fix convert_element_type on large Py int inputs

jax/_src/lax/lax.py

@@ -2658,6 +2658,12 @@ def _minmax_translation_rule(c, x, y, *, minmax=None, cmp=None):
 ad.defjvp_zero(lt_p)
 
 
+def _convert_element_type_impl(operand, *, new_dtype, weak_type):
+ if dtypes.is_python_scalar(operand):
+ operand = np.asarray(operand, dtype=new_dtype)
+ return xla.apply_primitive(convert_element_type_p, operand,
+ new_dtype=new_dtype, weak_type=weak_type)
+
 def _convert_element_type_shape_rule(operand, *, new_dtype, weak_type):
  return operand.shape
 
@@ -2693,7 +2699,7 @@ def _convert_element_type_jvp_rule(tangent, operand , *, new_dtype, weak_type):
  return convert_element_type_p.bind(tangent, new_dtype=new_dtype, weak_type=weak_type)
 
 convert_element_type_p = core.convert_element_type_p
-convert_element_type_p.def_impl(partial(xla.apply_primitive, convert_element_type_p))
+convert_element_type_p.def_impl(_convert_element_type_impl)
 convert_element_type_p.def_abstract_eval(
  partial(standard_abstract_eval, convert_element_type_p,
  _convert_element_type_shape_rule, _convert_element_type_dtype_rule,

jax/experimental/host_callback.py

@@ -934,6 +934,7 @@ def _outside_call_jvp_rule(primals, tangents, **params):
  if not params["identity"]:
  raise NotImplementedError("JVP rule is implemented only for id_tap, not for call.")
  tangent_instantiated = tuple(map(_instantiate_zeros, primals, tangents))
+ tangent_instantiated = tuple(map(ad.replace_float0s, primals, tangent_instantiated))
 
  arg_treedef = params["arg_treedef"]
  # The argument to the jvp tap is a pair of the tapped primals and tangents
@@ -946,6 +947,7 @@ def _outside_call_jvp_rule(primals, tangents, **params):
  arg_treedef=jvp_arg_treedef,
  ))
  out_primals_tapped, out_tangents_tapped = util.split_list(out_all, [len(primals)])
+ out_tangents_tapped = map(ad.recast_to_float0, out_primals_tapped, out_tangents_tapped)
  return tuple(out_primals_tapped), tuple(out_tangents_tapped)
 
 

tests/host_callback_test.py

@@ -1028,7 +1028,7 @@ def func(x, yint):
  2 )
  transforms: ['jvp', 'transpose'] what: pair
  ( 2.00
- False )""", testing_stream.output)
+ 0 )""", testing_stream.output)
  testing_stream.reset()
 
  def test_tap_vmap(self):
@@ -1590,8 +1590,8 @@ def padded_sum(x):
  ( 3 ) ) )
  ( ( [0. 0.1 0.2 0.3 0.4]
  [0. 0.2 0.4 0.6 0.8] )
- ( ( False )
- ( False ) ) ) )""", testing_stream.output)
+ ( ( 0 )
+ ( 0 ) ) ) )""", testing_stream.output)
  testing_stream.reset()
 
  # Now with JIT

tests/random_test.py

@@ -746,6 +746,8 @@ def f(x):
  grad(lambda x: jnp.sum(vmap(f)(x)))(jnp.ones(2))
 
  def testNoOpByOpUnderHash(self):
+ if not config.omnistaging_enabled:
+ raise SkipTest("test requires omnistaging")
  def fail(*args, **kwargs): assert False
  apply_primitive, xla.apply_primitive = xla.apply_primitive, fail
  try: