speech_recognition/FunASR
1
0
Fork 0
mirror of https://github.com/modelscope/FunASR synced 2025-09-15 14:48:36 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Dev gzf (#1469)

Browse Source 
* qwenaudio qwenaudiochat

* qwenaudio qwenaudiochat

* whisper

* whisper

* llm

* llm

* llm

* llm

* llm

* llm

* llm

* llm

* export onnx

* export onnx

* export onnx

* dingding

* dingding

* llm

* doc

* onnx

* onnx

* onnx
This commit is contained in:
zhifu gao 2024-03-11 19:37:50 +08:00 committed by GitHub
parent e847f85a14
commit cc59310dbf
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
7 changed files with 7 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
funasr/auto/auto_model.py
View File

@ -158,7 +158,6 @@ class AutoModel:
torch.set_num_threads(kwargs.get("ncpu", 4))
# build tokenizer
tokenizer = kwargs.get("tokenizer", None)
if tokenizer is not None:

2
funasr/models/bicif_paraformer/model.py
View File

@ -367,7 +367,7 @@ class BiCifParaformer(Paraformer):
else:
self.make_pad_mask = sequence_mask(max_seq_len, flip=False)
self.forward = self._export_forward
self.forward = self.export_forward
return self

2
funasr/models/ct_transformer/model.py
View File

@ -373,7 +373,7 @@ class CTTransformer(torch.nn.Module):
encoder_class = tables.encoder_classes.get(kwargs["encoder"]+"Export")
self.encoder = encoder_class(self.encoder, onnx=is_onnx)
self.forward = self._export_forward
self.forward = self.export_forward
return self

2
funasr/models/ct_transformer_streaming/model.py
View File

@ -182,7 +182,7 @@ class CTTransformerStreaming(CTTransformer):
encoder_class = tables.encoder_classes.get(kwargs["encoder"] + "Export")
self.encoder = encoder_class(self.encoder, onnx=is_onnx)
self.forward = self._export_forward
self.forward = self.export_forward
return self

2
funasr/models/fsmn_vad_streaming/model.py
View File

@ -647,7 +647,7 @@ class FsmnVADStreaming(nn.Module):
is_onnx = kwargs.get("type", "onnx") == "onnx"
encoder_class = tables.encoder_classes.get(kwargs["encoder"] + "Export")
self.encoder = encoder_class(self.encoder, onnx=is_onnx)
self.forward = self._export_forward
self.forward = self.export_forward
return self

2
funasr/models/paraformer/model.py
View File

@ -575,7 +575,7 @@ class Paraformer(torch.nn.Module):
else:
self.make_pad_mask = sequence_mask(max_seq_len, flip=False)
self.forward = self._export_forward
self.forward = self.export_forward
return self

5
funasr/models/paraformer_streaming/model.py
View File

@ -587,7 +587,6 @@ class ParaformerStreaming(Paraformer):
else:
self.make_pad_mask = sequence_mask(max_seq_len, flip=False)
self.forward = self._export_forward
import copy
import types
@ -595,7 +594,7 @@ class ParaformerStreaming(Paraformer):
decoder_model = copy.copy(self)
# encoder
encoder_model.forward = types.MethodType(ParaformerStreaming._export_encoder_forward, encoder_model)
encoder_model.forward = types.MethodType(ParaformerStreaming.export_encoder_forward, encoder_model)
encoder_model.export_dummy_inputs = types.MethodType(ParaformerStreaming.export_encoder_dummy_inputs, encoder_model)
encoder_model.export_input_names = types.MethodType(ParaformerStreaming.export_encoder_input_names, encoder_model)
encoder_model.export_output_names = types.MethodType(ParaformerStreaming.export_encoder_output_names, encoder_model)
@ -603,7 +602,7 @@ class ParaformerStreaming(Paraformer):
encoder_model.export_name = types.MethodType(ParaformerStreaming.export_encoder_name, encoder_model)
# decoder
decoder_model.forward = types.MethodType(ParaformerStreaming._export_decoder_forward, decoder_model)
decoder_model.forward = types.MethodType(ParaformerStreaming.export_decoder_forward, decoder_model)
decoder_model.export_dummy_inputs = types.MethodType(ParaformerStreaming.export_decoder_dummy_inputs, decoder_model)
decoder_model.export_input_names = types.MethodType(ParaformerStreaming.export_decoder_input_names, decoder_model)
decoder_model.export_output_names = types.MethodType(ParaformerStreaming.export_decoder_output_names, decoder_model)