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[Model] Add has_weight to RMSNorm and re-enable weights loading tracker for Mamba (#10739)

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Signed-off-by: Isotr0py <2037008807@qq.com>
This commit is contained in:
Isotr0py
2024-12-10 10:23:07 +08:00
committed by GitHub
parent 6d525288c1
commit d1f6d1c8af
3 changed files with 32 additions and 10 deletions
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9
vllm/model_executor/models/mamba.py
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@@ -1,5 +1,5 @@
"""PyTorch MAMBA model."""
from typing import Iterable, List, Optional, Tuple
from typing import Iterable, List, Optional, Set, Tuple
import torch
from torch import nn
@@ -47,6 +47,7 @@ class MambaDecoderLayer(nn.Module):
use_conv_bias=config.use_conv_bias,
use_bias=config.use_bias,
use_rms_norm=self.is_falcon_mamba,
rms_norm_has_weight=not self.is_falcon_mamba,
rms_norm_eps=mixer_rms_eps,
activation=config.hidden_act)
@@ -241,8 +242,10 @@ class MambaForCausalLM(nn.Module, HasInnerState, IsAttentionFree):
next_tokens = self.sampler(logits, sampling_metadata)
return next_tokens
def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
def load_weights(self, weights: Iterable[Tuple[str,
torch.Tensor]]) -> Set[str]:
params_dict = dict(self.named_parameters())
loaded_params: Set[str] = set()
for name, loaded_weight in weights:
if "A_log" in name:
name = name.replace("A_log", "A")
@@ -254,3 +257,5 @@ class MambaForCausalLM(nn.Module, HasInnerState, IsAttentionFree):
weight_loader = getattr(param, "weight_loader",
default_weight_loader)
weight_loader(param, loaded_weight)
loaded_params.add(name)
return loaded_params