count *= shape.dimensions(dim);
    }
  }
  rewrites->push_back({"{{I}}", absl::StrCat(i)});
  rewrites->push_back({"{{TYPE}}", type});
  rewrites->push_back({"{{DIM_VARS}}", absl::StrJoin(dim_vars, ", ")});
  rewrites->push_back({"{{DIM_SIZES}}", dim_sizes});
  rewrites->push_back({"{{INDICES}}", indices});
  rewrites->push_back({"{{COUNT}}", absl::StrCat(count)});
  return absl::OkStatus();
}

#include "mlir/Pass/Pass.h"  // from @llvm-project

namespace mlir {
namespace TFDevice {

// For architectures that support accelerated embedding lookups, this pass will
// rewrite the graph to use pipelining for better device utilization.
std::unique_ptr<OperationPass<ModuleOp>> CreateEmbeddingSequencingPass();

// This is a strictly sequential and formally correct fallback option for the

	// nolint: staticcheck
	action.MaxGrpcTimeout = action.Timeout

	out.Action = &route.Route_Route{Route: action}

	if in.Rewrite != nil {
		action.PrefixRewrite = in.Rewrite.GetUri()
		if in.Rewrite.GetAuthority() != "" {
			authority = in.Rewrite.GetAuthority()
		}
	}
	if authority != "" {
		action.HostRewriteSpecifier = &route.RouteAction_HostRewriteLiteral{
			HostRewriteLiteral: authority,

#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project  // IWYU pragma: keep
#include "mlir/Rewrite/FrozenRewritePatternSet.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project

	}

	if len(matches) == 0 {
		return
	}

	f, err = os.OpenFile(file, os.O_RDWR, 0)
	if err != nil {
		log.Fatal(err)
	}
	if err := buildid.Rewrite(f, matches, newID); err != nil {
		log.Fatal(err)
	}
	if err := f.Close(); err != nil {
		log.Fatal(err)
	}

namespace mhlo {

/// Converter to be used along with the fallback Tf2Xla patterns below.
class Tf2XlaTypeConverter : public TypeConverter {
 public:
  Tf2XlaTypeConverter();
};

/// Adds the TF to XLA via TF2XLA rewrite patterns to the pattern list.
/// `prefer_tf2xla` means an op will be included iff it is not in
/// `MlirLegalizedUnderPreferTf2XlaSet`. `!prefer_tf2xla` mean an op will be

==============================================================================*/

include "mlir/Pass/PassBase.td"

def TPURewritePass : Pass<"tf-tpu-rewrite", "mlir::ModuleOp"> {
  let summary = "Rewrites a `tf_device.cluster_func` on TPUs into TPU runtime operations.";

  let description = [{
    This pass rewrites a `tf_device.cluster_func` operation into a sequence of `tf._TPUCompileMlir`

	foo := p.NewComponent(string(cnp))
	foo.ReportProgress()
	expect(`- Processing resources for ` + cnpo + `.`)

	bar := p.NewComponent(string(cnb))
	bar.ReportProgress()
	// string buffer won't rewrite, so we append
	expect(`- Processing resources for ` + cnbo + `, ` + cnpo + `.`)
	bar.ReportProgress()
	bar.ReportProgress()

	bar.ReportWaiting([]string{"deployment"})

  //    XlaLaunch.
  static Status Encapsulate(std::unique_ptr<Graph>* graph,
                            FunctionLibraryDefinition* flib_def);

  // b) we rewrite the function calls generated in phase (a) into XlaLaunch
  //    operators. We also convert the XlaClusterOutput output nodes of the
  //    function call into the outputs of the XlaLaunch operator.

    return signalPassFailure();

  // Eliminate TPUCompilationResultOp now that the rewrite is complete.
  for (auto& it : compilation_results) {
    for (auto op : it.second) {
      if (!op.use_empty()) {
        mlir::InFlightDiagnostic err = op.emitError("uses remain post rewrite");
        for (auto user : op->getUsers())
          err.attachNote(user->getLoc()) << "remaining user";