runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [python3.9, python3.10, python3.11, python3.12]
    steps:
      - name: Delete unnecessary tools folder
        run: rm -rf /opt/hostedtoolcache
      -
        name: Checkout
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
      -
        name: Set up Docker Buildx

  ///
  /// DEFAULT IMPLEMENTATION: Does a BFS traversal of tree rooted at `path`,
  /// deleting entries as needed. Needs `path_exists`, `get_children`,
  /// `is_directory`, `delete_file`, and `delete_dir`.
  void (*delete_recursively)(const TF_Filesystem* filesystem, const char* path,
                             uint64_t* undeleted_files,
                             uint64_t* undeleted_dirs, TF_Status* status);

#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"

namespace tensorflow {
namespace parallel_device {
namespace {

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

using MaybeParallelTensorOwned =
    absl::variant<std::unique_ptr<ParallelTensor>, TensorHandlePtr>;

using MaybeParallelTensorUnowned =

  ASSERT_EQ(TF_GetCode(status_), TF_OUT_OF_RANGE) << TF_Message(status_);
  ASSERT_TRUE(CompareSubString(content_view.length() - 2, 2, result, read));

  delete[] result;
  tf_random_access_file::Cleanup(file);
  delete file;
}

TEST_F(GCSFilesystemTest, WritableFile) {
  tf_gcs_filesystem::Init(filesystem_, status_);
  ASSERT_TF_OK(status_) << "Could not initialize filesystem. "

      op_name, tape_tensors, input_ids, input_dtypes,
      [gradient_function]() -> GradientFunction* { return gradient_function; },
      [](GradientFunction* ptr) {
        if (ptr) {
          delete ptr;
        }
      });
}
bool Tape::ShouldRecord(
    absl::Span<const AbstractTensorHandle* const> tensors) const {
  std::vector<int64_t> tensor_ids(tensors.size());

namespace tensorflow {
namespace parallel_device {
namespace {

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

class StatusDeleter {
 public:
  void operator()(TF_Status* to_delete) const { TF_DeleteStatus(to_delete); }
};

using StatusPtr = std::unique_ptr<TF_Status, StatusDeleter>;

class ExecutorDeleter {
 public:

  if (op_id == -1) {
    // Do not delete watched tensors.
    return;
  }
  tensor_tape_.erase(tensor_op_it);
  auto op_it = op_tape_.find(op_id);
  CHECK(op_it != op_tape_.end());
  for (const auto& output : op_it->second.output_tensor_info) {
    if (tensor_usage_.find(output.GetID()) != tensor_usage_.end()) {
      // Found a usage for an output, so cannot delete the op.
      return;
    }
  }

  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_GraphCopyFunction(host_graph_, func_, nullptr, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Delete the gradient func.
  // It is safe to delete after adding a copy to host graph.
  TF_DeleteFunction(grad_func);

  // Check that GraphDef did not change
  GraphDef gdef2;
  GetGraphDef(host_graph_, &gdef2);

    TFE_ContextOptions* options, TFE_ContextDevicePlacementPolicy policy) {
  options->device_placement_policy = policy;
}

void TFE_DeleteContextOptions(TFE_ContextOptions* options) { delete options; }

TFE_Context* TFE_NewContext(const TFE_ContextOptions* opts, TF_Status* status) {
  if (opts->use_tfrt) {
    status->status = tensorflow::errors::Unimplemented("TFRT is not supported");
    return nullptr;

    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [python3.9, python3.10, python3.11, python3.12]
    steps:
      - name: Delete unnecessary tools folder
        run: rm -rf /opt/hostedtoolcache
      -
        name: Checkout
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
      -
        name: Set up Docker Buildx