namespace mlir {
namespace TF {
namespace {

bool IsResourceType(Type type) {
  if (auto tensor_type = mlir::dyn_cast<TensorType>(type)) {
    return mlir::isa<TF::ResourceType>(tensor_type.getElementType());
  }
  return false;
}

bool IsResource(Value value) { return IsResourceType(value.getType()); }

// Helper that returns the FuncOp that is the SessionInit function which

bool IsResourceTensor(Value value) {
  const auto tensor_type = mlir::dyn_cast<TensorType>(value.getType());
  return tensor_type &&
         mlir::isa<mlir::TF::ResourceType>(tensor_type.getElementType());
}

// The default criterion for operations being considered as causing or being
// dependent on side effects. Reflects the current runtime logic; see below.
bool OpHasSideEffects(Operation *op) {

                     permuted_shape.begin() + input_rank - 2);
      return rewriter.create<TFL::TransposeOp>(
          bmm_op->getLoc(),
          RankedTensorType::get(permuted_shape, input_type.getElementType()),
          input, permutation_tensor_op.getResult());
    };

    Value input_lhs = bmm_op.getX();
    Value input_rhs = bmm_op.getY();

    Value output_lhs =

  auto cst_op = llvm::dyn_cast_or_null<stablehlo::ConstantOp>(cst_input);
  if (!cst_op) return false;
  ElementsAttr value = cst_op.getValue();
  if (!value.isSplat()) return false;
  if (!value.getElementType().isF32()) return false;
  return std::abs(value.getSplatValue<float>() - val) < kTolerance;
}

// Determines if the given op is semantically that of the gauss error function.
bool MatchERF(Operation* op) {

  llvm::SmallVector<int64_t> shape = {pool.n, h, w, pool.c};

  auto op_type = mlir::cast<RankedTensorType>(op->getResult(0).getType());
  return RankedTensorType::get(shape, op_type.getElementType());
}

StringAttr GetAvgPoolOpPadAttr(Builder& builder, CompositeOp op) {
  const TorchAvgPoolData pool = GetTorchAvgPoolData(op);

  if (pool.ph == 0 && pool.pw == 0) {