Increase the minimum SciPy version to 1.11.1.

(1.11.0 was yanked from PyPi because of licensing problems, so 1.11.1 is the oldest 1.11 release.)

PiperOrigin-RevId: 713073731

CHANGELOG.md

@@ -19,6 +19,8 @@ When releasing, please add the new-release-boilerplate to docs/pallas/CHANGELOG.
 * Changes:
   * The minimum NumPy version is now 1.25. NumPy 1.25 will remain the minimum
     supported version until June 2025.
+  * The minimum SciPy version is now 1.11. SciPy 1.11 will remain the minimum
+    supported version until June 2025.
   * {func}`jax.numpy.einsum` now defaults to `optimize='auto'` rather than
     `optimize='optimal'`. This avoids exponentially-scaling trace-time in
     the case of many arguments ({jax-issue}`#25214`).

jaxlib/setup.py

@@ -61,8 +61,7 @@ setup(
     packages=['jaxlib', 'jaxlib.xla_extension'],
     python_requires='>=3.10',
     install_requires=[
-        'scipy>=1.10',
-        "scipy>=1.11.1; python_version>='3.12'",
+        'scipy>=1.11.1',
         'numpy>=1.25',
         'ml_dtypes>=0.2.0',
     ],

setup.py

@@ -60,8 +60,7 @@ setup(
         'numpy>=1.25',
         "numpy>=1.26.0; python_version>='3.12'",
         'opt_einsum',
-        'scipy>=1.10',
-        "scipy>=1.11.1; python_version>='3.12'",
+        'scipy>=1.11.1',
     ],
     extras_require={
         # Minimum jaxlib version; used in testing.

tests/linalg_test.py

@@ -1686,7 +1686,7 @@ class ScipyLinalgTest(jtu.JaxTestCase):
 
   @jtu.sample_product(
     n=[1, 4, 5, 20, 50, 100],
-    batch_size=[(), (2,), (3, 4)] if scipy_version >= (1, 9, 0) else [()],
+    batch_size=[(), (2,), (3, 4)],
     dtype=int_types + float_types + complex_types
   )
   def testExpm(self, n, batch_size, dtype):