In addition to dumping all script output to the terminal, place it into
# $TFCI_OUTPUT_DIR/script.log

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.
    * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using  `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).

*   `tf.math`

      looping.
  """
  default = environ_cp.get(var_name) or var_default
  full_query = '%s [Default is %s]: ' % (
      ask_for_var,
      default,
  )

  for _ in range(n_ask_attempts):
    val = get_from_env_or_user_or_default(environ_cp, var_name, full_query,
                                          default)
    if check_success(val):
      break

  ///
  /// Caller guarantees that:
  ///   * `paths` has exactly `num_files` entries.
  ///   * `statuses` is either null or an array of `num_files` non-null elements
  ///     of type `TF_Status*`.
  ///
  /// If `statuses` is not null, plugins must fill each element with detailed
  /// status for each file, as if calling `path_exists` on each one. Core

  // between calls to ShouldRecord and Accumulator), and its outputs
  // (`output_tensors`).
  //
  // If provided, a non-null `forward_function` will be used instead of the
  // backward function (`backward_function_getter` /
  // `backward_function_deleter`) to compute jvps for this operation. If
  // `forward_function` is null, a GradientTape is used on the backward function
  // to compute the jvp, which will waste computation when executing eagerly.

    }                                                                     \
  } while (0)

// Macro to verify that the field NAME of STRUCT_OBJ is not null.
#define TF_VALIDATE_NOT_NULL(STRUCT_NAME, STRUCT_OBJ, NAME)            \
  do {                                                                 \
    if (STRUCT_OBJ.NAME == 0) {                                        \