[dev] feat(moe): Support apply wd to qk layernorm for Qwen3-Next #2825
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Jan 6, 2026
megatron/core/ssm/gated_delta_net.py
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| ).uniform_(*self.A_init_range) | ||
| self.A_log.data.copy_(A) | ||
| A_log = torch.log(A) | ||
| self.A_log.data.copy_(A_log) |
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self.A_log.data.copy_(torch.log(A)) would be preferred if A_log will not be used somewhere else.
tests/unit_tests/test_optimizer.py
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| # k_layernorm.bias, linear.weight = 5 params | ||
| # wd_mult=0.0: regular_layernorm.weight, linear.bias = 2 params | ||
| assert wd_mult_1_count == 5, f"Expected 5 params with wd_mult=1.0, but got {wd_mult_1_count}" | ||
| assert wd_mult_0_count == 2, f"Expected 3 params with wd_mult=0.0, but got {wd_mult_0_count}" |
| weight_decay: float = 0.01 | ||
| """Weight decay coefficient for L2 regularization.""" | ||
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| no_weight_decay_cond: Optional[str] = None |
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The argument is no_weight_decay_cond_type. We should make it consistent.
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/ok to test 1a51783 |
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/ok to test 716e797 |
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/ok to test b2dfb88 |
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