Clean up and fix primal type to tangent type mapping

This is part of the ["stackless"](#23299) change. I'm splitting it out into a separate PR because we need it for some work on sharding types.

Changes:
  1. Rename `at_least_vspace` to `to_tangent_type` since that's what we always meant by it. `at_least_vspace` was always a bad name (sorry!) but it makes even less sense when you can have a special tangent type for a primal types that's already a vector space itself.
  2. Replace `Zero.from_value` with `Zero.from_primal_value`, which does the required primal-type-to-tangent-type conversion.
  3. Add `to_tangent_type` calls in various other places they're missing.
  4. Remove non-support for float0 in custom deriviatives?
  5. [Optional, WIP] Reinstate some checks that had been skipped over, presumably because of these bugs. (We'll see how far I get with it. Might end up being a separate PR.)
PiperOrigin-RevId: 676115753

jax/_src/ad_checkpoint.py

@@ -514,7 +514,7 @@ def remat_jvp(primals, tangents, jaxpr, prevent_cse, differentiated, policy):
       prevent_cse=prevent_cse, differentiated=differentiated, policy=policy)
   out_primals, out_tangents_ = split_list(outs, [len(jaxpr.outvars)])
   out_tangents_ = iter(out_tangents_)
-  out_tangents = [next(out_tangents_) if nz else ad_util.Zero.from_value(p)
+  out_tangents = [next(out_tangents_) if nz else ad_util.Zero.from_primal_value(p)
                   for p, nz in zip(out_primals, out_nz)]
   return out_primals, out_tangents
 ad.primitive_jvps[remat_p] = remat_jvp

jax/_src/ad_util.py

@@ -65,8 +65,8 @@ def __init__(self, aval: core.AbstractValue):
   def __repr__(self) -> str:
     return f'Zero({self.aval})'
   @staticmethod
-  def from_value(val: Any) -> Zero:
-    return Zero(raise_to_shaped(get_aval(val)))
+  def from_primal_value(val: Any) -> Zero:
+    return Zero(raise_to_shaped(get_aval(val)).to_tangent_aval())
 
 register_pytree_node(Zero, lambda z: ((), z.aval), lambda aval, _: Zero(aval))
 
@@ -82,6 +82,7 @@ def _stop_gradient_impl(x: T) -> T:
 stop_gradient_p.def_abstract_eval(lambda x: x)
 
 
+# User-facing version of `Zero`
 class SymbolicZero:
   def __init__(self, aval: core.AbstractValue) -> None:
     self.aval = aval
@@ -108,6 +109,10 @@ def __getattr__(self, name):
       else:
         return attr
 
+  @staticmethod
+  def from_primal_value(val: Any) -> SymbolicZero:
+    return SymbolicZero(get_aval(val).to_tangent_aval())
+
 JaxTypeOrTracer = Any
 
 def replace_internal_symbolic_zeros(

jax/_src/api.py

@@ -1826,7 +1826,7 @@ def _lift_linearized(jaxpr, primal_avals, io_tree, out_pvals, consts, *py_args):
   def fun(*tangents):
     tangent_avals = list(map(core.get_aval, tangents))
     for primal_aval, tangent_aval in zip(primal_avals, tangent_avals):
-      if not core.typecompat(primal_aval.at_least_vspace(), tangent_aval):
+      if not core.typecompat(primal_aval.to_tangent_aval(), tangent_aval):
         raise ValueError("linearized function called on tangent values inconsistent with "
                          "the original primal values: "
                          f"got {tangent_aval} for primal aval {primal_aval}")
@@ -1869,7 +1869,7 @@ def _vjp_pullback_wrapper(name, out_primal_avals, io_tree, fun, *py_args_):
                      f"got {in_tree}, but expected to match {in_tree_expected}")
   for arg, aval in zip(args, out_primal_avals):
     ct_aval = shaped_abstractify(arg)
-    ct_aval_expected = aval.at_least_vspace()
+    ct_aval_expected = aval.to_tangent_aval()
     if (not core.typecompat(ct_aval, ct_aval_expected) and
         not _temporary_dtype_exception(ct_aval, ct_aval_expected)):
       raise ValueError(

jax/_src/checkify.py

@@ -980,7 +980,7 @@ def jvp(*xs):
     out = core.eval_jaxpr(jvp_jaxpr, jvp_consts, *primals, *nonzero_tangents)
     out_primals, nz_out_tangents = split_list(out, [len(out_zeros)])
     nz_out_tangents_ = iter(nz_out_tangents)
-    out_tangents = [SymbolicZero(core.get_aval(p).at_least_vspace())
+    out_tangents = [SymbolicZero(core.get_aval(p).to_tangent_aval())
                     if z else next(nz_out_tangents_)
                     for p, z in zip(out_primals, out_zeros)]
     assert next(nz_out_tangents_, None) is None

jax/_src/core.py

@@ -1414,9 +1414,13 @@ def definitely_equal(x, y):
 class AbstractValue:
   __slots__: list[str] = []
 
-  def at_least_vspace(self):
+  def to_tangent_aval(self):
     raise NotImplementedError("must override")
 
+  # TODO(dougalm): deprecate this alias
+  def at_least_vspace(self):
+    return self.to_tangent_aval()
+
   def __repr__(self):
     try:
       kv_pairs = (f'{k}={v}' for k, v in self.__dict__.items())
@@ -1524,6 +1528,12 @@ def get_aval(x):
   else:
     return concrete_aval(x)
 
+def get_type(x):
+  aval = get_aval(x)
+  if isinstance(aval, ConcreteArray):
+    return raise_to_shaped(aval)
+  else:
+    return aval
 
 def concretization_function_error(fun, suggest_astype=False):
   fname = getattr(fun, "__name__", fun)
@@ -1647,7 +1657,7 @@ def __repr__(self):
   _oct     = concretization_function_error(oct)
   _index   = concretization_function_error(operator.index)
 
-  def at_least_vspace(self) -> AbstractValue:
+  def to_tangent_aval(self) -> AbstractValue:
     return UnshapedArray(primal_dtype_to_tangent_dtype(self.dtype),
                          self.weak_type)
 
@@ -1786,7 +1796,7 @@ def __hash__(self):
     return hash((self.shape, self.dtype, self.weak_type,
                  getattr(self, 'sharding', None)))
 
-  def at_least_vspace(self):
+  def to_tangent_aval(self):
     return ShapedArray(self.shape, primal_dtype_to_tangent_dtype(self.dtype),
                        self.weak_type)
 
@@ -1945,7 +1955,7 @@ def join(self, other):
     else:
       raise TypeError(self, other)
 
-  def at_least_vspace(self):
+  def to_tangent_aval(self):
     return DShapedArray(self.shape, primal_dtype_to_tangent_dtype(self.dtype),
                         self.weak_type)
 
@@ -2076,7 +2086,7 @@ def join(self, other):
     else:
       assert False, f"Cannot join {self} with {other}"
   def str_short(self, short_dtypes=False): return 'Tok'
-  def at_least_vspace(self): return self
+  def to_tangent_aval(self): return self
 abstract_token: AbstractToken = AbstractToken()
 
 # Singleton shaped array used by all abstract tokens when shape/dtype is needed.

jax/_src/custom_derivatives.py

@@ -67,7 +67,7 @@ def _sum_tangents(_, x, *xs):
   return reduce(ad.add_tangents, xs, x)
 
 def _zeros_like_pytree(x):
-  return tree_map(Zero.from_value, x)
+  return tree_map(Zero.from_primal_value, x)
 
 _stop_gradient = partial(
     tree_map,
@@ -327,24 +327,27 @@ def _flatten_jvp(primal_name, jvp_name, in_tree, maybe_out_type, *args):
            "shapes/dtypes of:\n"
            f"""    {str(ty_tree_).replace("'", "")}""")
       raise TypeError(m)
-  # TODO(mattjj): compare primals' tangent types to tangent objects' types
-  primal_avals_out = [raise_to_shaped(core.get_aval(x), weak_type=False)
-                      for x in primals_out]
+  primal_avals_out = [raise_to_shaped(core.get_aval(x), weak_type=False) for x in primals_out]
+  expected_tangent_avals_out = [
+    raise_to_shaped(core.get_aval(x), weak_type=False).to_tangent_aval()
+    for x in primals_out]
   tangent_avals_out = [raise_to_shaped(core.get_aval(t), weak_type=False)
                        if type(t) is not SymbolicZero else t.aval.strip_weak_type()
                        for t in tangents_out]
-  if primal_avals_out != tangent_avals_out:
-    if len(primal_avals_out) == 1:
-      (av1,), (av2,) = primal_avals_out, tangent_avals_out
+  if expected_tangent_avals_out != tangent_avals_out:
+    if len(expected_tangent_avals_out) == 1:
+      (av_p,), (av_et,), (av_t,) = primal_avals_out, expected_tangent_avals_out, tangent_avals_out
       msg = ("Custom JVP rule must produce primal and tangent outputs with "
-             "equal shapes and dtypes, but got {} and {} respectively.")
-      raise TypeError(msg.format(av1.str_short(), av2.str_short()))
+             "corresponding shapes and dtypes. Expected {} (tangent type of {}) but got {}.")
+      raise TypeError(msg.format(av_et.str_short(), av_p.str_short(), av_t.str_short()))
     else:
       msg = ("Custom JVP rule must produce primal and tangent outputs with "
-             "equal shapes and dtypes, but got:\n{}")
+             "corresponding shapes and dtypes, but got:\n{}")
       disagreements = (
-          f"  primal {av1.str_short()} for tangent {av2.str_short()}"
-          for av1, av2 in zip(primal_avals_out, tangent_avals_out) if av1 != av2)
+          f"  primal {av_p.str_short()} with tangent {av_t.str_short()}, expecting tangent {av_et}"
+          for av_p, av_et, av_t in zip(primal_avals_out, expected_tangent_avals_out, tangent_avals_out)
+          if av_et != av_t)
+
       raise TypeError(msg.format('\n'.join(disagreements)))
   yield primals_out + tangents_out, (out_tree, primal_avals)
 
@@ -392,7 +395,7 @@ def jvp(*xs):
     out = core.eval_jaxpr(jvp_jaxpr, jvp_consts, *primals, *nonzero_tangents)
     out_primals, nz_out_tangents = split_list(out, [len(out_zeros)])
     nz_out_tangents_ = iter(nz_out_tangents)
-    out_tangents = [SymbolicZero(core.get_aval(p).at_least_vspace())
+    out_tangents = [SymbolicZero(core.get_aval(p).to_tangent_aval())
                     if z else next(nz_out_tangents_)
                     for p, z in zip(out_primals, out_zeros)]
     assert next(nz_out_tangents_, None) is None
@@ -780,10 +783,10 @@ def append(x, d):
     raise TypeError(msg.format(in_tree2, in_tree)) from None
   results = []
   for kp, a, ct in zip(keypaths, in_avals, cts_in_flat):
-    if ct is zero or a != a.at_least_vspace():
-      results.append(Zero(a.at_least_vspace()))
+    if ct is zero or a != a.to_tangent_aval():
+      results.append(Zero(a.to_tangent_aval()))
     elif type(ct) is SymbolicZero:
-      if not core.typecompat(a.at_least_vspace(), a_ := ct.aval):
+      if not core.typecompat(a.to_tangent_aval(), a_ := ct.aval):
         msg = ("Custom VJP bwd rule produced a SymbolicZero with a shape/dtype "
                "that does not match the corresponding input tangent shape/dtype: "
                f"at output{keystr(kp)} the SymbolicZero had shape/dtype "
@@ -794,7 +797,7 @@ def append(x, d):
         raise ValueError(msg)
       results.append(Zero(ct.aval))
     else:
-      if (not core.typecompat(a.at_least_vspace(), a_ := core.get_aval(ct))
+      if (not core.typecompat(a.to_tangent_aval(), a_ := core.get_aval(ct))
           and not (_temporary_dtype_exception(a, a_) or
                    _temporary_shape_exception(a, a_))):
         msg = ("Custom VJP bwd rule must produce an output with the same "
@@ -908,16 +911,12 @@ def _custom_vjp_call_jaxpr_jvp(
   _, res_tree = out_trees()
   res_and_primals_out = core.eval_jaxpr(fwd_jaxpr, fwd_consts, *args)
   res, primals_out = split_list(res_and_primals_out, [res_tree.num_leaves])
-  avals_out = [raise_to_shaped(core.get_aval(x)) for x in primals_out]
+  avals_out = [raise_to_shaped(core.get_aval(x)).to_tangent_aval() for x in primals_out]
   args_dot = map(ad.instantiate_zeros, args_dot)
-  # Cast float0 to zeros with the primal dtype because custom vjp rules don't
-  # currently handle float0s
-  args_dot = map(ad.replace_float0s, args, args_dot)
   tangents_out = ad.custom_lin_p.bind(
       *res, *args_dot, num_res=res_tree.num_leaves, bwd=bwd,
       out_avals=avals_out, symbolic_zeros=symbolic_zeros)
   tangents_out = map(lax.tie_p.bind, primals_out, tangents_out)
-  tangents_out = map(ad.recast_to_float0, primals_out, tangents_out)
   return primals_out, tangents_out
 ad.primitive_jvps[custom_vjp_call_jaxpr_p] = _custom_vjp_call_jaxpr_jvp
 
@@ -1039,7 +1038,7 @@ def fwd(*args, **kwargs):
     ans, rule = fun(*args, **kwargs)
     ans_flat, out_tree = tree_flatten((ans,))
     rule, in_tree = flatten_fun_nokwargs(lu.wrap_init(rule), out_tree)
-    ans_avals = [core.get_aval(x).at_least_vspace() for x in ans_flat]
+    ans_avals = [core.get_aval(x).to_tangent_aval() for x in ans_flat]
     jaxpr, _, consts, () = pe.trace_to_jaxpr_dynamic(rule, ans_avals)
     return ans, Residuals(jaxpr, in_tree(), out_tree, consts)
 
@@ -1153,7 +1152,7 @@ def _maybe_perturbed(x: Any) -> bool:
   elif isinstance(x, pe.DynamicJaxprTracer):
     # If x is a DynamicJaxprTracer then we're staging out; differentiation could
     # happen later, but some types always have trivial tangents.
-    vspace = x.aval.at_least_vspace()
+    vspace = x.aval.to_tangent_aval()
     return not (vspace is core.abstract_token or
                 getattr(vspace, 'dtype', None) == dtypes.float0)
   elif not isinstance(x, ad.JVPTracer):
@@ -1425,7 +1424,7 @@ def custom_vjp_by_custom_transpose(fun, fwd, bwd):
   @fun.defjvp
   def jvp(primals, tangents):
     outs, residuals = fwd(*primals)
-    tan_out_types = tree_map(lambda o: core.get_aval(o).at_least_vspace(), outs)
+    tan_out_types = tree_map(lambda o: core.get_aval(o).to_tangent_aval(), outs)
     tan_fn = custom_transpose(partial(disallow_jvp, out_avals=tan_out_types))
     tan_fn.def_transpose(bwd)
     return outs, tan_fn(tan_out_types, residuals, tangents)

jax/_src/dtypes.py

@@ -784,7 +784,7 @@ def check_user_dtype_supported(dtype, fun_name=None):
       uint2,
       uint4,
   ]
-  if np_dtype.kind not in "biufc" and not is_custom_dtype:
+  if np_dtype.kind not in "biufc" and not is_custom_dtype and not dtype == float0:
     msg = f"JAX only supports number and bool dtypes, got dtype {dtype}"
     msg += f" in {fun_name}" if fun_name else ""
     raise TypeError(msg)

jax/_src/export/_export.py

@@ -1127,7 +1127,7 @@ def flattened_primal_fun_jax(*args_flat):
 
   vjp_in_avals = list(
       itertools.chain(in_avals,
-                      map(lambda a: a.at_least_vspace(), out_avals)))
+                      map(lambda a: a.to_tangent_aval(), out_avals)))
 
   if apply_jit:
     assert device_assignment is not None