TF_DataType dtype) {
  DCHECK(index >= 0 && index < shape_list->num_items);
  TF_ShapeAndType& shape_and_type = shape_list->items[index];
  shape_and_type.dtype = dtype;
}

void TF_DeleteShapeAndTypeList(TF_ShapeAndTypeList* shape_list) {
  if (shape_list == nullptr) return;
  for (size_t i = 0; i < shape_list->num_items; ++i) {

  TestRemoteExecuteUpdateServerDefResourceAccess(true);
}

void TestRemoteExecuteUpdateServerDefWithFailures(bool async) {
  // Fail fast on GetStatus requests so we can get errors instead of timeout
  // when updating cluster with non-exsitent worker
  tensorflow::setenv("GRPC_FAIL_FAST", "TRUE", /*overwrite=*/1);

  tensorflow::ServerDef server_def = GetServerDef(2);
  // This server def has the task index set to 0.

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;
}

static void Append(const TF_WritableFile* file, const char* buffer, size_t n,
                   TF_Status* status) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);

           {"condition", "x"},
           {{"T", std::vector<DataType>{DT_FLOAT}}}},
          {{"y"},
           "CollectiveReduce",
           {"x"},
           {{"T", DT_FLOAT},
            {"group_size", static_cast<int>(devices.size())},
            {"group_key", 0},
            {"instance_key", 0},
            {"merge_op", "Add"},
            {"final_op", "Id"},
            {"subdiv_offsets", std::vector<int>()}},

  dlm_tensor->dl_tensor.byte_offset =
      0;  // TF doesn't handle the strides and byte_offsets here
  return static_cast<void*>(dlm_tensor);
}

TFE_TensorHandle* TFE_HandleFromDLPack(void* dlm, TF_Status* status,
                                       TFE_Context* ctx) {
  DLManagedTensor* dlmt = static_cast<DLManagedTensor*>(dlm);
  DLTensor* dl_tensor = &dlmt->dl_tensor;
  absl::optional<std::string> device_name =

// may lead to collisions. Introduce another way to get a unique id for this
// tensor.
int64_t ToId(const AbstractTensorHandle* t) {
  return static_cast<int64_t>(reinterpret_cast<uintptr_t>(t));
}

Status ZerosLike(AbstractContext* ctx, AbstractTensorHandle* t,
                 AbstractTensorHandle** result) {
  AbstractOperationPtr op(ctx->CreateOperation());

  delete[] static_cast<bool*>(data);
}

static void Int32Deallocator(void* data, size_t, void* arg) {
  delete[] static_cast<int32_t*>(data);
}

static void DoubleDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<double*>(data);
}

static void FloatDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<float*>(data);
}

TF_Tensor* BoolTensor(bool v) {

      TFE_TensorHandleResolve(var_value_unpacked, status.get()),
      TF_DeleteTensor);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(111., *static_cast<float*>(TF_TensorData(resolved_value.get())));

  // Free the backing buffer for the variable.
  op.reset(TFE_NewOp(context.get(), "DestroyResourceOp", status.get()));
  TFE_OpAddInput(op.get(), var_handle, status.get());

void ParallelTensorDeallocator(void* data) {
  delete reinterpret_cast<ParallelTensor*>(data);
}

// Used as an argument to TFE_NewCustomDeviceTensorHandle, for computing the
// number of dimensions of a parallel tensor.
int ParallelTensorNumDims(void* data, TF_Status* status) {
  const std::vector<int64_t>* shape;
  Status s = reinterpret_cast<ParallelTensor*>(data)->Shape(&shape);
  if (!s.ok()) {

  ASSERT_EQ(read, -1) << "Read: " << read;
  ASSERT_EQ(TF_GetCode(status_), TF_NOT_FOUND) << TF_Message(status_);
  TF_SetStatus(status_, TF_OK, "");

  auto gcs_file =
      static_cast<tf_gcs_filesystem::GCSFile*>(filesystem_->plugin_filesystem);
  ASSERT_TRUE(WriteToServer(filepath, 0, content_view.length(),
                            &gcs_file->gcs_client, status_));