}

TapeTensor::TapeTensor(AbstractTensorHandle* handle) : handle_(handle) {
  handle_->Ref();
}
TapeTensor::TapeTensor(const TapeTensor& other) {
  handle_ = other.handle_;
  handle_->Ref();
}
TapeTensor::~TapeTensor() { handle_->Unref(); }

int64_t TapeTensor::GetID() const { return ToId(handle_); }

tensorflow::DataType TapeTensor::GetDType() const {
  return handle_->DataType();
}

      MemoryReleaser memory_releaser, void* memory_releaser_arg) = 0;

  // Create a handle to wrap and manage a Tensor
  virtual ImmediateExecutionTensorHandle* CreateLocalHandle(
      AbstractTensorInterface* t) = 0;
  // Copy the handle to another device.
  virtual ImmediateExecutionTensorHandle* CopyTensorHandleToDevice(
      ImmediateExecutionTensorHandle* handle, const char* device_name,
      Status* status) = 0;

      creator, device_type, configs);
}

#undef CONFIG_TOGGLE

absl::Status InitGraphPlugin(void* dso_handle) {
  tsl::Env* env = tsl::Env::Default();

  // Step 1: Load symbol for `TF_InitPlugin`
  void* dso_symbol;
  TF_RETURN_IF_ERROR(
      env->GetSymbolFromLibrary(dso_handle, "TF_InitGraph", &dso_symbol));

  // Step 2: Call `TF_InitPlugin`

        ],
    }),
)

cc_library(
    name = "immediate_execution_tensor_handle",
    srcs = ["immediate_execution_tensor_handle.cc"],
    hdrs = ["immediate_execution_tensor_handle.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":abstract_tensor_handle",
        "//tensorflow/c:tensor_interface",
        "//tensorflow/core:framework",

  if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_TensorHandle* var_handle = nullptr;
  int num_retvals = 1;
  TFE_Execute(op, &var_handle, &num_retvals, status);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_DeleteOp(op);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  CHECK_EQ(1, num_retvals);
  TF_DeleteStatus(status);
  return var_handle;
}

TFE_TensorHandle* CreateVariable(TFE_Context* ctx, float value,

limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/gradients/math_grad.h"

#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/gradients.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"

using std::vector;

                              /*expected_max_outputs=*/1, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  const std::vector<std::unique_ptr<ParallelTensor>>& handles = *outputs;
  std::vector<ParallelTensor*> handle_inputs;
  handle_inputs.reserve(handles.size());
  for (auto& handle : handles) {
    handle_inputs.push_back(handle.get());
  }

    if (it != loaded_libs->end()) {
      lib_handle->lib_handle = it->second;
    } else {
      status->status =
          env->LoadDynamicLibrary(library_filename, &lib_handle->lib_handle);
      if (status->status.ok()) {
        TF_CHECK_OK(
            tensorflow::RegisterPluggableDevicePlugin(lib_handle->lib_handle));
      } else {
        delete lib_handle;
        return nullptr;
      }
    }

// SECTION 2. Implementation for `TF_WritableFile`
// ----------------------------------------------------------------------------
namespace tf_writable_file {

typedef struct PosixFile {
  const char* filename;
  FILE* handle;
} PosixFile;

static void Cleanup(TF_WritableFile* file) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);
  plugin_memory_free(const_cast<char*>(posix_file->filename));
  delete posix_file;
}

//
// On success, returns the newly created library handle and places OK in status.
// The caller owns the library handle.
//
// On failure, returns nullptr and places an error status in status.
TF_CAPI_EXPORT extern TF_Library* TF_LoadPluggableDeviceLibrary(
    const char* library_filename, TF_Status* status);

// Frees the memory associated with the library handle.
// Does NOT unload the library.