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[bugfix] support MTP-only pipeline stages #155

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[bugfix] support MTP-only pipeline stages #155

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8003b9c
fix MTP-only pipeline stage specs
taking-lying-flat Jul 31, 2026
7a27197
align Qwen3.5 MTP layer spec
Aug 5, 2026
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27 changes: 22 additions & 5 deletions src/mcore_bridge/model/gpts/qwen3_next_gdn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,11 +115,8 @@ def _set_linear_decoupled_in_proj(self, mg_attn, hf_state_dict, to_mcore: bool):
class Qwen3NextLoader(ModelLoader):
gated_delta_net = GatedDeltaNet

def get_transformer_layer_spec(self, vp_stage: Optional[int] = None):
from megatron.core.models.gpt.experimental_attention_variant_module_specs import \
get_transformer_block_with_experimental_attention_variant_spec
layer_specs = get_transformer_block_with_experimental_attention_variant_spec(self.config, vp_stage)
for layer_spec in layer_specs.layer_specs:
def _replace_transformer_layer_specs(self, layer_specs):
for layer_spec in layer_specs:
attn_module = layer_spec.submodules.self_attention.module
if issubclass(attn_module, SelfAttention):
layer_spec.submodules.self_attention.module = GatedSelfAttention
Expand All @@ -128,8 +125,28 @@ def get_transformer_layer_spec(self, vp_stage: Optional[int] = None):
if self.config.linear_decoupled_in_proj:
layer_spec.submodules.input_layernorm = TENorm
layer_spec.submodules.self_attention.submodules.in_proj = TEColumnParallelLinear

def get_transformer_layer_spec(self, vp_stage: Optional[int] = None):
from megatron.core.models.gpt.experimental_attention_variant_module_specs import \
get_transformer_block_with_experimental_attention_variant_spec
layer_specs = get_transformer_block_with_experimental_attention_variant_spec(self.config, vp_stage)
self._replace_transformer_layer_specs(layer_specs.layer_specs)
return layer_specs

def get_mtp_block_spec(self, transformer_layer_spec, vp_stage: Optional[int] = None):
from megatron.core.models.gpt.experimental_attention_variant_module_specs import \
get_transformer_layer_with_experimental_attention_variant_spec
decoder_layer_specs = get_transformer_layer_with_experimental_attention_variant_spec(self.config)
self._replace_transformer_layer_specs(decoder_layer_specs)

transformer_layer_spec = copy.deepcopy(transformer_layer_spec)
transformer_layer_spec.layer_specs = [decoder_layer_specs[-1]]
self._set_shared_expert_gate(transformer_layer_spec)
self._set_transformer_layer(transformer_layer_spec)
self._replace_mla_attention(transformer_layer_spec)
self._replace_router(transformer_layer_spec)
return super().get_mtp_block_spec(transformer_layer_spec, vp_stage=vp_stage)

def build_model(
self,
pre_process=True,
Expand Down