#ifndef TENSORFLOW_COMPILER_JIT_XLA_HOST_RECV_DEVICE_CONTEXT_H_
#define TENSORFLOW_COMPILER_JIT_XLA_HOST_RECV_DEVICE_CONTEXT_H_

#include "xla/shape.h"
#include "xla/stream_executor/device_memory.h"
#include "xla/stream_executor/stream.h"
#include "tensorflow/core/framework/device_base.h"
#include "tfrt/concurrency/async_value_ref.h"  // from @tf_runtime

namespace tensorflow {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/constant_fold.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.h"
#include "xla/stream_executor/stream_executor.h"
#include "tensorflow/core/framework/logging.h"
#include "tsl/platform/statusor.h"

namespace mlir {
namespace {

}  // anonymous namespace

#include "tensorflow/compiler/mlir/tensorflow/transforms/set_tpu_infeed_layout.h"
#include "xla/layout.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"
#include "xla/shape.h"
#include "xla/stream_executor/tpu/c_api_conversions.h"
#include "xla/stream_executor/tpu/tpu_api.h"
#include "xla/translate/mhlo_to_hlo/type_to_shape.h"

namespace mlir {
namespace mhlo {
namespace {

#define GEN_PASS_DEF_INFEEDOPSXLAADJUSTLAYOUT

# Description:
# test for stream_executor
load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_shared_object",
)

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

tf_cc_shared_object(
    name = "test_pluggable_device.so",
    srcs = ["test_pluggable_device.cc"],
    visibility = ["//tensorflow/c:__subpackages__"],
    deps = [

#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/client_library.h"
#include "xla/shape.h"
#include "xla/stream_executor/platform.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/monitoring/cell_reader.h"

#include "tensorflow/compiler/jit/xla_platform_info.h"
#include "tensorflow/compiler/tf2xla/layout_util.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/stream_executor/gpu/gpu_init.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {

    "//tensorflow/core:lib",
    "//tensorflow/core:state_ops_op_lib",
    "//tensorflow/core/platform:stream_executor_no_cuda",
    "//tensorflow/core/profiler/lib:traceme",
    "@local_xla//xla/stream_executor/integrations:tf_allocator_adapter",
    "@com_google_absl//absl/types:optional",
]

# Linked by tensorflow core, without registration of jit compilation passes.
cc_library(

#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf.h"
#include "xla/client/client_library.h"
#include "xla/shape.h"
#include "xla/stream_executor/platform.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/protobuf/config.pb.h"

  return client_->Load(serialized_executable, build_options);
}

void XlaDeviceCompilerClient::WaitForProgramsToFinish() {
  if (client_ == nullptr) return;

  for (auto* executor : client_->backend().stream_executors()) {
    bool ok = executor->SynchronizeAllActivity();
    if (!ok) {
      LOG(ERROR) << "Error synchronizing activity while waiting for all "
                    "programs to complete";
    }
  }
}

#include "tensorflow/compiler/jit/xla_device.h"
#include "tensorflow/compiler/jit/xla_device_ops.h"
#include "tensorflow/compiler/tf2xla/layout_util.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {
using tensorflow::IdentityShapeRepresentationFn;