Support axis_index inside shard_map(auto=...) by using iota and

then calling full_to_shard.

PiperOrigin-RevId: 705704369

jax/_src/lax/parallel.py

@@ -1591,7 +1591,25 @@ def _build_axis_index_lowering_hlo(ctx, axis_name, axis_env):
     axis_name, = axis_name
   if axis_name not in axis_env.names:
     raise NameError(f"unbound axis name: {axis_name}")
+  axis_context = ctx.module_context.axis_context
   axis_pos = list(axis_env.names).index(axis_name)
+
+  # For partial auto, lower using iota.
+  if (isinstance(axis_context, SPMDAxisContext) and
+      axis_context.manual_axes and
+      axis_context.manual_axes != frozenset(axis_context.mesh.axis_names)):
+    x = hlo.iota(ir.RankedTensorType.get(
+        [axis_env.sizes[axis_pos]], ir.IntegerType.get_signless(32)), mlir.i64_attr(0))
+    sharding_proto = (
+        NamedSharding(axis_context.mesh, P(axis_name))
+        ._to_xla_hlo_sharding(1).to_proto())
+    aval_in = ShapedArray((axis_env.sizes[axis_pos],), np.int32)
+    aval_out = ShapedArray((1,), np.int32)
+    sx = mlir.wrap_with_sharding_op(ctx, x, aval_in, sharding_proto)
+    proto = pxla.manual_proto(aval_in, axis_context.manual_axes, axis_context.mesh)
+    x = mlir.wrap_with_full_to_shard_op(ctx, sx, aval_out, proto)
+    return hlo.reshape(ir.RankedTensorType.get([], ir.IntegerType.get_signless(32)), x)
+
   nreplicas = axis_env.nreps // math.prod(axis_env.sizes)
   div = mlir.ir_constant(
       np.array(
@@ -1599,12 +1617,7 @@ def _build_axis_index_lowering_hlo(ctx, axis_name, axis_env):
       )
   )
   mod = mlir.ir_constant(np.array(axis_env.sizes[axis_pos], dtype=np.uint32))
-  axis_context = ctx.module_context.axis_context
-  is_spmd = isinstance(
-      axis_context,
-      (SPMDAxisContext, ShardingContext),
-  )
-  if is_spmd:
+  if isinstance(axis_context, (ShardingContext, SPMDAxisContext)):
     device_id = hlo.partition_id()
   else:
     device_id = hlo.replica_id()

tests/shard_map_test.py

@@ -2147,6 +2147,22 @@ class ShardMapTest(jtu.JaxTestCase):
 
     self.assertAllClose(jax.jit(f)(), jnp.zeros((2,)))
 
+  def test_partial_auto_axis_index(self):
+    if config.use_shardy_partitioner.value:
+      self.skipTest('Shardy does not support full-to-shard.')
+
+    mesh = jtu.create_mesh((4, 2), ('i', 'j'))
+    out_sharding = NamedSharding(mesh, P('i', None))
+
+    @partial(jax.jit, out_shardings=out_sharding)
+    def f():
+      return shard_map(lambda: jax.lax.axis_index('i').reshape(1,1),
+                       mesh, in_specs=P('i', None), out_specs=P('i', None),
+                       check_rep=False, auto=frozenset({'j'}))()
+
+    self.assertAllClose(f(), np.array(range(4), dtype=np.int32).reshape(-1, 1))
+
+
   def test_vmap_grad_shmap_spmd_axis_name_residuals(self):
     # https://github.com/jax-ml/jax/pull/21032
     mesh = jtu.create_mesh((4, 2), ('i', 'j'))