Future-proof JAX array API import

array_api_compat/common/_helpers.py

@@ -377,9 +377,13 @@ def your_function(x, y):
             elif use_compat is False:
                 import jax.numpy as jnp
             else:
-                # jax.experimental.array_api is already an array namespace. We do
-                # not have a wrapper submodule for it.
-                import jax.experimental.array_api as jnp
+                # JAX v0.4.32 and newer implements the array API directly in jax.numpy.
+                # For older JAX versions, it is available via jax.experimental.array_api.
+                import jax.numpy
+                if hasattr(jax.numpy, "__array_api_version__"):
+                    jnp = jax.numpy
+                else:
+                    import jax.experimental.array_api as jnp
             namespaces.add(jnp)
         elif is_pydata_sparse_array(x):
             if use_compat is True:
@@ -613,8 +617,9 @@ def to_device(x: Array, device: Device, /, *, stream: Optional[Union[int, Any]]
             return x
         raise ValueError(f"Unsupported device {device!r}")
     elif is_jax_array(x):
-        # This import adds to_device to x
-        import jax.experimental.array_api # noqa: F401
+        if not hasattr(x, "__array_namespace__"):
+            # In JAX v0.4.31 and older, this import adds to_device method to x.
+            import jax.experimental.array_api # noqa: F401
         return x.to_device(device, stream=stream)
     elif is_pydata_sparse_array(x) and device == _device(x):
         # Perform trivial check to return the same array if

docs/index.md

@@ -63,7 +63,8 @@ import array_api_compat.dask as da
 ```{note}
 There are no `array_api_compat` submodules for JAX, sparse, or ndonnx. These
 support for these libraries is contained in the libraries themselves (JAX
-support is in the `jax.experimental.array_api` module). The
+support is in the `jax.numpy` module in JAX v0.4.32 or newer, and in the
+`jax.experimental.array_api` module for older JAX versions). The
 array-api-compat support for these libraries consists of supporting them in
 the [helper functions](helper-functions).
 ```

tests/_helpers.py

@@ -18,7 +18,11 @@ def import_(library, wrapper=False):
         pytest.importorskip(library)
     if wrapper:
         if 'jax' in library:
-            library = 'jax.experimental.array_api'
+            # JAX v0.4.32 implements the array API directly in jax.numpy
+            # Older jax versions use jax.experimental.array_api
+            jax_numpy = import_module("jax.numpy")
+            if not hasattr(jax_numpy, "__array_api_version__"):
+                library = 'jax.experimental.array_api'
         elif library.startswith('sparse'):
             library = 'sparse'
         else:

tests/test_array_namespace.py

@@ -26,8 +26,14 @@ def test_array_namespace(library, api_version, use_compat):
 
     if use_compat is False or use_compat is None and library not in wrapped_libraries:
         if library == "jax.numpy" and use_compat is None:
-            import jax.experimental.array_api
-            assert namespace == jax.experimental.array_api
+            import jax.numpy
+            if hasattr(jax.numpy, "__array_api_version__"):
+                # JAX v0.4.32 or later uses jax.numpy directly
+                assert namespace == jax.numpy
+            else:
+                # JAX v0.4.31 or earlier uses jax.experimental.array_api
+                import jax.experimental.array_api
+                assert namespace == jax.experimental.array_api
         else:
             assert namespace == xp
     else:
@@ -58,8 +64,11 @@ def test_array_namespace(library, api_version, use_compat):
 assert 'jax.experimental.array_api' not in sys.modules
 namespace = array_api_compat.array_namespace(array, api_version={api_version!r})
 
-import jax.experimental.array_api
-assert namespace == jax.experimental.array_api
+if hasattr(jax.numpy, '__array_api_version__'):
+    assert namespace == jax.numpy
+else:
+    import jax.experimental.array_api
+    assert namespace == jax.experimental.array_api
 """
         subprocess.run([sys.executable, "-c", code], check=True)