[Misc] Add uninitialized params tracking for AutoWeightsLoader (#10327)

Signed-off-by: Isotr0py <2037008807@qq.com>
This commit is contained in:
Isotr0py
2024-11-18 09:07:46 +08:00
committed by GitHub
parent d1557e66d3
commit c4e464333e
74 changed files with 454 additions and 185 deletions

View File

@@ -18,7 +18,7 @@
# limitations under the License.
"""Inference-only BaiChuan model compatible with HuggingFace weights."""
import math
from typing import Iterable, List, Optional, Tuple, Union
from typing import Iterable, List, Optional, Set, Tuple, Union
import torch
from torch import nn
@@ -404,13 +404,15 @@ class BaiChuanBaseForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
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]:
stacked_params_mapping = [
# (param_name, shard_name, shard_id)
("gate_up_proj", "gate_proj", 0),
("gate_up_proj", "up_proj", 1),
]
params_dict = dict(self.named_parameters())
loaded_params: Set[str] = set()
for name, loaded_weight in weights:
if "rotary_emb.inv_freq" in name:
continue
@@ -449,6 +451,8 @@ class BaiChuanBaseForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
weight_loader = getattr(param, "weight_loader",
default_weight_loader)
weight_loader(param, loaded_weight)
loaded_params.add(name)
return loaded_params
class BaichuanForCausalLM(BaiChuanBaseForCausalLM):