[monarch] refactor monarch/ callsites to use monarch.actor

examples/grpo_actor.py

@@ -13,9 +13,8 @@
 import torch
 import torch.nn as nn
 import torch.optim as optim
-from monarch.actor_mesh import Actor, ActorMeshRef, endpoint
 
-from monarch.proc_mesh import proc_mesh
+from monarch.actor import Actor, ActorMeshRef, endpoint, proc_mesh
 from monarch.rdma import RDMABuffer
 from torch.distributions import Categorical, kl_divergence
 

examples/notebooks/ping_pong.ipynb

@@ -16,7 +16,7 @@
             "metadata": {},
             "source": [
                 "## Hello World\n",
-                "Actors are spawned in Process meshes via the `monarch.proc_mesh` API. For those familiar with distributed systems, it can be helpful to think of each Actor as a server with endpoints that can be called."
+                "Actors are spawned in Process meshes via the `monarch.actor` API. For those familiar with distributed systems, it can be helpful to think of each Actor as a server with endpoints that can be called."
             ]
         },
         {
@@ -43,8 +43,8 @@
             "source": [
                 "import asyncio\n",
                 "\n",
-                "from monarch.proc_mesh import proc_mesh, ProcMesh\n",
-                "from monarch.actor_mesh import Actor, endpoint, current_rank\n",
+                "from monarch.actor import proc_mesh, ProcMesh\n",
+                "from monarch.actor import Actor, endpoint, current_rank\n",
                 "\n",
                 "NUM_ACTORS=4\n",
                 "\n",
@@ -168,8 +168,8 @@
             "source": [
                 "import asyncio\n",
                 "\n",
-                "from monarch.proc_mesh import proc_mesh, ProcMesh\n",
-                "from monarch.actor_mesh import Actor, endpoint, current_rank\n",
+                "from monarch.actor import proc_mesh, ProcMesh\n",
+                "from monarch.actor import Actor, endpoint, current_rank\n",
                 "\n",
                 "class ExampleActor(Actor):\n",
                 "    def __init__(self, actor_name):\n",

examples/notebooks/spmd_ddp.ipynb

@@ -24,8 +24,8 @@
                 "import torch.nn as nn\n",
                 "import torch.optim as optim\n",
                 "\n",
-                "from monarch.proc_mesh import proc_mesh\n",
-                "from monarch.actor_mesh import Actor, current_rank, endpoint\n",
+                "from monarch.actor import proc_mesh\n",
+                "from monarch.actor import Actor, current_rank, endpoint\n",
                 "\n",
                 "from torch.nn.parallel import DistributedDataParallel as DDP\n",
                 "\n",

python/monarch/_src/actor/proc_mesh.py

@@ -22,8 +22,6 @@
     TypeVar,
 )
 
-from monarch._rust_bindings import has_tensor_engine
-
 from monarch._rust_bindings.hyperactor_extension.alloc import (  # @manual=//monarch/monarch_extension:monarch_extension  # @manual=//monarch/monarch_extension:monarch_extension
     Alloc,
     AllocConstraints,
@@ -44,11 +42,21 @@
 from monarch._src.actor.future import Future
 from monarch._src.actor.shape import MeshTrait
 
+HAS_TENSOR_ENGINE = False
+try:
+    # TODO: while the tensor_engine submodule doesn't exist yet, use the
+    # available of monarch.rdma as a proxy.
+    # type: ignore
+    from monarch.rdma import RDMAManager  # @manual
+
+    HAS_TENSOR_ENGINE = True
+except ImportError:
+    pass
+
 
 if TYPE_CHECKING:
     Tensor = Any
     DeviceMesh = Any
-    RDMAManager = Any
 
 
 T = TypeVar("T")
@@ -84,10 +92,7 @@ def __init__(
         self._auto_reload_actor: Optional[AutoReloadActor] = None
         self._maybe_device_mesh: Optional["DeviceMesh"] = _device_mesh
         self._stopped = False
-        if _mock_shape is None and has_tensor_engine():
-            # type: ignore[21]
-            from monarch.rdma import RDMAManager  # @manual
-
+        if _mock_shape is None and HAS_TENSOR_ENGINE:
             # type: ignore[21]
             self._rdma_manager = self._spawn_blocking("rdma_manager", RDMAManager)
 
@@ -192,7 +197,7 @@ async def _spawn_nonblocking(
 
     @property
     def _device_mesh(self) -> "DeviceMesh":
-        if not has_tensor_engine():
+        if not HAS_TENSOR_ENGINE:
             raise RuntimeError(
                 "DeviceMesh is not available because tensor_engine was not compiled (USE_TENSOR_ENGINE=0)"
             )
@@ -308,7 +313,7 @@ def local_proc_mesh(*, gpus: Optional[int] = None, hosts: int = 1) -> Future[Pro
     )
 
 
-_BOOTSTRAP_MAIN = "monarch.bootstrap_main"
+_BOOTSTRAP_MAIN = "monarch._src.actor.bootstrap_main"
 
 
 def _get_bootstrap_args() -> tuple[str, Optional[list[str]], dict[str, str]]:

python/monarch/_testing.py

@@ -14,12 +14,12 @@
 
 import monarch_supervisor
 from monarch._src.actor.shape import NDSlice
+from monarch.actor import proc_mesh, ProcMesh
 from monarch.common.client import Client
 from monarch.common.device_mesh import DeviceMesh
 from monarch.common.invocation import DeviceException, RemoteException
 from monarch.controller.backend import ProcessBackend
 from monarch.mesh_controller import spawn_tensor_engine
-from monarch.proc_mesh import proc_mesh, ProcMesh
 from monarch.python_local_mesh import PythonLocalContext
 from monarch.rust_local_mesh import (
     local_mesh,

python/monarch/actor/__init__.py

@@ -12,27 +12,34 @@
     Accumulator,
     Actor,
     ActorError,
+    ActorMeshRef,
     current_actor_name,
     current_rank,
     current_size,
     endpoint,
     MonarchContext,
+    Point,
+    send,
     ValueMesh,
 )
 from monarch._src.actor.future import Future
-from monarch._src.actor.proc_mesh import proc_mesh, ProcMesh
+from monarch._src.actor.proc_mesh import local_proc_mesh, proc_mesh, ProcMesh
 
 __all__ = [
     "Accumulator",
     "Actor",
     "ActorError",
+    "ActorMeshRef",
     "current_actor_name",
     "current_rank",
     "current_size",
     "endpoint",
+    "Future",
+    "local_proc_mesh",
     "MonarchContext",
-    "ValueMesh",
+    "Point",
     "proc_mesh",
     "ProcMesh",
-    "Future",
+    "send",
+    "ValueMesh",
 ]

python/monarch/mesh_controller.py

@@ -34,8 +34,8 @@
 from monarch._rust_bindings.monarch_hyperactor.proc import (  # @manual=//monarch/monarch_extension:monarch_extension
     ActorId,
 )
+from monarch._src.actor.actor_mesh import Port, PortTuple
 from monarch._src.actor.shape import NDSlice
-from monarch.actor_mesh import Port, PortTuple
 from monarch.common import messages
 from monarch.common.controller_api import TController
 from monarch.common.invocation import Seq

python/tests/error_test_binary.py

@@ -13,8 +13,7 @@
 
 from monarch._rust_bindings.monarch_extension.panic import panicking_function
 
-from monarch.actor_mesh import Actor, endpoint, send
-from monarch.proc_mesh import proc_mesh
+from monarch.actor import Actor, endpoint, proc_mesh, send
 
 
 class ErrorActor(Actor):

python/tests/test_actor_error.py

@@ -10,8 +10,7 @@
 
 import pytest
 from monarch._rust_bindings.monarch_hyperactor.proc_mesh import ProcEvent
-from monarch.actor_mesh import Actor, ActorError, endpoint, send
-from monarch.proc_mesh import local_proc_mesh, proc_mesh
+from monarch.actor import Actor, ActorError, endpoint, local_proc_mesh, proc_mesh
 
 
 class ExceptionActor(Actor):

python/tests/test_allocator.py

@@ -38,8 +38,14 @@
     StaticRemoteAllocInitializer,
     TorchXRemoteAllocInitializer,
 )
-from monarch.actor_mesh import Actor, current_rank, current_size, endpoint, ValueMesh
-from monarch.proc_mesh import ProcMesh
+from monarch.actor import (
+    Actor,
+    current_rank,
+    current_size,
+    endpoint,
+    ProcMesh,
+    ValueMesh,
+)
 from monarch.tools.mesh_spec import MeshSpec, ServerSpec
 from monarch.tools.network import get_sockaddr
 

python/tests/test_python_actors.py

@@ -12,8 +12,6 @@
 from types import ModuleType
 from unittest.mock import AsyncMock, patch
 
-import monarch
-
 import pytest
 
 import torch
@@ -23,6 +21,7 @@
 from monarch.actor import (
     Accumulator,
     Actor,
+    ActorError,
     current_actor_name,
     current_rank,
     current_size,
@@ -545,7 +544,7 @@ def _patch_output(msg):
         breakpoints = await debug_client.list.call_one()
         assert len(breakpoints) == 0
 
-        with pytest.raises(monarch.actor.ActorError, match="ValueError: bad rank"):
+        with pytest.raises(ActorError, match="ValueError: bad rank"):
             await fut
 
 

python/tests/test_tensor_engine.py

@@ -8,8 +8,8 @@
 import pytest
 import torch
 from monarch import remote
+from monarch.actor import proc_mesh
 from monarch.mesh_controller import spawn_tensor_engine
-from monarch.proc_mesh import proc_mesh
 
 
 two_gpu = pytest.mark.skipif(

setup.py

@@ -166,7 +166,7 @@ def run(self):
     entry_points={
         "console_scripts": [
             "monarch=monarch.tools.cli:main",
-            "monarch_bootstrap=monarch.bootstrap_main:invoke_main",
+            "monarch_bootstrap=monarch._src.actor.bootstrap_main:invoke_main",
         ],
     },
     rust_extensions=rust_extensions,