#define GEN_PASS_DECL_LEGALIZETF
#define GEN_PASS_DECL_LEGALIZETFCOLLECTIVE
#define GEN_PASS_DECL_LEGALIZETFMODULEPASS
#define GEN_PASS_DECL_LEGALIZETFTYPESPASS
#define GEN_PASS_DECL_TFXLADEVICESPECIFICTRANSFORMS
#define GEN_PASS_DECL_VERIFYTFXLALEGALIZATION
#include "tensorflow/compiler/mlir/tf2xla/transforms/xla_legalize_tf_passes.h.inc"

#define GEN_PASS_REGISTRATION
#define GEN_PASS_DECL_LEGALIZETFCOMMUNICATIONPASS

                             StringPiece tensor_name, Device* device,
                             Tensor* cpu_tensor, StatusCallback done) override;

  void CopyTensorInSameDevice(const Tensor* input_tensor, Device* device,
                              Tensor* output_tensor,
                              StatusCallback done) const override {
    done(errors::Internal("device->device copy not implemented."));
  }

 private:

  }

  void CopyTensorInSameDevice(const Tensor* input_tensor, Device* device,
                              Tensor* output_tensor,
                              StatusCallback done) const override {
    done(errors::Internal("device->device copy not implemented."));
  }

 private:
  se::Stream* stream_;                        // Not owned.

// Classes and utilities that work with StreamExecutor C API for internal use.
// This includes functions used for device registration and interfaces needed
// for testing.
#ifndef TENSORFLOW_C_EXPERIMENTAL_STREAM_EXECUTOR_STREAM_EXECUTOR_INTERNAL_H_
#define TENSORFLOW_C_EXPERIMENTAL_STREAM_EXECUTOR_STREAM_EXECUTOR_INTERNAL_H_

#include "tensorflow/c/experimental/stream_executor/stream_executor.h"

class DeviceInfoCache {
 public:
  bool IsGpu(DeviceId device) const { return is_gpu_[device.id()]; }
  bool IsCpu(DeviceId device) const { return is_cpu_[device.id()]; }

  absl::string_view GetNameFor(DeviceId device) const {
    return names_[device.id()];
  }

  absl::StatusOr<DeviceId> GetIdFor(absl::string_view name);

        int_attr.getSplatValue<APInt>() == raw_value)
      return true;
  }

  return false;
}

// Returns true if `op` is placed on GPU device, and false if it's on other
// devices or the device is not specified.
bool IsOnGpuDevice(mlir::Operation *op);

// Wrappers for CopyDeviceAndUnderscoredAttributes
void CopyDeviceAndUnderscoredAttributesAdaptor(mlir::OpResult src,

  });
}

// Copies attributes that are either `device` or whose name begins with an _
// from `from` to `to`.
// TODO(b/158769932): This should be a general feature instead post some policy
// discussion.
inline void CopyDeviceAndUnderscoredAttributes(Operation *from, Operation *to) {
  auto device = mlir::StringAttr::get(from->getContext(), "device");
  CopyAttributes(from, to, [&device](const NamedAttribute &attr) {

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

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_ANALYSIS_RESOURCE_VALUE_TYPED_ANALYZER_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_ANALYSIS_RESOURCE_VALUE_TYPED_ANALYZER_H_

#include <tuple>

#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/StringRef.h"

  // type.
  if (!updated.hasRank()) return false;

  // If the original type doesn't have a rank, then refine as the updated type
  // has a rank.
  if (!original.hasRank()) return true;

  // Both types must have the same rank.
  if (original.getRank() != updated.getRank()) return false;

  // Refine if the updated type is bounded.
  return IsBounded(updated);
}

#ifdef GOARCH_ppc64le
#define ENDIAN_MOVE(off, ptr, dst, idx) \
	MOVWZ	off(ptr),dst
#else
#define ENDIAN_MOVE(off, ptr, dst, idx) \
	MOVD	$off,idx; \
	MOVWBR	(idx)(ptr), dst
#endif

#define M00 R18
#define M01 R19
#define M02 R20
#define M03 R24
#define M04 R25
#define M05 R26
#define M06 R27
#define M07 R28
#define M08 R29
#define M09 R21
#define M10 R11
#define M11 R8
#define M12 R7