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Update train_ep.py
Force all2all backward the same number of times
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@ -110,6 +110,14 @@ def main():
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if type(layer.mlp).__name__ != "DeepseekV2MoE":
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continue
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layer.mlp.ep_group = ep_group
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# Force all2all backward the same number of times
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if ep_size > 1 and not expert_config["non_expert_modules"]:
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min_layer_id = min(int(k) for k, v in expert_config["experts"].items() if v)
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mlp = model.model.layers[min_layer_id].mlp
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forward = mlp.forward
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def custom_forward(self, hidden_states: torch.Tensor):
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return forward(hidden_states.requires_grad_(torch.is_grad_enabled()))
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mlp.forward = MethodType(custom_forward, mlp)
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# Initialize Trainer
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trainer = Trainer(
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