has_resource_result = true;
    int result_idx = result.getResultNumber();

    Value ret0 =
        op->getRegion(0).front().getTerminator()->getOperand(result_idx);
    for (Region &region : op->getRegions().drop_front()) {
      Value ret = region.front().getTerminator()->getOperand(result_idx);
      if (ret != ret0) {
        return op->emitError("Result #")
               << result_idx

    for (auto operand_and_idx : llvm::enumerate(op->getOperands()))
      TF_RETURN_IF_ERROR(AddEdgeBetweenNodes(operand_and_idx.value(), dst_node,
                                             operand_and_idx.index()));

    operand_offset = op->getNumOperands();
  }

  // For all other ops (including tf_executor.island), add remaining edges.
  for (auto operand_and_idx : llvm::enumerate(inst->getOperands()))
    TF_RETURN_IF_ERROR(

    for (auto operand_and_idx : llvm::enumerate(op->getOperands()))
      TF_RETURN_IF_ERROR(AddEdgeBetweenNodes(operand_and_idx.value(), dst_node,
                                             operand_and_idx.index()));

    operand_offset = op->getNumOperands();
  }

  // For all other ops (including tf_executor.island), add remaining edges.
  for (auto operand_and_idx : llvm::enumerate(inst->getOperands()))
    TF_RETURN_IF_ERROR(

                                   SmallVector<TransposeOp, 2>* transpose_ops) {
  for (auto it = transpose_ops->begin(); it != transpose_ops->end(); ++it) {
    auto tranpose_op = *it;
    for (auto tranpose_operand : tranpose_op.getOperands()) {
      auto ranked_tranpose_type =
          mlir::dyn_cast_or_null<RankedTensorType>(tranpose_operand.getType());
      if (!ranked_tranpose_type) continue;
      if (ranked_tranpose_type.getRank() == permutation.size() &&

  auto new_operands = llvm::to_vector<8>(caller->getOperands());
  llvm::SmallVector<int64_t, 8> changed_indices;
  // Find the operands to change, and create the loads.
  for (auto& entry : arg_data_type_and_updated_output_index) {
    int64_t index = entry.getFirst();
    Type new_type = entry.getSecond().first;
    int64_t updated_index = entry.getSecond().second;
    auto operand = caller->getOperand(index);
    builder.setInsertionPoint(caller);

      // inputs.
      SmallVector<Value, 4> inputs;
      inputs.reserve(op_with_region->getNumOperands());
      for (Value operand : op_with_region->getOperands()) {
        const Type operand_type = operand.getType();
        if (mlir::isa<NoneType>(operand_type)) {
          inputs.push_back(operand);
          continue;
        }

        const Type element_type =

    auto decomposition = mlir::cast<FlatSymbolRefAttr>(calledComputations[0]);

    auto composite = rewriter.create<mlir::stablehlo::CompositeOp>(
        op.getLoc(), op.getResultTypes(), op.getOperands(), name.str(), attrs,
        decomposition.getValue());
    rewriter.replaceOp(op, composite.getResults());
    return success();
  }
};

struct LegalizeStablehloCustomCallToCompositePass

    // while creating the ops so make sure there aren't any type changes between
    // the original op operands and the operands during the conversion.
    for (auto&& [old_val, new_val] : llvm::zip(op->getOperands(), operands)) {
      if (old_val.getType() != new_val.getType()) return failure();
    }

    auto abstractOp = op->getRegisteredInfo();
    if (!abstractOp) return failure();

OpFoldResult LeakyReluOp::fold(FoldAdaptor adaptor) {
  auto operands = adaptor.getOperands();
  assert(operands.size() == 1 && "leaky relu has one operand");

  // leaky_relu(x, alpha: 1) -> x
  if (getAlpha().convertToFloat() == 1.0f &&
      getOperand().getType() == getType())
    return getOperand();

  auto calculate = [&](FloatAttr arg) {
    APFloat val = arg.getValue();

        func_op.getRegion().getBlocks().front().getTerminator());
    if (!return_op) return failure();
    auto req_op = llvm::dyn_cast_or_null<mlir::stablehlo::UniformQuantizeOp>(
        return_op.getOperands()[0].getDefiningOp());
    if (!req_op) return failure();

    // Create a new func.call op with f32 output.
    auto new_call_op = call_op.clone();
    new_call_op->getResult(0).setType(