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Fix speech_paraformer issue with unexpected changes (#12416)

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* Fix speech_paraformer issue with unexpected changes

* Add paraformer version specified
This commit is contained in:
SONG Ge 2024-11-18 23:01:20 -08:00 committed by GitHub
parent a9cb70a71c
commit ff3f7cb25f
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GPG key ID: B5690EEEBB952194
3 changed files with 20 additions and 16 deletions
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4
python/llm/example/NPU/HF-Transformers-AutoModels/Multimodal/README.md
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@ -37,8 +37,8 @@ pip install timm torch==2.1.2 torchvision==0.16.2
pip install BCEmbedding==0.1.5 transformers==4.40.0
# [optional] for Speech_Paraformer-Large
pip install -U funasr
pip install modelscope torch==2.1.2 torchaudio==2.1.2
pip install funasr==1.1.14
pip install modelscope==1.20.1 torch==2.1.2 torchaudio==2.1.2
```
### 2. Runtime Configurations

2
python/llm/src/ipex_llm/transformers/npu_model.py
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@ -162,10 +162,12 @@ class _BaseAutoModelClass:
model = cls.HF_Model.from_pretrained(*args, **kwargs)
else:
model = cls.HF_Model(*args, **kwargs)
if hasattr(model, "config"):
model.config.update({"bigdl_lcmu_enabled": False})
logger.info(f"Converting model, it may takes up to several minutes ...")
if hasattr(model, "config"):
model.config.update({"optimize_model": optimize_model})
if mock_device == "cpu":

26
python/llm/src/ipex_llm/transformers/npu_models/paraformer_mp.py
View file

@ -294,17 +294,17 @@ class FusedLlamaLowBitDecoderlayer(torch.nn.Module):
torch.Tensor: result
"""
backend_cls = self.backend_cls_prefill
inputs = (x,
masks,
self.layer_norm_0_weight,
self.layer_norm_0_bias,
self.layer_norm_1_weight,
self.layer_norm_1_bias,
self.fsmn_weight,
self.qkv_bias,
self.out_bias,
self.w1_bias,
self.w2_bias,
inputs = (x.to(torch.float16),
masks.to(torch.float16),
self.layer_norm_0_weight.to(torch.float16),
self.layer_norm_0_bias.to(torch.float16),
self.layer_norm_1_weight.to(torch.float16),
self.layer_norm_1_bias.to(torch.float16),
self.fsmn_weight.to(torch.float16),
self.qkv_bias.to(torch.float16),
self.out_bias.to(torch.float16),
self.w1_bias.to(torch.float16),
self.w2_bias.to(torch.float16),
)
outputs = run_model(
@ -431,6 +431,8 @@ class PrefillRunner:
args = (xs_pad, masks)
self.prefill_input_queue.put(args)
xs_pad, masks = self.prefill_result_queue.get()
xs_pad = xs_pad.to(torch.float32)
masks = masks.to(torch.float32)
return xs_pad, masks
def shutdown(self):
@ -639,7 +641,7 @@ class FusedLlamaLowBitMultiDecoderlayer(torch.nn.Module):
):
super().__init__()
self.do_print = True
self.do_print = do_print
op_parameters = []
for w in parameters: