#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/fingerprint.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tensorflow/core/util/device_name_utils.h"

namespace mlir {
namespace TFTPU {

constexpr char kStepMarkerLocationAttr[] = "step_marker_location";

  }
}

// Checks if an operation can have TPU devices propagated through.
bool IsSupportedOpToSetDevice(Operation& op) {
  return IsSupportedExecutorOp(op) ||
         isa<TF::IdentityOp, TF::IdentityNOp, TF::ShapeOp>(op);
}

// Finds nonconflicting TPU device for an operation from its operands. If an
// operand has no device or a non TPU device, or if there are conflicting

CreateTFExecutorIslandCoarseningPass();

// Creates a pass to merge IslandOps for operation marked for execution on TPU.
// This is a V1 backward compatibility.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandCoarseningPass();

// Creates a pass to outlining TPU clusters from single IslandOp into a nested
// module suitable for being processed as-if it was a V2 module.

    compatible_with = get_compatible_with_portable(),  # copybara: comment
    visibility = [
        # copybara:uncomment "//learning/brain/experimental/tfrt:__subpackages__",
        # copybara:uncomment "//learning/brain/tfrt/tpu/compiler:__subpackages__",
        "//tensorflow/compiler/mlir/tfrt:__subpackages__",
        "//tensorflow/core/runtime_fallback:internal",
        "//tensorflow/core/tfrt/saved_model:friends",

  return llvm::isa<TF::CastOp, TF::IdentityOp>(op);
}

// Adds outside compilation attributes to unary ops such as Identity/Cast ops
// at the head of TPU computation that is used only by other outside compiled
// ops. Identity ops and Cast ops is commonly added to the start of TPU
// computation. Adding/expanding outside compilation attributes to these ops
// will ensure that head outside compiled ops are correctly located and moved to
// host.

}

// Returns a set of ops that are outside compiled and can be extracted to before
// the TPU computation. These ops are either connected to the inputs of the TPU
// computation or other ops that can be extracted, and have no operands from
// other ops in the TPU computation that cannot be extracted.
llvm::SmallVector<Operation*, 4> FindOutsideCompiledOpsAtHead(

// Creates a pass that converts TPU models for CPU by removing TPU related ops
// such as TPUPartitionedCall, TPUReplicatedOp, etc. The TF quantizer does not
// work with models specifically designed for TPU, so this pass makes the input
// TPU model compatible with the TF quantizer by rewriting the TPU ops. The
// output model of this pass is expected to be ready for the TF quantizer.

namespace tensorflow {
namespace tf2xla {
namespace v2 {

using ::tensorflow::monitoring::testing::CellReader;
using ::testing::Not;
using ::testing::TestWithParam;
using tpu::FunctionToHloArgs;
using tpu::MlirToHloArgs;
using tpu::ShardingAndIndex;
using tpu::TPUCompileMetadataProto;

static constexpr char kCompilationTimeStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_time";

        // Handle replicated TPU case.
        islands_to_outline.push_back(island_op);
        break;
      }
      auto device_type =
          op.getAttrOfType<StringAttr>(TF::kCompileDeviceTypeAttr);
      if (device_type && device_type.getValue() == TF::kTpuDevice &&
          !op.hasAttrOfType<StringAttr>(TF::kReplicationInfoAttr)) {
        // Handle single-core TPU case (no `TPUReplicateMetadataOp`).

	if err != nil && err != io.ErrUnexpectedEOF {
		return err
	}

	return nil
}

func osCPUInfoName() string {
	modelName := ""
	cpuMHz := ""

	// The 512-byte buffer is enough to hold the contents of CPU0
	buf := make([]byte, 512)
	err := readLinuxProcCPUInfo(buf)
	if err != nil {
		return ""
	}

	scanner := bufio.NewScanner(bytes.NewReader(buf))
	for scanner.Scan() {