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Key the tied-embedding TP rule on the model's input embedding attribute #48779

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Key the tied-embedding TP rule on the model's input embedding attribute #48779

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1043552
Key the tied-embedding TP rule on the model's input embedding attribute
Siddhant231xyz Sep 13, 2026
ca3ede7
Merge branch 'main' into tp-tied-embed-layer
3outeille Sep 17, 2026
4c1b12a
Merge branch 'main' into tp-tied-embed-layer
3outeille Sep 17, 2026
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7 changes: 0 additions & 7 deletions src/transformers/configuration_utils.py
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Expand Up @@ -352,13 +352,6 @@ def __post_init__(self, **kwargs):
if per_layer_config is not None:
self.per_layer_config = per_layer_config

# TODO: to support models whose input embedding module is not named `embed_tokens` (e.g. GPT-NeoX's `embed_in`).
if getattr(self, "tie_word_embeddings", False) and self.base_model_tp_plan is not None:
self.base_model_tp_plan = {
**self.base_model_tp_plan,
"embed_tokens": "embedding_rowwise",
}

def __init_subclass__(cls, *args, **kwargs):
super().__init_subclass__(*args, **kwargs)
cls_has_custom_init = "__init__" in cls.__dict__
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5 changes: 4 additions & 1 deletion src/transformers/distributed/mixin.py
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Expand Up @@ -66,7 +66,10 @@ def init_parallel_plans(self) -> None:

if self.base_model is self:
self._pp_plan.update(self.config.base_model_pp_plan or {})
self._tp_plan.update(self.config.base_model_tp_plan or {})
tp_plan = dict(self.config.base_model_tp_plan or {})
if tp_plan and getattr(self.config, "tie_word_embeddings", False):
tp_plan.setdefault(getattr(self, "_input_embed_layer", "embed_tokens"), "embedding_rowwise")
self._tp_plan.update(tp_plan)
self._ep_plan.update(self.config.base_model_ep_plan or {})
self._fsdp_plan.update(self.config.base_model_fsdp_plan or {})

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