if (method.ok() && method->has_static_range_ptq()) return true;
  }

  TF::PartitionedCallOp call_op = dyn_cast_or_null<TF::PartitionedCallOp>(op);
  return call_op && call_op->hasAttrOfType<StringAttr>(kQuantTraitAttrName) &&
         call_op->getAttrOfType<StringAttr>(kQuantTraitAttrName).getValue() ==
             llvm::StringRef(

  for (auto& function_use : function_uses.value()) {
    auto call_op = function_use.getUser();
    auto caller_func = call_op->getParentOfType<func::FuncOp>();
    if (!caller_func) return failure();

    builder.setInsertionPoint(call_op);
    for (auto [lifted_op, arg_idx] : lifted_op_and_arg_idx) {
      auto new_op = builder.clone(*lifted_op, mapping);
      call_op->insertOperands(arg_idx, new_op->getResult(0));
    }

  return method.has_weight_only_ptq();
}

bool IsWeightOnlyQuantizableOp(const Operation& op) {
  if (auto call_op = dyn_cast<TF::XlaCallModuleOp>(op)) {
    StringRef entry_function_name = GetEntryFunctionName(call_op);
    absl::StatusOr<Method> quantization_method = GetQuantizationMethod(call_op);
    return ContainsConvOrDot(entry_function_name) && quantization_method.ok() &&
           quantization_method->has_weight_only_ptq();

  func::FuncOp main_fn = FindMainFuncOp(*module_op);
  ASSERT_THAT(main_fn, NotNull());

  Operation* call_op = FindOperationOfType<TF::XlaCallModuleOp>(main_fn);
  EXPECT_FALSE(IsHybridQuantizedOp(call_op));
}

constexpr absl::string_view kModuleDotGeneralFullyConnected = R"mlir(
  module {

        max_iterations);
  } else if (auto call_op = dyn_cast<CallOpInterface>(op)) {
    if (auto func =
            dyn_cast<func::FuncOp>(call_op.resolveCallable(&symbol_table_))) {
      PropagateConstantToCallee(call_op, func, module);
      FailureOr<bool> failure_or_converged = PropagateShapeToFunctions(
          module, call_op.getArgOperands().getTypes(), {func}, max_iterations);

  op_builder.setInsertionPointToStart(&region.front());
  auto call_op = op_builder.create<mlir::func::CallOp>(
      loc, func.getFunctionType().getResults(), func.getSymName(),
      region.getArguments());
  op_builder.create<mlir::TFL::YieldOp>(loc, call_op.getResults());
}

void InlineStablehloOpRegion(mlir::Region& region, mlir::func::FuncOp func) {

  auto get_call_index = [&](mlir::Block& b) -> std::optional<int> {
    if (b.getOperations().size() != 2) return std::nullopt;
    if (auto call_op = dyn_cast<mlir::func::CallOp>(b.front()))
      return subgraph_index_map_.at(call_op.getCallee().str());
    return std::nullopt;
  };
  auto body_subgraph_index = get_call_index(op.getBody().front());

  auto inputs = func_ty.getInputs();
  block->addArguments(inputs, SmallVector<Location>(inputs.size(), loc));
  mlir::func::CallOp call_op = rewriter.create<mlir::func::CallOp>(
      loc, func, func_ty.getResults(), block->getArguments());
  rewriter.create<mhlo::ReturnOp>(loc, call_op.getResults());
}

//===----------------------------------------------------------------------===//
// Op converters.

  // only executes ops with no side effects.
  mutable llvm::SmallDenseMap<Operation*, bool> is_pure_function_;
};

bool OpSideEffectCollector::IsCallToPureFunction(Operation* callOp) const {
  auto call = llvm::dyn_cast<CallOpInterface>(callOp);
  if (!call)
    return false;  // not a call
  func::FuncOp func_op = dyn_cast<func::FuncOp>(call.resolveCallable(
      &symbol_table_collection_));
  return IsPureFunction(func_op);

// license that can be found in the LICENSE file.

//go:build goexperiment.rangefunc && !windows

package main

/*
#include <stdint.h> // for uintptr_t

void go_callback_coro(uintptr_t handle);

static void call_go(uintptr_t handle) {
	go_callback_coro(handle);
}
*/
import "C"

import (
	"fmt"
	"iter"
	"runtime/cgo"
)

func init() {
	register("CoroCgoIterCallback", func() {
		println("expect: OK")