if (VLOG_IS_ON(1) && status->status.ok()) {
    tensorflow::Tensor tensor;
    if (tensorflow::TF_TensorToTensor(ret, &tensor).ok()) {
      VLOG(1) << "Dequeued tensor content: " << tensor.DebugString();
    }
  }
  return ret;
}

void TF_EnqueueNamedTensor(TF_Session* session, int tensor_id,
                           TF_Tensor* tensor, TF_Status* status) {
  assert(session);
  {

    TF_Status* out_status) const {
  Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));

  DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor;
  dlm_tensor->manager_ctx = tf_dlm_tensor_ctx;
  dlm_tensor->deleter = &DLManagedTensorDeleter;
  dlm_tensor->dl_tensor.device = tf_dlm_context;
  int ndim = tensor->dims();
  dlm_tensor->dl_tensor.ndim = ndim;
  dlm_tensor->dl_tensor.data = tf_dlm_data;
  dlm_tensor->dl_tensor.dtype = tf_dlm_type;

    ],
)

cc_library(
    name = "tensor_pjrt_buffer_util",
    srcs = ["tensor_pjrt_buffer_util.cc"],
    hdrs = ["tensor_pjrt_buffer_util.h"],
    visibility = ["//visibility:public"],
    deps = [
        "//tensorflow/compiler/jit:pjrt_tensor_buffer_util",
        "//tensorflow/core:framework",
        "//tensorflow/core/tfrt/common:async_value_tensor",
        "//tensorflow/core/tfrt/common:global_state",

from fastapi._compat import PYDANTIC_V2

needs_py39 = pytest.mark.skipif(sys.version_info < (3, 9), reason="requires python3.9+")
needs_py310 = pytest.mark.skipif(
    sys.version_info < (3, 10), reason="requires python3.10+"
)
needs_pydanticv2 = pytest.mark.skipif(not PYDANTIC_V2, reason="requires Pydantic v2")

    TFE_TensorHandle* h, TF_Status* status) {
  tensorflow::TensorHandle* handle =
      TensorHandleFromInterface(tensorflow::unwrap(h));
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return nullptr;
  }

  std::vector<int64_t> dev_dims = TensorShapeAsVector(*handle, &status->status);
  if (!status->status.ok()) {
    return nullptr;

TF_CAPI_EXPORT extern TF_Tensor* TF_DequeueNamedTensor(TF_Session* session,
                                                       int tensor_id,
                                                       TF_Status* status);

// On success, enqueues `tensor` into a TF-managed FifoQueue given by
// `tensor_id`, associated with `session`. There must be a graph node named
// "fifo_queue_enqueue_<tensor_id>", to be executed by this API call. It reads

    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    TF_Tensor* expected_out0 = expected_csession->output_tensor(0);
    TF_Tensor* expected_out1 = expected_csession->output_tensor(1);

    CompareTensors(out0, expected_out0);
    CompareTensors(out1, expected_out1);
  }

  void CompareTensors(TF_Tensor* a, TF_Tensor* b) {
    float* a_data = static_cast<float*>(TF_TensorData(a));

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_Tensor* result_tensor = TFE_TensorHandleResolve(result_t, status.get());

  // Copy Tensor data into an array.
  float result_data[4] = {0};
  memcpy(&result_data[0], TF_TensorData(result_tensor),
         TF_TensorByteSize(result_tensor));

  int data_len = 4;  // length of result_data
  for (int i = 0; i < data_len; i++) {

  }

  /**
   * Send a close frame with optional code and reason.
   *
   * @param code Status code as defined by
   *     [Section 7.4 of RFC 6455](http://tools.ietf.org/html/rfc6455#section-7.4) or `0`.
   * @param reason Reason for shutting down or `null`.
   */
  @Throws(IOException::class)
  fun writeClose(
    code: Int,
    reason: ByteString?,
  ) {
    var payload = ByteString.EMPTY