Merge pull request #8561 from mattjj:add-donated-invars-to-xlacomputa…

…tion

PiperOrigin-RevId: 410368194

jax/_src/api.py

@@ -488,17 +488,21 @@ class Lowered:
   querying properties of lowered computations across JAX's various
   lowering paths (``jit``, ``pmap``, etc.).
   """
-  __slots__ = ['in_tree', 'out_tree', '_lowering', '_no_kwargs']
+  __slots__ = ['in_tree', 'out_tree', 'donate_argnums', '_lowering',
+               '_no_kwargs']
 
   in_tree: PyTreeDef
   out_tree: PyTreeDef
+  donate_argnums: Tuple[int]
   _lowering: Union[xla.XlaComputation, pxla.MeshComputation]
   _no_kwargs: bool
 
-  def __init__(self, lowering, in_tree, out_tree, no_kwargs=False):
+  def __init__(self, lowering, in_tree, out_tree, donate_argnums,
+               no_kwargs=False):
     self._lowering = lowering
     self.in_tree = in_tree
     self.out_tree = out_tree
+    self.donate_argnums = donate_argnums
     self._no_kwargs = no_kwargs
 
   def _xla_computation(self):
@@ -508,7 +512,8 @@ def _xla_computation(self):
 
   def compile(self) -> 'Compiled':
     return Compiled(
-        self._lowering.compile(), self.in_tree, self.out_tree, self._no_kwargs)
+        self._lowering.compile(), self.in_tree, self.out_tree,
+        self.donate_argnums, self._no_kwargs)
 
 
 class Compiled:
@@ -519,17 +524,21 @@ class Compiled:
   common API for querying properties of compiled computations across
   JAX's various compilation paths and backends.
   """
-  __slots__ = ['in_tree', 'out_tree', '_executable', '_no_kwargs']
+  __slots__ = ['in_tree', 'out_tree', 'donate_argnums', '_executable',
+               '_no_kwargs']
 
   in_tree: PyTreeDef
   out_tree: PyTreeDef
+  donate_argnums: Tuple[int]
   _executable: Union[xla.XlaCompiledComputation, pxla.MeshExecutable]
   _no_kwargs: bool
 
-  def __init__(self, executable, in_tree, out_tree, no_kwargs=False):
+  def __init__(self, executable, in_tree, out_tree, donate_argnums,
+               no_kwargs=False):
     self._executable = executable
     self.in_tree = in_tree
     self.out_tree = out_tree
+    self.donate_argnums = donate_argnums
     self._no_kwargs = no_kwargs
 
   def _xla_executable(self):
@@ -589,7 +598,7 @@ def lower(*args, **kwargs) -> Lowered:
     arg_specs = unsafe_map(arg_spec, args_flat)
     computation = xla.lower_xla_callable(
         flat_fun, device, backend, name, donated_invars, *arg_specs)
-    return Lowered(computation, in_tree, out_tree())
+    return Lowered(computation, in_tree, out_tree(), donate_argnums)
 
   return lower
 

jax/experimental/pjit.py

@@ -229,23 +229,24 @@ def infer_params(*args, **kwargs):
         donated_invars=donated_invars,
         name=flat_fun.__name__,
         positional_semantics=maps._positional_semantics)
-    return args_flat, params, in_tree, out_tree()
+    return args_flat, params, in_tree, out_tree(), donate_argnums
 
   @wraps(fun)
   def wrapped(*args, **kwargs):
     for arg in tree_leaves(args):
       _check_arg(arg)
-    args_flat, params, _, out_tree = infer_params(*args, **kwargs)
+    args_flat, params, _, out_tree, _ = infer_params(*args, **kwargs)
     out = pjit_p.bind(*args_flat, **params)
     return tree_unflatten(out_tree, out)
 
   def lower(*args, **kwargs):
-    args_flat, params, in_tree, out_tree = infer_params(*args, **kwargs)
+    args_flat, params, in_tree, out_tree, donate_argnums = \
+        infer_params(*args, **kwargs)
     lowering = _pjit_lower(
         params['jaxpr'], params['in_axis_resources'],
         params['out_axis_resources'], params['resource_env'],
         params['donated_invars'], params['name'], maps._positional_semantics)
-    return Lowered(lowering, in_tree, out_tree, no_kwargs=True)
+    return Lowered(lowering, in_tree, out_tree, donate_argnums, no_kwargs=True)
 
   wrapped.lower = lower
   return wrapped

jax/interpreters/pxla.py

@@ -1723,15 +1723,16 @@ def lower_mesh_computation(
 
   built = c.Build(out_tuple)
   return MeshComputation(
-      built, mesh, local_in_untiled_avals,
+      built, donated_invars, mesh, local_in_untiled_avals,
       local_out_untiled_avals, (out_jaxpr_avals if spmd_lowering else None),
       in_axes, out_axes, spmd_lowering, tuple_args)
 
 
 class MeshComputation:
-  def __init__(self, hlo, *compile_args):
+  def __init__(self, hlo, donated_invars, *compile_args):
     self._executable = None
     self._hlo = hlo
+    self._donated_invars = donated_invars
     self.compile_args = compile_args
 
   def hlo(self):

jax/interpreters/xla.py

@@ -800,7 +800,7 @@ def lower_xla_callable(fun: lu.WrappedFun, device, backend, name,
   # and don't need to evaluate their arguments.
   if not jaxpr.eqns:
     return XlaComputation(
-        name, None, True, jaxpr, consts, device, abstract_args, out_avals,
+        name, None, True, None, jaxpr, consts, device, abstract_args, out_avals,
         kept_var_idx)
 
   if not _on_exit:
@@ -850,8 +850,8 @@ def lower_xla_callable(fun: lu.WrappedFun, device, backend, name,
          ", ".join(unused_donations)))
   built = c.build(output)
   return XlaComputation(
-      name, built, False, nreps, device, backend, tuple_args, abstract_args,
-      out_avals, kept_var_idx)
+      name, built, False, donated_invars, nreps, device, backend, tuple_args,
+      abstract_args, out_avals, kept_var_idx)
 
 
 def compile_or_get_cached(backend, computation, compile_options):
@@ -875,11 +875,14 @@ class XlaComputation:
   name: str
   _is_trivial: bool
   _executable: Optional['XlaCompiledComputation']
+  _donated_invars: Optional[Sequence[bool]]
 
-  def __init__(self, name: str, hlo, is_trivial: bool, *compile_args):
+  def __init__(self, name: str, hlo, is_trivial: bool,
+               donated_invars: Optional[Sequence[bool]], *compile_args):
     self.name = name
     self._hlo = hlo
     self._is_trivial = is_trivial
+    self._donated_invars = donated_invars
     self._executable = None
     self.compile_args = compile_args
 

tests/api_test.py

@@ -780,6 +780,14 @@ def f(*args):
     f_exe = self.jit(f).lower(1., 1.).compile()
     self.assertAllClose(f_exe(1., 1.), 1.)
 
+  def test_jit_lower_donate_argnums_available(self):
+    def f(*args):
+      x, *_ = args
+      return x
+    f_low = self.jit(f, donate_argnums=(0,)).lower(1., 1.)
+    f_com = f_low.compile()
+    f_low.donate_argnums == f_com.donate_argnums == (0,)
+
 
 class PythonJitTest(CPPJitTest):
 

tests/pjit_test.py

@@ -385,7 +385,19 @@ def _test_rule(*args, **kwargs):
   def testLowerWithDuckTyping(self):
     x = jax.ShapeDtypeStruct((2, 2), jnp.float32)
     # Make sure this doesn't crash
-    pjit(lambda x: x + 4, in_axis_resources=P('x'), out_axis_resources=P('x')).lower(x)
+    pjit(lambda x: x + 4,
+         in_axis_resources=P('x'), out_axis_resources=P('x')).lower(x)
+
+  @jtu.with_mesh([('x', 2)])
+  def testLowerDonateArgnumsAvailable(self):
+    x = jax.ShapeDtypeStruct((2, 2), jnp.float32)
+    def f(*args):
+      x, *_ = args
+      return x
+    f_low = pjit(f, donate_argnums=(0,),
+                 in_axis_resources=P('x'), out_axis_resources=P('x')).lower(x)
+    f_com = f_low.compile()
+    f_low.donate_argnums == f_com.donate_argnums == (0,)
 
   def testInfeed(self):
     devices = np.array(jax.local_devices())