TF_Graph* const graph = s->graph;
  if (graph != nullptr) {
    graph->mu.lock();
    graph->sessions.erase(s);
    const bool del = graph->delete_requested && graph->sessions.empty();
    graph->mu.unlock();
    if (del) delete graph;
  }
  delete s->session;
  delete s;
}

void TF_SessionRun(TF_Session* session, const TF_Buffer* run_options,

    importlib.import_module("tf_keras.src.optimizers")
  else:
    importlib.import_module("keras.src.optimizers")
except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which

void TF_DeleteAbstractTensor(TF_AbstractTensor* t) { unwrap(t)->Unref(); }

TF_OutputList* TF_NewOutputList() { return wrap(new OutputList); }
void TF_DeleteOutputList(TF_OutputList* o) { delete unwrap(o); }
void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs,
                                TF_Status* s) {
  unwrap(o)->expected_num_outputs = num_outputs;
  unwrap(o)->outputs.clear();

  // device.
  std::function<void(Variable*)> variable_deleter = [&](Variable* to_delete) {
    to_delete->Destroy(context, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
    delete to_delete;
  };
  std::unique_ptr<Variable, decltype(variable_deleter)> variable(
      Variable::Create(context, TF_FLOAT, /* Scalar */ {}, 0, device_name,

  // If true, only explicit op placements are accepted. If false, uses
  // type-based dispatch.
  bool strict_scope_placement;
};

struct LoggedTensor {
  TFE_TensorHandle* tensor;
  LoggedTensor() = delete;
  explicit LoggedTensor(TFE_TensorHandle* tensor) : tensor(tensor) {}
  ~LoggedTensor() { TFE_DeleteTensorHandle(tensor); }
};

int64_t LoggedTensorDim(void* data, int dim_index, TF_Status* status) {

                             void* plugin_resource, void (*delete_func)(void*),
                             TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  tensorflow::PluginResource* cc_resource_ptr = new tensorflow::PluginResource(
      plugin_resource, plugin_resource_name, delete_func);
  auto cc_status =
      cc_ctx->resource_manager()->Create<tensorflow::PluginResource>(

#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. "

TF_CAPI_EXPORT extern void TF_CreateDir(const char* dirname, TF_Status* status);

// Deletes the specified directory. Typical status codes are:
//  * TF_OK - successfully deleted the directory
//  * TF_FAILED_PRECONDITION - the directory is not empty
TF_CAPI_EXPORT extern void TF_DeleteDir(const char* dirname, TF_Status* status);

// Deletes the specified directory and all subdirectories and files underneath

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: