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65 lines
2.4 KiB
Python
65 lines
2.4 KiB
Python
# Copyright (c) 2026, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Any
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import torch
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from nemo.utils import logging
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def patch_flashoptim_uneven_shard_support(optimizer) -> None:
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"""Patch flashoptim to handle FSDP2 unevenly-sharded parameters in DCP.
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FlashOptim <= 0.1.3 raises ``ValueError`` when saving optimizer state for
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parameters whose shard dimension is not evenly divisible by the FSDP mesh
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size. The root cause is that ``DTensor.from_local()`` is called without an
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explicit ``shape``, so it infers ``global = local * mesh_size`` which is
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wrong for padded (uneven) shards.
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This patch replaces ``_wrap_state_as_dtensor`` on the optimizer class so
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that ``shape=param.shape`` and ``stride=param.stride()`` are always passed,
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which is correct for both even and uneven shards.
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"""
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klass = type(optimizer)
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if not hasattr(klass, "_wrap_state_as_dtensor"):
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return
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if getattr(klass, "_nemo_patched_uneven_shard", False):
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return
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@staticmethod
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def _fixed_wrap_state_as_dtensor(state: dict[str, Any], param: torch.Tensor) -> None: # noqa: UP006
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if not hasattr(param, "device_mesh"):
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return
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from torch.distributed.tensor import DTensor
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mesh = param.device_mesh
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placements = param.placements
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for key, val in state.items():
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if isinstance(val, torch.Tensor) and not isinstance(val, DTensor) and val.dim() > 0:
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state[key] = DTensor.from_local(
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val,
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mesh,
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placements,
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shape=param.shape,
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stride=param.stride(),
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)
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klass._wrap_state_as_dtensor = _fixed_wrap_state_as_dtensor
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klass._nemo_patched_uneven_shard = True
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logging.info("Patched flashoptim %s to support unevenly-sharded FSDP2 parameters in DCP.", klass.__name__)
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