#include "absl/synchronization/mutex.h"
#include "tensorflow/c/env.h"
#include "tensorflow/c/tf_status.h"

namespace tf_gcs_filesystem {

/// \brief An LRU cache of string keys and arbitrary values, with configurable
/// max item age (in seconds) and max entries.
///
/// This class is thread safe.
template <typename T>
class ExpiringLRUCache {
 public:
  /// A `max_age` of 0 means that nothing is cached. A `max_entries` of 0 means

# 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

  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;
    }

        files.
*   Eager Execution:
    *   With eager execution Datasets can now be used as standard python
        iterators (`for batch in dataset:`). Both `Dataset.__iter__()` and
        `Dataset.make_one_shot_iterator()` can now be used to create iterators
        when eager execution is enabled.
    *   Automatic device placement has been enabled (i.e., use a GPU if

        "//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",

typedef enum TF_Filesystem_Option_Type {
  TF_Filesystem_Option_Type_Int = 0,
  TF_Filesystem_Option_Type_Real,
  TF_Filesystem_Option_Type_Buffer,
  TF_Filesystem_Num_Option_Types,  // must always be the last item
} TF_Filesystem_Option_Type;

typedef struct TF_Filesystem_Option {
  char* name;                         // null terminated, owned
  char* description;                  // null terminated, owned

# 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

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.

}

TEST(TF_GrapplerItem, NodesToPreserve) {
  GrapplerItem item;
  item.fetch = std::vector<string>{"Conv", "BiasAdd"};
  std::unordered_set<string> nodes_preserved = item.NodesToPreserve();
  TF_GrapplerItem* c_item = reinterpret_cast<TF_GrapplerItem*>(&item);

  int list_total_size = 0;
  for (const string& s : nodes_preserved) {
    list_total_size += s.size();
  }

                                         TF_Status* status);

// Retrieves the next item from the given TF_StringStream and places a pointer
// to it in *result. If no more items are in the list, *result is set to NULL
// and false is returned.
//
// Ownership of the items retrieved with this function remains with the library.
// Item points are invalidated after a call to TF_StringStreamDone.