[Rollback] Bumped the minimum ml_dtypes version to 0.4.0

Reverts e86c436e7f8e4e0546eff8bc2d3756a7c49dc83b

PiperOrigin-RevId: 642741832

CHANGELOG.md

@@ -8,6 +8,12 @@ Remember to align the itemized text with the first line of an item within a list
 
 ## jax 0.4.30
 
+* Changes
+  * JAX supports ml_dtypes >= 0.2. In 0.4.29 release, the ml_dtypes version was
+    bumped to 0.4.0 but this has been rolled back in this release to give users
+    of both TensorFlow and JAX more time to migrate to a newer TensorFlow
+    release.
+
 ## jaxlib 0.4.30
 
 ## jax 0.4.29 (June 10, 2024)

jax/_src/dtypes.py

@@ -42,8 +42,8 @@ try:
 except:
   pass
 else:
-  if _ml_dtypes_version < (0, 4, 0):
-    raise ValueError("JAX requires ml_dtypes version 0.4.0 or newer; "
+  if _ml_dtypes_version < (0, 2, 0):
+    raise ValueError("JAX requires ml_dtypes version 0.2.0 or newer; "
                      f"installed version is {ml_dtypes.__version__}.")
 
 export = set_module('jax.dtypes')
@@ -500,7 +500,7 @@ def _type_promotion_lattice(jax_numpy_dtype_promotion: str) -> dict[JAXType, lis
   This DAG maps each type to its immediately higher type on the lattice.
   """
   b1, = _bool_types
-  uint4, u1, u2, u4, u8, int4, i1, i2, i4, i8 = _int_types
+  _uint4, u1, u2, u4, u8, _int4, i1, i2, i4, i8 = _int_types
   *f1_types, bf, f2, f4, f8 = _float_types
   c4, c8 = _complex_types
   i_, f_, c_ = _weak_types
@@ -508,13 +508,18 @@ def _type_promotion_lattice(jax_numpy_dtype_promotion: str) -> dict[JAXType, lis
     out: dict[JAXType, list[JAXType]]
     out = {
       b1: [i_],
-      uint4: [], u1: [i2, u2], u2: [i4, u4], u4: [i8, u8], u8: [f_],
-      i_: [uint4, int4, u1, i1],
-      int4: [], i1: [i2], i2: [i4], i4: [i8], i8: [f_],
+      u1: [i2, u2], u2: [i4, u4], u4: [i8, u8], u8: [f_],
+      i_: [u1, i1], i1: [i2], i2: [i4], i4: [i8], i8: [f_],
       f_: [*f1_types, bf, f2, c_],
       **{t: [] for t in f1_types}, bf: [f4], f2: [f4], f4: [f8, c4], f8: [c8],
       c_: [c4], c4: [c8], c8: [],
     }
+    if _int4_dtype is not None:
+      out[i_].append(_int4_dtype)
+      out[_int4_dtype] = []
+    if _uint4_dtype is not None:
+      out[i_].append(_uint4_dtype)
+      out[_uint4_dtype] = []
     return out
   elif jax_numpy_dtype_promotion == 'strict':
     return {

jax/_src/public_test_util.py

@@ -104,6 +104,15 @@ def _assert_numpy_allclose(a, b, atol=None, rtol=None, err_msg=''):
   def maybe_upcast(x):
     if x.dtype in custom_float_dtypes:
       return x.astype(np.float32)
+    # TODO(reedwm): Upcasting int4 to int8 will no longer be neccessary once
+    # ml_dtypes has a stable release with commit
+    # https://github.com/jax-ml/ml_dtypes/commit/348fd3704306cae97f617c38045cee6bc416bf10.
+    # Remove these checks once JAX depends on a version on ml_dtypes with that
+    # commit.
+    if x.dtype == _dtypes.int4:
+      return x.astype(np.int8)
+    if x.dtype == _dtypes.uint4:
+      return x.astype(np.uint8)
     return x
 
   a = maybe_upcast(a)

jaxlib/setup.py

@@ -64,7 +64,7 @@ setup(
         'scipy>=1.9',
         "scipy>=1.11.1; python_version>='3.12'",
         'numpy>=1.22',
-        'ml_dtypes>=0.4.0',
+        'ml_dtypes>=0.2.0',
     ],
     extras_require={
       'cuda12_pip': [

setup.py

@@ -54,7 +54,7 @@ setup(
     package_data={'jax': ['py.typed', "*.pyi", "**/*.pyi"]},
     python_requires='>=3.9',
     install_requires=[
-        'ml_dtypes>=0.4.0',
+        'ml_dtypes>=0.2.0',
         'numpy>=1.22',
         "numpy>=1.23.2; python_version>='3.11'",
         "numpy>=1.26.0; python_version>='3.12'",