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fsdp: materialize clip_grad_norm's DTensor before logging #35

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Merged
zhihengy merged 1 commit into from
Jul 13, 2026
Merged

fsdp: materialize clip_grad_norm's DTensor before logging #35

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5 changes: 5 additions & 0 deletions miles/backends/fsdp_utils/actor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import ray
import torch
import torch.distributed as dist
from torch.distributed.tensor import DTensor

import miles.backends.fsdp_utils.configs.qwen_image # noqa: F401 — register pipeline config
import miles.backends.fsdp_utils.configs.sd3 # noqa: F401 — register pipeline config
Expand Down Expand Up @@ -407,6 +408,10 @@ def _train_core(self, rollout_id: int, rollout_data) -> None:
if not self.args.debug_skip_optimizer_step:
self.scaler.unscale_(self.optimizer)
grad_norm = torch.nn.utils.clip_grad_norm_(self.model.parameters(), self.args.clip_grad)
if isinstance(grad_norm, DTensor):
# clip returns a lazily-reduced partial norm; materialize it,
# otherwise the logged metric leaks the local shard's value.
grad_norm = grad_norm.full_tensor()
log_stats["grad_norm"].append(grad_norm.detach())
self.scaler.step(self.optimizer)
self.scaler.update()
Expand Down
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