[jax2tf] Disable jax2tf with non-native serialization.

jax2tf with native_serialization=False or with enable_xla=False have been deprecated since July 2024.

This change turns an attempt to use `native_serialization=False` or `enable_xla=False` into an error.

PiperOrigin-RevId: 689708392

CHANGELOG.md

@@ -12,6 +12,12 @@ When releasing, please add the new-release-boilerplate to docs/pallas/CHANGELOG.
 
 ## jax 0.4.36
 
+* Breaking Changes
+  * {func}`jax.experimental.jax2tf.convert` with `native_serialization=False`
+    or with `enable_xla=False` have been deprecated since July 2024, with
+    JAX version 0.4.31. Now we removed support for these use cases. `jax2tf`
+    with native serialization will still be supported.
+
 ## jax 0.4.35 (Oct 22, 2024)
 
 * Breaking Changes
@@ -21,6 +27,10 @@ When releasing, please add the new-release-boilerplate to docs/pallas/CHANGELOG.
   * `jax.experimental.host_callback` has been deprecated since March 2024, with
     JAX version 0.4.26. Now we removed it.
     See {jax-issue}`#20385` for a discussion of alternatives.
+  * {func}`jax.experimental.jax2tf.convert` with `native_serialization=False`
+    or with `enable_xla=False` have been deprecated since July 2024, with
+    JAX version 0.4.31. Now we removed support for these use cases. `jax2tf`
+    with native serialization is still supported.
 
 * Changes:
   * `jax.lax.FftType` was introduced as a public name for the enum of FFT

jax/experimental/jax2tf/jax2tf.py

@@ -119,6 +119,10 @@ def _sanitize_scope_name(name):
 # Line below is different externally and internally.
 allow_enable_xla_false = lambda: True
 
+# TODO(b/353437398): Deprecate support for `native_serialization=False`.
+# Line below is different externally and internally.
+allow_native_serialization_false = lambda: True
+
 # A value suitable in a TF tracing context: tf.Tensor, tf.Variable,
 # or Python scalar or numpy.ndarray. (A tf.EagerTensor is a tf.Tensor.)
 TfVal = Any
@@ -294,8 +298,8 @@ def convert(fun_jax: Callable,
       See [the README](https://github.com/jax-ml/jax/blob/main/jax/experimental/jax2tf/README.md#shape-polymorphic-conversion)
       for more details.
 
-    polymorphic_constraints: a sequence of contraints on symbolic dimension expressions, of
-      the form `e1 >= e2` or `e1 <= e2`.
+    polymorphic_constraints: a sequence of constraints on symbolic dimension
+      expressions, of the form `e1 >= e2` or `e1 <= e2`.
       See more details at https://github.com/jax-ml/jax/blob/main/jax/experimental/jax2tf/README.md#user-specified-symbolic-constraints.
     with_gradient: if set (default), add a tf.custom_gradient to the lowered
       function, by converting the ``jax.vjp(fun)``. This means that reverse-mode
@@ -332,28 +336,38 @@ def convert(fun_jax: Callable,
     tuple/lists/dicts thereof), and returns TfVals as outputs, and uses
     only TensorFlow ops and thus can be called from a TensorFlow program.
   """
-  if not enable_xla:
-    if allow_enable_xla_false():
-      warnings.warn("jax2tf.convert with enable_xla=False is deprecated.",
-                    DeprecationWarning,
-                    stacklevel=2)
-    else:
-      raise ValueError("jax2tf.convert with enable_xla=False is not supported.")
-
   if native_serialization is DEFAULT_NATIVE_SERIALIZATION:
     if not enable_xla:
       native_serialization = False
     else:
       native_serialization = config.jax2tf_default_native_serialization.value
 
-  if not native_serialization:
-    warnings.warn(
-        "jax2tf.convert with native_serialization=False is deprecated.",
-        DeprecationWarning,
-        stacklevel=2)
-  if native_serialization and not enable_xla:
-    raise ValueError(
-        "native_serialization is not supported with enable_xla=False")
+  if not enable_xla:
+    if allow_enable_xla_false():
+      warnings.warn(
+          "jax2tf.convert with enable_xla=False has been deprecated "
+          "since July 2024.",
+          DeprecationWarning,
+          stacklevel=2)
+      if native_serialization:
+        raise ValueError(
+            "native_serialization is not supported with enable_xla=False")
+    else:
+      raise ValueError(
+          "jax2tf.convert with enable_xla=False has been deprecated "
+          "since July 2024 and it is not supported anymore.")
+
+  elif not native_serialization:
+    if allow_native_serialization_false():
+      warnings.warn(
+          "jax2tf.convert with native_serialization=False has been deprecated "
+          "since July 2024.",
+          DeprecationWarning,
+          stacklevel=2)
+    else:
+      raise ValueError(
+          "jax2tf.convert with native_serialization=False has been deprecated "
+          "since July 2024 and it is not supported anymore.")
 
   if not native_serialization and polymorphic_constraints:
     raise ValueError(
@@ -2188,7 +2202,7 @@ def _dot_general(lhs, rhs, *, dimension_numbers,
                  _out_aval: core.ShapedArray):
   """Implementation of lax.dot_general_p in terms of tf.linalg.einsum."""
   # TODO(b/293247337): we ought to turn on this safety check, but this leads to
-  # failures. Since we are going to turn on native serializaton soon, wait
+  # failures. Since we are going to turn on native serialization soon, wait
   # until then to turn on this check.
   # lhs_aval, rhs_aval = _in_avals
   # if lhs_aval.dtype != rhs_aval.dtype:

jax/experimental/jax2tf/tests/call_tf_test.py

@@ -90,7 +90,7 @@ def setUp(self):
     super().setUp()
     self.warning_ctx = jtu.ignore_warning(
         message=(
-            "(jax2tf.convert with native_serialization=False is deprecated"
+            "(jax2tf.convert with native_serialization=False has been deprecated"
             "|Calling from_dlpack with a DLPack tensor is deprecated)"
         )
     )
@@ -897,7 +897,7 @@ def setUp(self):
     super().setUp()
     self.warning_ctx = jtu.ignore_warning(
         message=(
-            "(jax2tf.convert with native_serialization=False is deprecated"
+            "(jax2tf.convert with native_serialization=False has been deprecated"
             "|Calling from_dlpack with a DLPack tensor is deprecated)"
         )
     )
@@ -1203,7 +1203,7 @@ def setUp(self):
     super().setUp()
     self.warning_ctx = jtu.ignore_warning(
         message=(
-            "(jax2tf.convert with native_serialization=False is deprecated"
+            "(jax2tf.convert with native_serialization=False has been deprecated"
             "|Calling from_dlpack with a DLPack tensor is deprecated)"
         )
     )

jax/experimental/jax2tf/tests/jax2tf_test.py

@@ -79,7 +79,7 @@ def setUpClass(cls):
   def setUp(self):
     super().setUp()
     self.warning_ctx = jtu.ignore_warning(
-        message="jax2tf.convert with native_serialization=False is deprecated"
+        message="jax2tf.convert with native_serialization=False has been deprecated"
     )
     self.warning_ctx.__enter__()
 
@@ -1722,7 +1722,7 @@ class Jax2tfWithCustomPRNGTest(tf_test_util.JaxToTfTestCase):
   def setUp(self):
     super().setUp()
     self.warning_ctx = jtu.ignore_warning(
-        message="jax2tf.convert with native_serialization=False is deprecated"
+        message="jax2tf.convert with native_serialization=False has been deprecated"
     )
     self.warning_ctx.__enter__()
 
@@ -1763,7 +1763,7 @@ def setUp(self):
     super().setUp()
 
   @jtu.ignore_warning(
-      message="jax2tf.convert with native_serialization=False is deprecated"
+      message="jax2tf.convert with native_serialization=False has been deprecated"
   )
   def test_simple(self):
     self.ConvertAndCompare(jnp.sin, 0.7)

jax/experimental/jax2tf/tests/shape_poly_test.py

@@ -1031,7 +1031,7 @@ def f_jax(x):  # A function whose gradient is a constant
     self.assertAllClose(f_jax(x), restored_f(x))
 
   @jtu.ignore_warning(
-      message="jax2tf.convert with native_serialization=False is deprecated"
+      message="jax2tf.convert with native_serialization=False has been deprecated"
   )
   def test_readme_examples(self):
     """Some of the examples from the README."""
@@ -1124,31 +1124,6 @@ def f2_jax(x):  # f32[b, b]
     # JAX with static shapes sees that x.shape[0] != x.shape[1]
     self.assertEqual(jnp.sum(x45), f2_jax(x45))
 
-    # In graph serialization eager mode, we catch the broken assumption b >= 1
-    with self.assertRaisesRegex(
-        tf.errors.InvalidArgumentError,
-        re.escape(
-          "Found inconsistency between dimension size args[0].shape[1] (= 5) "
-          "and the specification 'b' (= 4)")):
-      jax2tf.convert(f2_jax, polymorphic_shapes=["b, b"],
-                     native_serialization=False)(x45)
-
-    # In graph serialization graph mode we also catch it (except on TPU, where
-    # the behavior is as for jit_compile=1)
-
-    f2_tf = tf.function(
-        jax2tf.convert(f2_jax, polymorphic_shapes=["b, b"],
-                       native_serialization=False),
-        autograph=False,
-    ).get_concrete_function(tf.TensorSpec([None, None], dtype=np.float32))
-    if jtu.test_device_matches(["tpu"]):
-      self.assertEqual(1. + jnp.sum(x45), f2_tf(x45))
-    else:
-      with self.assertRaisesRegex(
-          tf.errors.InvalidArgumentError,
-          r"Found inconsistency"):
-        _ = f2_tf(x45)
-
     # We also catch the error with native serialization
     with self.assertRaisesRegex(
         tf.errors.InvalidArgumentError,