}

// Check if a function is an entry function.
bool IsEntryFunction(func::FuncOp op) {
  return op->hasAttr(kEntryFunctionAttr);
}

// Returns true iff the provided FuncOp is qualified to be included in the main
// function.
bool ShouldIncludeInMainFunction(func::FuncOp func_op) {
  return !func_op.isPrivate() && IsExported(func_op) &&
         IsEntryFunction(func_op);
}

  return func_op->getNumRegions() == 0 || func_op.getBody().empty();
}

// Gets the GraphOp from the function op. Returns an empty op iff it doesn't
// exist.
GraphOp GetGraphOpFromFuncOp(func::FuncOp func_op) {
  if (IsFuncOpEmpty(func_op)) return {};

  auto graph_op_range = func_op.front().without_terminator();
  if (llvm::hasSingleElement(graph_op_range)) {
    // The pass runs on a valid tf_executor dialect, so the op should be the

    // Builder builder(func_op.getContext());
    func_op->setAttr(
        kTfInputShapesAttr,
        ArrayAttr::get(func_op.getContext(), updated_input_shapes_attr));
  }
}

// Validates func ops. Returns `failure` if the function is invalid.
LogicalResult ValidateFuncOp(func::FuncOp func_op) {
  auto input_shapes_attr =
      func_op->getAttrOfType<ArrayAttr>(kTfInputShapesAttr);

  }
};

// Returns true iff func_op has either no Region or the body has no Blocks.
bool IsFuncOpEmpty(func::FuncOp func_op) {
  return func_op->getNumRegions() == 0 || func_op.getBody().empty();
}

// Gets the GraphOp from the function op. Returns an empty op iff it doesn't
// exist.
GraphOp GetGraphOpFromFuncOp(func::FuncOp func_op) {
  if (IsFuncOpEmpty(func_op)) return {};

constexpr char kResourceFunctionMsg[] =
    "expects function level resource argument";
constexpr char kInvalidResourceMsg[] =
    "expects resource to be a VarHandleOp or function argument";
constexpr char kResourceNameArgAttr[] = "tf.resource_name";

// Checks if a function has only one block.
mlir::LogicalResult CheckSingleBlockFunction(func::FuncOp function) {
  if (!llvm::hasSingleElement(function)) {
    return function.emitError()

    result.replaceAllUsesWith(new_op->getResult(next_result_idx++));
  }
  op->erase();
}

// Clones a function if it cannot be patched in place. Clone if there are
// multiple uses or unknown uses (for external functions). The cloned function
// will be marked as private.
func::FuncOp CloneFunctionIfNeeded(func::FuncOp func) {
  ModuleOp module = func->getParentOfType<ModuleOp>();

void DeferActivationTransposePass::runOnOperation() {
  func::FuncOp func_op = getOperation();
  MLIRContext& ctx = getContext();

  RewritePatternSet patterns(&ctx);
  patterns.add<DeferActivationTransposeForAddOp,
               DeferActivationTransposeForMaxPoolReduceWindowOp,
               DeferActivationTransposeForMaxOp>(&ctx);
  if (failed(applyPatternsAndFoldGreedily(func_op, std::move(patterns)))) {

    absl::StrAppend(&unique_func_name, "_");
  }

  Value func_input_arg;
  // Creates a function.
  func::FuncOp func_op = PrepareFunctionRegister(
      rewriter, input_val, result_type, unique_func_name, func_input_arg);

  // Fills the body.
  Operation* last_op_in_func =
      quantization_operations_func(rewriter, func_op.getOperation(),
                                   func_input_arg, result_type, quant_type);

}

// Decomposes any ReduceDatasetOps in `function` into a dataset iteration and a
// call to the reduce function in the ReduceDatasetOp.
LogicalResult DecomposeReduceDatasetInFunction(FuncOp function) {
  if (!llvm::hasSingleElement(function))
    return function.emitOpError("Expecting a single block function");

  auto decompose_result = function.walk([&](ReduceDatasetOp reduce_dataset) {

  return dyn_cast_or_null<func::FuncOp>(
      symbol_table.lookup(entry_function_symbol_ref.getValue()));
}

// Replaces the function type of `entry_func_op` to a quantized one, matching
// the input and output types of `xla_call_module_op`.
void SetQuantizedFunctionType(PatternRewriter& rewriter,
                              func::FuncOp entry_func_op,