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# mypy: allow-untyped-defs
import warnings
from typing import Tuple, Union
from torch.distributed.device_mesh import _mesh_resources
from torch.distributed.tensor import DeviceMesh
from torch.distributed.tensor.placement_types import Placement
try:
from torch._dynamo.external_utils import is_compiling as is_torchdynamo_compiling
except Exception:
def is_torchdynamo_compiling(): # type: ignore[misc]
return False
LayoutsType = Union[Placement, Tuple[Placement, ...]]
def _deprecate_warnings(func_name: str, extra_msg: str) -> None:
"""
Inject common validation logics for `_prepare_input` funcs via this decorator.
Include verifying that input needs to be either a :class:`Tensor` or :class:`DTensor`
and only 1D :class:`DeviceMesh` is passed in.
"""
# TODO: Will follow up with dynamo POC to make warnings.warn working with dynamo.
if not is_torchdynamo_compiling():
warnings.warn(
f"{func_name} is deprecated and will be removed soon. {extra_msg}",
FutureWarning,
stacklevel=3,
)
def _validate_tp_mesh_dim(
device_mesh: DeviceMesh,
) -> None:
"""
Check whether TP mesh dimension is valid or not.
Args:
device_mesh (:class:`DeviceMesh`):
The `device_mesh` where we perform
Tensor Parallelism on.
Return:
`True` if the mesh dimension
is valid, `False` otherwise.
"""
if device_mesh.ndim > 1:
raise ValueError(
f"Tensor Parallel only accepts a 1D DeviceMesh, but found {device_mesh.ndim}D!"
'If you have a 2-D or N-D device_mesh, consider passing in device_mesh["tp"]'
)
root_mesh = _mesh_resources.get_root_mesh(device_mesh)
# if a root mesh is not the same as device_mesh,
# meaning the device_mesh is sliced out from the root mesh.
if root_mesh and root_mesh != device_mesh:
tp_mesh_dim_in_root = _mesh_resources.get_root_mesh_dim(device_mesh)
if tp_mesh_dim_in_root != root_mesh.ndim - 1:
raise RuntimeError(
f"Found TP device_mesh on the {tp_mesh_dim_in_root} dimension of its parent mesh.",
"Currently we only support intranode TP and TP needs to be the innermost dimension on its parent mesh.",
)
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