labels-to-remove-when-unstale: 'stat:awaiting response'
          only-labels: "stat:awaiting response"
          stale-issue-message: > 
            This issue is stale because it has been open for 7 days with no activity.
            It will be closed if no further activity occurs. Thank you.
          close-issue-message: >

  # Write tools/python_bin_path.sh
  with open(
      os.path.join(_TF_WORKSPACE_ROOT, 'tools', 'python_bin_path.sh'),
      'w') as f:
    f.write('export PYTHON_BIN_PATH="{}"'.format(python_bin_path))


def reset_tf_configure_bazelrc():
  """Reset file that contains customized config settings."""
  open(_TF_BAZELRC, 'w').close()


def cleanup_makefile():

static void NewRandomAccessFile(const TF_Filesystem* filesystem,
                                const char* path, TF_RandomAccessFile* file,
                                TF_Status* status) {
  int fd = open(path, O_RDONLY);
  if (fd < 0) {
    TF_SetStatusFromIOError(status, errno, path);
    return;
  }

  struct stat st;
  fstat(fd, &st);
  if (S_ISDIR(st.st_mode)) {

  bool found_neg = false;
  size_t pos = 0;
  TF_Operation* oper;
  while ((oper = TF_GraphNextOperation(graph, &pos)) != nullptr) {
    if (oper == feed) {
      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;
    } else if (oper == three) {
      EXPECT_FALSE(found_scalar_const);
      found_scalar_const = true;
    } else if (oper == add) {
      EXPECT_FALSE(found_add);
      found_add = true;

selects.config_setting_group(
    name = "is_cuda_enabled_and_windows",
    match_all = [
        ":is_cuda_enabled",
        ":windows",
    ],
)

# Config setting to use in select()s to distinguish open source build from
# google internal build on configurable attributes.
#
# For non-configurable distinction between OSS and Google builds, see
# `if_oss()` and `if_google()` macros in tensorflow.bzl.
config_setting(

const char* TF_OperationName(TF_Operation* oper) {
  return oper->node.name().c_str();
}

const char* TF_OperationOpType(TF_Operation* oper) {
  return oper->node.type_string().c_str();
}

const char* TF_OperationDevice(TF_Operation* oper) {
  return oper->node.requested_device().c_str();
}

int TF_OperationNumOutputs(TF_Operation* oper) {
  return oper->node.num_outputs();
}

        -  It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own!
        -  If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.
        -  As a workaround, you could import the same private symbol keras `keras.src`, but keep in mind the `src` namespace is not stable and those APIs may change or be removed in the future.

    return absl::OkStatus();
  }

  tensorflow::FullTypeDef FullType() const override {
    const FullTypeDef* ft;
    mutex_lock l(graph_->mu);
    graph_->graph.NodeType(output_.oper->node.name(), &ft);
    if (ft == nullptr) {
      return FullTypeDef();
    } else {
      return *ft;
    }
  }

  TF_Output output_;

  // For LLVM style RTTI.

    std::unordered_map<const Node*, std::vector<int>>* input_nodes)
    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  input_tensors->reserve(ninputs);
  for (int i = 0; i < ninputs; ++i) {
    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

    TF_RETURN_WITH_CONTEXT_IF_ERROR(
        fn_body->graph.IsValidOutputTensor(node, idx),