bool use_function) {
  AbstractTensorHandle* model_outputs[1];

  // Run the model.
  TF_RETURN_IF_ERROR(
      RunModel(forward, ctx, inputs, model_outputs, use_function));
  AbstractTensorHandlePtr model_out(model_outputs[0]);

  TF_Tensor* model_out_tensor;
  TF_RETURN_IF_ERROR(GetValue(model_out.get(), &model_out_tensor));
  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

#include "tensorflow/core/tfrt/common/pjrt_util.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/casts.h"
#include "tsl/platform/status_matchers.h"
#include "tsl/protobuf/error_codes.pb.h"

namespace tensorflow {
namespace {

using ::testing::HasSubstr;
using ::testing::NotNull;
using ::tsl::testing::StatusIs;

PJRT_Buffer* CreateCBuffer() {

namespace tensorflow {

std::string AbstractTensorHandle::DebugString() const {
  PartialTensorShape shape;
  Status s = Shape(&shape);
  std::string shape_string;
  if (!s.ok()) {
    shape_string = "<error computing shape>";
  } else {
    shape_string = shape.DebugString();
  }
  return absl::StrCat("TensorHandle(shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()),

    TF_SetStatus(status, TF_OK, "");
    PopulateDefaultParam(params);
    params->device_type = nullptr;
  };

  tensorflow::Status status = InitGraphPlugin(plugin_init);
  ASSERT_EQ(status.code(), tensorflow::error::FAILED_PRECONDITION);
  ASSERT_EQ(
      status.message(),
      "'device_type' field in TP_OptimizerRegistrationParams must be set.");
}

TEST(Grappler, OptimizeFuncNotSet) {

          .c_str());
  return nullptr;
}

// For TFE_CustomDevice::copy_tensor_from_device in the parallel device
// registration.
//
// Currently this is an error, and un-packing ParallelTensors must be performed
// explicitly by running a TPUReplicatedOutput operation on the parallel device.
//
// TODO(allenl): There are some use-cases that are only supported by copying to

// type of files.
static Status ValidateOperations(const TF_FilesystemPluginOps* ops) {
  TF_RETURN_IF_ERROR(ValidateHelper(ops->filesystem_ops));
  TF_RETURN_IF_ERROR(ValidateHelper(ops->random_access_file_ops));
  TF_RETURN_IF_ERROR(ValidateHelper(ops->writable_file_ops));
  TF_RETURN_IF_ERROR(ValidateHelper(ops->read_only_memory_region_ops));

  if (ops->filesystem_ops->new_random_access_file != nullptr &&

    TracingOperationPtr operation(CreateOperation());
    TF_RETURN_IF_ERROR(operation->Reset("Placeholder", nullptr));
    TF_RETURN_IF_ERROR(
        operation->SetOpName(absl::StrCat("_input_", inputs_.size()).c_str()));
    TF_RETURN_IF_ERROR(operation->SetAttrType("dtype", dtype));
    if (!shape.unknown_rank()) {
      TF_RETURN_IF_ERROR(operation->SetAttrShape(

    ASSERT_EQ(errors::OK, s.code()) << s.message();
    s = dyn_cast<tracing::TracingContext>(ctx.get())->AddParameter(
        DT_FLOAT, shape, &x_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    x.reset(x_raw);
  }

  PartialTensorShape shape;
  Status s = x->Shape(&shape);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  ASSERT_FALSE(shape.unknown_rank());

    TF_SetStatus(&s, static_cast<TF_Code>(result.error_code()),
                 std::string(result.error_message()).data());
    if (TF_GetCode(&s) != TF_Code::TF_OK) {
      tensorflow::CoordinationServiceError error;
      *error.mutable_source_task() = result.error_payload().source_task();
      TF_SetPayload(&s, tensorflow::CoordinationErrorPayloadKey().data(),
                    error.SerializeAsString().c_str());
    }

    {
      Status s = StatusFromTF_Status(status.get());
      CHECK_EQ(errors::OK, s.code()) << s.message();
    }

    {
      AbstractContext* ctx_raw = nullptr;
      Status s =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
      ASSERT_EQ(errors::OK, s.code()) << s.message();
      ctx_.reset(ctx_raw);
    }