#include "tensorflow/compiler/mlir/tf2xla/api/v2/tf_executor_to_graph.h"
#include "tensorflow/compiler/tf2xla/xla_compiler.h"
#include "xla/client/client_library.h"
#include "xla/client/compile_only_client.h"
#include "xla/stream_executor/host/host_platform_id.h"
#include "xla/stream_executor/platform_manager.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/framework/function.h"

}

Status XlaTensor::AllocateShapedBuffer(DataType dtype,
                                       const xla::Shape& on_device_shape,
                                       xla::LocalClient* client,
                                       int device_ordinal) {
  xla::Shape on_host_shape =
      xla::ShapeUtil::DeviceShapeToHostShape(on_device_shape);
  xla::ScopedShapedBuffer shaped_buffer(on_host_shape, on_device_shape,

#include "tensorflow/compiler/mlir/tensorflow/utils/convert_type.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/serialize_mlir_module_utils.h"
#include "xla/mlir_hlo/mhlo/IR/register.h"
#include "xla/shape.h"
#include "xla/translate/mhlo_to_hlo/type_to_shape.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tsl/platform/errors.h"

#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 {

        "@llvm-project//mlir:MlirOptLib",
        "@llvm-project//mlir:Support",
        "@llvm-project//mlir:Transforms",
        "@local_xla//xla/mlir/framework/ir:xla_framework",
        "@local_xla//xla/mlir/framework/transforms:passes",
        "@local_xla//xla/mlir_hlo:all_passes",
    ],
)

cc_library(
    name = "passes",
    visibility = [
        ":__subpackages__",

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

// Registers the XLA_CPU device, which is an XlaDevice instantiation that runs
// operators using XLA via the XLA "Host" (CPU) backend.

#include <array>

#include "absl/memory/memory.h"
#include "tensorflow/compiler/jit/defs.h"
#include "tensorflow/compiler/jit/flags.h"
#include "tensorflow/compiler/jit/kernels/xla_ops.h"

#include "tensorflow/compiler/tf2xla/shape_util.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/stream_executor/device_memory.h"
#include "xla/stream_executor/platform_manager.h"
#include "xla/stream_executor/stream.h"
#include "xla/stream_executor/stream_executor.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tsl/lib/core/status_test_util.h"

namespace tensorflow {

#include "tensorflow/compiler/mlir/tf2xla/internal/test_matchers.h"
#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"

    bool prefer_tf2xla = false);

// Legalizes TF/XLA communication ops (TF dialect) to HLO dialect communication
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCommunicationPass();

// Legalizes TF/XLA collective ops (TF dialect) to HLO dialect collective
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCollectivePass();

// Verifies that the TF/XLA ops have all been lowered to MHLO.

#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
#include "xla/client/compile_only_client.h"
#include "tensorflow/core/tpu/kernels/tpu_compile_op_support.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

// Legalize the given MLIR module to XLA HLO using a combination of the MLIR
// Bridge and XlaBuilder