remove vestigial ad.reducing_transposes table

these were an xmap / avals-with-names named axis thing, but that stuff is gone so we can simplify

jax/_src/ad_checkpoint.py

@@ -652,7 +652,7 @@ def remat_transpose(out_cts, *in_primals, jaxpr, **params):
             for x in in_primals]
   assert next(in_cts_nz_, None) is next(in_zeros_, None) is None
   return in_cts
-ad.reducing_transposes[remat_p] = remat_transpose
+ad.primitive_transposes[remat_p] = remat_transpose
 
 # TODO(mattjj): move this to ad.py
 def transpose_jaxpr(jaxpr: core.ClosedJaxpr, in_linear: bool | Sequence[bool],

jax/_src/interpreters/ad.py

@@ -277,9 +277,6 @@ def backward_pass(jaxpr: core.Jaxpr, transform_stack,
           call_jaxpr = params.pop('call_jaxpr')
           cts_out = get_primitive_transpose(eqn.primitive)(
               params, call_jaxpr, invals, cts_in, cts_in_avals)
-        elif eqn.primitive in reducing_transposes:
-          cts_out = reducing_transposes[eqn.primitive](
-              cts_in, *invals, **eqn.params)
         else:
           cts_out = get_primitive_transpose(eqn.primitive)(
               cts_in, *invals, **eqn.params)
@@ -586,8 +583,6 @@ class LinearizeTracer(Tracer):
 
 primitive_jvps : dict[core.Primitive, Callable] = {}
 primitive_transposes: dict[core.Primitive, Callable] = {}
-# transpose rules that internally perform reductions over the given named axes
-reducing_transposes: dict[core.Primitive, Callable] = {}
 primitive_linearizations : dict[core.Primitive, Callable]  = {}
 
 def deflinear(primitive, transpose_rule):
@@ -871,3 +866,6 @@ class CustomVJPException(Exception):
            "closed-over value into the custom_vjp function as an argument, and "
            "adapting the custom_vjp fwd and bwd rules.")
     super().__init__(msg)
+
+# TODO(mattjj): remove this vestigial dict
+reducing_transposes: dict[core.Primitive, Callable] = {}

jax/_src/lax/control_flow/conditionals.py

@@ -780,7 +780,7 @@ cond_p.multiple_results = True
 cond_p.def_impl(partial(dispatch.apply_primitive, cond_p))
 cond_p.def_effectful_abstract_eval(_cond_abstract_eval)
 ad.primitive_jvps[cond_p] = _cond_jvp
-ad.reducing_transposes[cond_p] = _cond_transpose
+ad.primitive_transposes[cond_p] = _cond_transpose
 pe.custom_partial_eval_rules[cond_p] = _cond_partial_eval
 batching.fancy_primitive_batchers[cond_p] = _cond_batching_rule
 xla.register_initial_style_primitive(cond_p)

jax/_src/lax/control_flow/loops.py

@@ -1228,7 +1228,7 @@ scan_p.multiple_results = True
 scan_p.def_impl(partial(dispatch.apply_primitive, scan_p))
 scan_p.def_effectful_abstract_eval(_scan_abstract_eval)
 ad.primitive_jvps[scan_p] = _scan_jvp
-ad.reducing_transposes[scan_p] = _scan_transpose
+ad.primitive_transposes[scan_p] = _scan_transpose
 pe.custom_partial_eval_rules[scan_p] = _scan_partial_eval
 xla.register_initial_style_primitive(scan_p)
 mlir.register_lowering(scan_p,

jax/_src/pjit.py

@@ -2385,7 +2385,7 @@ def _pjit_transpose(cts_in, *primals_in,
     _set_states(attrs_tracked, final_states)
 
   return tree_unflatten(cts_out_treedef, nz_cts_out)
-ad.reducing_transposes[pjit_p] = _pjit_transpose
+ad.primitive_transposes[pjit_p] = _pjit_transpose
 
 
 @weakref_lru_cache