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;

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");

  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;

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(

#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/node_properties.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/status.h"
#include "tsl/platform/errors.h"

namespace tensorflow {

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/pjrt/pjrt_client.h"
#include "tensorflow/core/framework/device_base.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/lib/core/refcount.h"
#include "tensorflow/core/platform/status.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/statusor.h"

    input_values.back().tensor = &tensor;
  }

  tensorflow::OpKernelContext::Params params;
  params.inputs = input_values;
  params.device = runner->device();
  params.op_kernel = runner->op_kernel();

  // Still use original device's resource_manager.
  params.resource_manager = runner->resource_manager();
  params.input_alloc_attrs = runner->input_alloc_attrs();

    .Attr("T: type")
    .Attr("enabled: bool")
    .Attr("func_name: string")
    .Attr("node_name: string")
    .SetIsStateful();

class DumpTensorOp : public OpKernel {
 public:
  explicit DumpTensorOp(OpKernelConstruction* ctx) : OpKernel(ctx) {
    string log_dir_path;
    string file_name;
    string func_name;
    string node_name;
    OP_REQUIRES_OK(ctx, ctx->GetAttr("log_dir_path", &log_dir_path));