public:
  using OpRewritePattern<SrcOp>::OpRewritePattern;

  LogicalResult matchAndRewrite(SrcOp srcop,
                                PatternRewriter &rewriter) const final {
    Operation *op = srcop.getOperation();
    bool allTypesFp = true;
    bool allTypesQuantizedOrInt = true;
    for (auto operand : op->getOperands()) {
      ShapedType type = mlir::dyn_cast<ShapedType>(operand.getType());
      if (!type) continue;

    }
    // Use the min/max from the operands and the num_bits and narrow_range
    // attribute to create the quantization parameter for the new quantize op.
    rewriter.setInsertionPointAfter(tf_op.getOperation());
    IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.getNumBits());
    BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.getNarrowRange());
    Type res_type = tf_op.getType();

             << ")";
    }
  }
  return success();
}

void GraphOp::print(OpAsmPrinter &p) {
  p << ' ';
  p.printRegion(getOperation()->getRegion(0));
  p.printOptionalAttrDict(getOperation()->getAttrs());
}

ParseResult GraphOp::parse(OpAsmParser &parser, OperationState &result) {
  llvm::SMLoc loc = parser.getCurrentLocation();

  // Parse the body region.

          operand->get().getType() ==
              ShuffleRankedTensorType(ranked_tranpose_type, permutation)) {
        TransposeOp transpose = tranpose_op;
        transpose.getOperation()->moveBefore(op);
        transpose.setOperand(0, operand->get());
        transpose.setOperand(1, permutation_op);
        transpose_ops->erase(it);
        return transpose;
      }
    }
  }

  llvm::SmallVector<TF::TPUReplicateMetadataOp, 4> metadata;
  getOperation()->walk(
      [&metadata](TF::TPUReplicateMetadataOp op) { metadata.push_back(op); });

  IntegerAttr num_cores_per_replica;
  if (metadata.size() == 1) {
    num_cores_per_replica = metadata.front().getNumCoresPerReplicaAttr();
  }

  auto result = getOperation()->walk([&num_cores_per_replica](Operation* op) {

  target.addLegalDialect<TFL::TensorFlowLiteDialect>();
  target.addLegalDialect<arith::ArithDialect>();

  if (failed(applyPartialConversion(getOperation(), target,
                                    std::move(patterns)))) {
    getOperation().emitError("Composite lowering pass failed.");
    signalPassFailure();
  }
}

}  // namespace

// Creates an instance of the pass.

  LogicalResult matchAndRewrite(OpTy op,
                                PatternRewriter& rewriter) const override {
    if (op.getOperation()->template hasTrait<OpTrait::IsTerminator>()) {
      return failure();
    }
    for (auto result : op.getOperation()->getOpResults()) {
      if (!result.use_empty()) {
        return failure();
      }
    }

    - output_attribute: istio_responseClass
      match:
      - value: 2xx
        condition: response.code >= 200 && response.code <= 299
    - output_attribute: istio_operationId
      match:
      - value: getoperation
        condition: request.method == 'GET'
    - output_attribute: istio_grpcResponseStatus
      match:
      - value: OK

    }
  }
}

void TpuV1BridgeExecutorIslandCoarsening::runOnOperation() {
  SymbolTable symbol_table(getOperation());

  // Map tpu cluster names to the functions that contain operations for this
  // cluster.
  DenseMap<StringRef, DenseSet<func::FuncOp>> tpu_funcs;
  for (func::FuncOp func_op : getOperation().getOps<func::FuncOp>()) {
    func_op.walk([&](Operation* op) {

                        .getOperation();
  tpu_copy_with_dynamic_shape_op->moveBefore(return_op);
  return success();
}

// Update all the usage of tf_device.return op with launch op result.
void UpdateReturnOpResultWithLaunchOpResult(tf_device::LaunchOp* launch_op) {
  auto operand_not_in_launch = [&](OpOperand& operand) {
    return !launch_op->getOperation()->isProperAncestor(operand.getOwner());
  };