Merge pull request #12497 from mattjj:djax-dag-fix1

PiperOrigin-RevId: 477038279

jax/interpreters/partial_eval.py

@@ -2095,7 +2095,9 @@ def infer_lambda_input_type(
   idxs, implicit_types = _collect_implicit(args, specs)
   implicit_sig = [(ty, False) for ty in implicit_types]
   explicit_sig = [(_arg_type(idxs, x, s), True) for x, s in zip(args, specs)]
-  return (*implicit_sig, *explicit_sig)
+  input_type = (*implicit_sig, *explicit_sig)
+  lu._check_input_type(input_type)
+  return input_type
 
 def _canonicalize_specs(
     ndims: Sequence[int], specs: Optional[Sequence[AbstractedAxesSpec]]
@@ -2143,6 +2145,7 @@ def _complete_specs(
              for x, spec in zip(args, specs))
   return specs
 
+
 def _collect_implicit(
     args: Sequence[Any], specs: List[Dict[int, AbstractedAxisName]]
   ) -> Tuple[Dict[AbstractedAxisName, DBIdx], List[AbstractValue]]:
@@ -2153,24 +2156,23 @@ def _collect_implicit(
   idxs: Dict[AbstractedAxisName, DBIdx] = {}
   implicit_types: List[AbstractValue] = []
   explicit_tracers: Dict[TracerId, int] = {}
-  counter = (DBIdx(i) for i in it.count())
+  counter = it.count()
 
   # Add implicit arguments to idxs.
-
   for explicit_idx, (x, spec) in enumerate(zip(args, specs)):
     for i, name in spec.items():
       if name not in idxs and id(x.shape[i]) not in explicit_tracers:
-        idxs[name] = next(counter)
+        idxs[name] = DBIdx(next(counter))
         implicit_types.append(raise_to_shaped(get_aval(x.shape[i])))
     if isinstance(x, Tracer):
-      explicit_tracers[id(x)] = explicit_idx
+      explicit_tracers.setdefault(id(x), explicit_idx)  # use the first
 
   # Now that we know the implicit args, add explicit args to idxs.
   offset = len(implicit_types)
   for x, spec in zip(args, specs):
     for i, name in spec.items():
       if id(x.shape[i]) in explicit_tracers:
-        idxs[name] = DBIdx(offset + explicit_tracers[id(x.shape[i])])
+        idxs.setdefault(name, DBIdx(offset + explicit_tracers[id(x.shape[i])]))
 
   return idxs, implicit_types
 

jax/linear_util.py

@@ -236,17 +236,29 @@ def wrap_init(f, params=None) -> WrappedFun:
   params = () if params is None else tuple(sorted(params.items()))
   return WrappedFun(f, (), (), params, None)
 
-def annotate(f: WrappedFun,
-             in_type: Optional[Tuple[Tuple[core.AbstractValue, bool], ...]]
-             ) -> WrappedFun:
+
+def annotate(f: WrappedFun, in_type: core.InputType) -> WrappedFun:
   assert f.in_type is None
   if in_type is None:
     return f
+  _check_input_type(in_type)
+  return WrappedFun(f.f, f.transforms, f.stores, f.params, in_type)
+
+def _check_input_type(in_type: core.InputType) -> None:
+  # Check that in_type is syntactically well-formed
   assert (type(in_type) is tuple and all(type(e) is tuple for e in in_type) and
           all(isinstance(a, core.AbstractValue) and type(b) is bool
               and not isinstance(a, core.ConcreteArray) for a, b in in_type) and
           all(isinstance(d, (int, core.BInt, core.DBIdx)) for a, _ in in_type
               if type(a) is core.DShapedArray for d in a.shape))
+
+  # Check that all DBIdx point to positions to the left of the input on which
+  # they appear.
+  assert all(d.val < i for i, (aval, _) in enumerate(in_type)
+             if isinstance(aval, core.DShapedArray) for d in aval.shape
+             if isinstance(d, core.DBIdx))
+
+  # Check that all implicit arguments have at least one DBIdx pointing to them.
   provided = [e for _, e in in_type]
   for aval, _ in in_type:
     if type(aval) is core.DShapedArray:
@@ -254,7 +266,6 @@ def annotate(f: WrappedFun,
         if isinstance(d, core.DBIdx):
           provided[d.val] = True
   assert all(provided)
-  return WrappedFun(f.f, f.transforms, f.stores, f.params, in_type)
 
 
 class _CacheLocalContext(threading.local):

tests/dynamic_api_test.py

@@ -1354,6 +1354,12 @@ class DynamicShapeTest(jtu.JaxTestCase):
     d, = jaxpr.eqns[0].outvars
     self.assertEqual(d.aval.shape, (a, a))
 
+  def test_inferring_valid_subjaxpr_type_add(self):
+    def f(x):
+      return x + x.shape[0]
+
+    jax.make_jaxpr(f, abstracted_axes=('n',))(jnp.arange(3))  # doesn't crash
+
 
 if __name__ == '__main__':
   absltest.main(testLoader=jtu.JaxTestLoader())