ENH: lazy_xp_function support for iterators (data-apis#418)

Author: crusaderky

src/array_api_extra/_lib/_utils/_helpers.py

@@ -6,7 +6,7 @@
 import math
 import pickle
 import types
-from collections.abc import Callable, Generator, Iterable
+from collections.abc import Callable, Generator, Iterable, Iterator
 from functools import wraps
 from types import ModuleType
 from typing import (
@@ -512,13 +512,24 @@ class _AutoJITWrapper(Generic[T]):  # numpydoc ignore=PR01
     convert them to/from PyTrees.
     """
 
-    obj: T
+    _obj: Any
+    _is_iter: bool
     _registered: ClassVar[bool] = False
-    __slots__: tuple[str, ...] = ("obj",)
+    __slots__: tuple[str, ...] = ("_is_iter", "_obj")
 
     def __init__(self, obj: T) -> None:  # numpydoc ignore=GL08
         self._register()
-        self.obj = obj
+        if isinstance(obj, Iterator):
+            self._obj = list(obj)
+            self._is_iter = True
+        else:
+            self._obj = obj
+            self._is_iter = False
+
+    @property
+    def obj(self) -> T:  # numpydoc ignore=RT01
+        """Return wrapped object."""
+        return iter(self._obj) if self._is_iter else self._obj
 
     @classmethod
     def _register(cls) -> None:  # numpydoc ignore=SS06
@@ -531,7 +542,7 @@ def _register(cls) -> None:  # numpydoc ignore=SS06
 
             jax.tree_util.register_pytree_node(
                 cls,
-                lambda obj: pickle_flatten(obj, jax.Array),  # pyright: ignore[reportUnknownArgumentType]
+                lambda instance: pickle_flatten(instance, jax.Array),  # pyright: ignore[reportUnknownArgumentType]
                 lambda aux_data, children: pickle_unflatten(children, aux_data),  # pyright: ignore[reportUnknownArgumentType]
             )
             cls._registered = True
@@ -556,6 +567,7 @@ def jax_autojit(
     - Automatically descend into non-array return values and find ``jax.Array`` objects
       inside them, then rebuild them downstream of exiting the JIT, swapping the JAX
       tracer objects with concrete arrays.
+    - Returned iterators are immediately completely consumed.
 
     See Also
     --------

tests/test_helpers.py

@@ -1,3 +1,4 @@
+from collections.abc import Iterator
 from types import ModuleType
 from typing import TYPE_CHECKING, Generic, TypeVar, cast
 
@@ -417,3 +418,16 @@ def f(x: list[int]) -> list[int]:
         out = f([1, 2])
         assert isinstance(out, list)
         assert out == [3, 4]
+
+    def test_iterators(self, jnp: ModuleType):
+        @jax_autojit
+        def f(x: Array) -> Iterator[Array]:
+            return (x + i for i in range(2))
+
+        inp = jnp.asarray([1, 2])
+        out = f(inp)
+        assert isinstance(out, Iterator)
+        xp_assert_equal(next(out), jnp.asarray([1, 2]))
+        xp_assert_equal(next(out), jnp.asarray([2, 3]))
+        with pytest.raises(StopIteration):
+            _ = next(out)

tests/test_testing.py

@@ -1,4 +1,4 @@
-from collections.abc import Callable
+from collections.abc import Callable, Iterator
 from types import ModuleType
 from typing import cast
 
@@ -468,3 +468,22 @@ def test_patch_lazy_xp_functions_deprecated_monkeypatch(
     monkeypatch.undo()
     y = non_materializable5(x)
     xp_assert_equal(y, x)
+
+
+def my_iter(x: Array) -> Iterator[Array]:
+    yield x[0, :]
+    yield x[1, :]
+
+
+lazy_xp_function(my_iter)
+
+
+def test_patch_lazy_xp_functions_iter(xp: ModuleType):
+    x = xp.asarray([[1.0, 2.0], [3.0, 4.0]])
+    it = my_iter(x)
+
+    assert isinstance(it, Iterator)
+    xp_assert_equal(next(it), x[0, :])
+    xp_assert_equal(next(it), x[1, :])
+    with pytest.raises(StopIteration):
+        _ = next(it)