namespace grappler {

Status CGraphOptimizer::Optimize(Cluster* cluster, const GrapplerItem& item,
                                 GraphDef* optimized_graph_def) {
  OwnedTFStatus c_status(TF_NewStatus());
  OwnedTFBuffer graph_buf(TF_NewBuffer());
  OwnedTFBuffer optimized_graph_buf(TF_NewBuffer());
  TF_RETURN_IF_ERROR(MessageToBuffer(item.graph, graph_buf.get()));

  optimizer_.optimize_func(c_optimizer_, graph_buf.get(),

        "//tensorflow/c:tf_status",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/core:framework",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core/grappler:grappler_item",
        "//tensorflow/core/grappler/costs:graph_properties",
        "//tensorflow/core/grappler/optimizers:custom_graph_optimizer",
        "//tensorflow/core/grappler/optimizers:custom_graph_optimizer_registry",

# Install Visual C++ Redistributable for Visual Studio 2015-2022.
RUN New-Item -Path "C:/" -Name "TEMP" -ItemType "directory"; \
    Invoke-WebRequest "https://aka.ms/vs/17/release/vc_redist.x64.exe" \
        -OutFile C:/TEMP/vc_redist.x64.exe -UseBasicParsing; \
    Start-Process -filepath C:/TEMP/vc_redist.x64.exe -ArgumentList '/install', '/passive', '/norestart' -Wait; \
    Remove-Item C:/TEMP/vc_redist.x64.exe

# Finally: Run your script of choice.
#   If you've clicked on a test result from our CI (via a dashboard or GitHub link),
#   click to "Invocation Details" and find BUILD_CONFIG, which will contain a
#   "build_file" item that indicates the script used.
ci/official/wheel.sh

# Advanced: Select specific build/test targets with "any.sh".
# TF_ANY_TARGETS=":your/target" TF_ANY_MODE="test" ci/official/any.sh

def get_var(environ_cp,
            var_name,
            query_item,
            enabled_by_default,
            question=None,
            yes_reply=None,
            no_reply=None):
  """Get boolean input from user.

  If var_name is not set in env, ask user to enable query_item or not. If the
  response is empty, use the default.

  Args:
    environ_cp: copy of the os.environ.

  for (auto&& item : gcs_file->gcs_client.ListObjectsAndPrefixes(
           bucket, gcs::Prefix(prefix), gcs::Delimiter(delimiter),
           gcs::Fields("items(name),prefixes"))) {
    if (count == max_results) {
      TF_SetStatus(status, TF_OK, "");
      return result;
    }
    if (!item) {
      TF_SetStatusFromGCSStatus(item.status(), status);
      return result;
    }

        "//tensorflow/core/grappler/graph_analyzer:graph_analyzer_tool",
        "//tensorflow/core/grappler/optimizers:meta_optimizer",
        "//tensorflow/core/grappler:grappler_item",
        "//tensorflow/core/grappler:grappler_item_builder",
        "//tensorflow/core/kernels:data_service_ops",
        "//tensorflow/core/kernels:dataset_ops",
        "//tensorflow/core/platform:logging",

  if (!status->status.ok()) return -1;
  auto iter = name_ranges.find(arg_name);
  if (iter == name_ranges.end()) {
    status->status = InvalidArgument("Output arg '", arg_name, "' not found");
    return -1;
  }
  return iter->second.second - iter->second.first;
}

int TF_OperationNumInputs(TF_Operation* oper) {
  return oper->node.num_inputs();
}

    const ForwardOperation& op,
    std::unique_ptr<GradientFunction>* gradient_function) const {
  auto iter = registry_.find(op.op_name);
  if (iter == registry_.end()) {
    const string error_msg = "No gradient defined for op: " + op.op_name + ".";
    return errors::NotFound(error_msg);
  }
  gradient_function->reset(iter->second(op));
  return absl::OkStatus();
}

    return;
  }
  std::vector<tensorflow::CoordinatedTask> task_vec(tasks.length);
  auto* task_iter = static_cast<const tensorflow::CoordinatedTask*>(tasks.data);
  for (size_t i = 0; i < tasks.length; ++i) {
    task_vec[i].set_job_name(task_iter->job_name());
    task_vec[i].set_task_id(task_iter->task_id());
    ++task_iter;
  }
  auto results = coord_agent->GetTaskState(task_vec);
  if (!results.ok()) {