Fix crash from concurrent when nb::make_iterator<> under free-threading.

The `State` class used by make_iterator is constructed lazily, but
without locking it is possible for the caller to crash when the class
type is only partially constructed. This PR adds an ft_mutex around the
binding of the State type.

My initial instinct was to use an nb_object_guard on the `holder` scope.
Unfortunately this doesn't work; I suspect another critical section is
acquired by code during the class binding and that releases the outer
critical section.

include/nanobind/make_iterator.h

@@ -71,27 +71,30 @@ typed<iterator, ValueType> make_iterator_impl(handle scope, const char *name,
         "make_iterator_impl(): the generated __next__ would copy elements, so the "
         "element type must be copy-constructible");
 
-    if (!type<State>().is_valid()) {
-        class_<State>(scope, name)
-            .def("__iter__", [](handle h) { return h; })
-            .def("__next__",
-                 [](State &s) -> ValueType {
-                     if (!s.first_or_done)
-                         ++s.it;
-                     else
-                         s.first_or_done = false;
-
-                     if (s.it == s.end) {
-                         s.first_or_done = true;
-                         throw stop_iteration();
-                     }
-
-                     return Access()(s.it);
-                 },
-                 std::forward<Extra>(extra)...,
-                 Policy);
+    {
+        static ft_mutex mu;
+        ft_lock_guard lock(mu);
+        if (!type<State>().is_valid()) {
+            class_<State>(scope, name)
+                .def("__iter__", [](handle h) { return h; })
+                .def("__next__",
+                    [](State &s) -> ValueType {
+                        if (!s.first_or_done)
+                            ++s.it;
+                        else
+                            s.first_or_done = false;
+
+                        if (s.it == s.end) {
+                            s.first_or_done = true;
+                            throw stop_iteration();
+                        }
+
+                        return Access()(s.it);
+                    },
+                    std::forward<Extra>(extra)...,
+                    Policy);
+        }
     }
-
     return borrow<typed<iterator, ValueType>>(cast(State{
         std::forward<Iterator>(first), std::forward<Sentinel>(last), true }));
 }

tests/common.py

@@ -1,6 +1,7 @@
 import platform
 import gc
 import pytest
+import threading
 
 is_pypy = platform.python_implementation() == 'PyPy'
 is_darwin = platform.system() == 'Darwin'
@@ -17,3 +18,25 @@ def collect() -> None:
 
 xfail_on_pypy_darwin = pytest.mark.xfail(
     is_pypy and is_darwin, reason="This test for some reason fails on PyPy/Darwin")
+
+
+# Helper function to parallelize execution of a function. We intentionally
+# don't use the Python threads pools here to have threads shut down / start
+# between test cases.
+def parallelize(func, n_threads):
+    barrier = threading.Barrier(n_threads)
+    result = [None]*n_threads
+
+    def wrapper(i):
+        barrier.wait()
+        result[i] = func()
+
+    workers = []
+    for i in range(n_threads):
+        t = threading.Thread(target=wrapper, args=(i,))
+        t.start()
+        workers.append(t)
+
+    for worker in workers:
+        worker.join()
+    return result

tests/test_make_iterator.py

@@ -1,5 +1,5 @@
 import test_make_iterator_ext as t
-import pytest
+from common import parallelize
 
 data = [
     {},
@@ -30,6 +30,10 @@ def test03_items_iterator():
         assert sorted(list(m.items_l())) == sorted(list(d.items()))
 
 
+def test03_items_iterator_parallel(n_threads=8):
+    parallelize(test03_items_iterator, n_threads=n_threads)
+
+
 def test04_passthrough_iterator():
     for d in data:
         m = t.StringMap(d)

tests/test_thread.py

@@ -1,29 +1,6 @@
 import test_thread_ext as t
 from test_thread_ext import Counter
-
-import threading
-
-# Helper function to parallelize execution of a function. We intentionally
-# don't use the Python threads pools here to have threads shut down / start
-# between test cases.
-def parallelize(func, n_threads):
-    barrier = threading.Barrier(n_threads)
-    result = [None]*n_threads
-
-    def wrapper(i):
-        barrier.wait()
-        result[i] = func()
-
-    workers = []
-    for i in range(n_threads):
-        t = threading.Thread(target=wrapper, args=(i,))
-        t.start()
-        workers.append(t)
-
-    for worker in workers:
-        worker.join()
-    return result
-
+from common import parallelize
 
 def test01_object_creation(n_threads=8):
     # This test hammers 'inst_c2p' from multiple threads, and