});
  }
}

void XlaDevice::Compute(OpKernel* op_kernel, OpKernelContext* context) {
  VLOG(2) << "XlaDevice::Compute " << op_kernel->name() << ":"
          << op_kernel->type_string();
  ShowXlaDeviceDeprecationWarning(jit_device_name_.type_string());
  op_kernel->Compute(context);
}

void XlaDevice::ComputeAsync(AsyncOpKernel* op_kernel, OpKernelContext* context,

  std::unique_ptr<OpKernel> kernel =
      CreateOpKernel(DeviceType(DEVICE_CPU), nullptr, nullptr, def, 1, &status);
  ASSERT_TRUE(status.ok()) << status.ToString();

  OpKernelContext::Params params;
  DummyDevice dummy_device(nullptr);
  params.device = &dummy_device;
  params.op_kernel = kernel.get();
  gtl::InlinedVector<TensorValue, 4> inputs;

    return failure();

  params_.inputs = inputs;
  params_.op_kernel = op_kernel.get();
  llvm::SmallVector<tensorflow::AllocatorAttributes, 4> output_attr(
      op_->getNumResults());
  params_.output_attr_array = output_attr.data();

  tensorflow::OpKernelContext op_context(&params_, op_->getNumResults());
  device_->Compute(params_.op_kernel, &op_context);

  status = op_context.status();
  if (!status.ok()) {

limitations under the License.
==============================================================================*/

#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

REGISTER_OP("TestCApi1").Doc(R"doc(Used to test C API)doc");

namespace tensorflow {
namespace {

// An OpKernel whose methods delegate to C function pointers.
class COpKernel : public OpKernel {
 public:
  explicit COpKernel(OpKernelConstruction* ctx,
                     void* (*create_func)(TF_OpKernelConstruction*),
                     void (*compute_func)(void*, TF_OpKernelContext*),
                     void (*delete_func)(void*))

  std::unique_ptr<OpKernel> kernel =
      CreateOpKernel(DeviceType(DEVICE_CPU), nullptr, nullptr, def, 1, &status);
  ASSERT_TRUE(status.ok()) << status.ToString();
  OpKernelContext::Params params;
  DummyDevice dummy_device(nullptr);
  params.device = &dummy_device;
  params.op_kernel = kernel.get();
  AllocatorAttributes alloc_attrs;
  params.output_attr_array = &alloc_attrs;

  ~XlaDevice() override;

  Allocator* GetAllocator(AllocatorAttributes attr) override
      TF_LOCKS_EXCLUDED(mu_);
  void Compute(OpKernel* op_kernel, OpKernelContext* context) override;
  void ComputeAsync(AsyncOpKernel* op_kernel, OpKernelContext* context,
                    AsyncOpKernel::DoneCallback done) override;
  Status Sync() override;

limitations under the License.
==============================================================================*/

#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

REGISTER_OP("TestCApi").Doc(R"doc(Used to test C API)doc");

#define TENSORFLOW_COMPILER_JIT_TF_TO_HLO_COMPILER_H_

#include <memory>
#include <vector>

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {

class TfToHloCompiler {
 public:
  TfToHloCompiler() = default;
  virtual ~TfToHloCompiler() = default;

  // Compiles a Tensorflow `function` to an HloModuleProto stored in the

==============================================================================*/
#include "tensorflow/core/framework/common_shape_fns.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {
namespace tf_mlrt {

REGISTER_OP("TestAsyncIdentity")
    .Input("in: T")
    .Output("out: T")
    .Attr(