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export

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游雁 2023-03-28 20:08:09 +08:00
parent c776f8afc0
commit 8a788ad0d9
3 changed files with 9 additions and 9 deletions
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1
funasr/export/export_model.py
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@ -193,6 +193,7 @@ class ModelExport:
model, vad_infer_args = VADTask.build_model_from_file( model, vad_infer_args = VADTask.build_model_from_file(
config, model_file, 'cpu' config, model_file, 'cpu'
) )
self.export_config["feats_dim"] = 400
self._export(model, tag_name) self._export(model, tag_name)

4
funasr/export/models/e2e_vad.py
View File

@ -11,7 +11,7 @@ from funasr.export.models.encoder.fsmn_encoder import FSMN as FSMN_export
class E2EVadModel(nn.Module): class E2EVadModel(nn.Module):
def __init__(self, model, def __init__(self, model,
max_seq_len=512, max_seq_len=512,
feats_dim=560, feats_dim=400,
model_name='model', model_name='model',
**kwargs,): **kwargs,):
super(E2EVadModel, self).__init__() super(E2EVadModel, self).__init__()
@ -31,7 +31,7 @@ class E2EVadModel(nn.Module):
in_cache3: torch.Tensor, in_cache3: torch.Tensor,
): ):
scores, cache0, cache1, cache2, cache3 = self.encoder(feats, scores, (cache0, cache1, cache2, cache3) = self.encoder(feats,
in_cache0, in_cache0,
in_cache1, in_cache1,
in_cache2, in_cache2,

13
funasr/export/models/encoder/fsmn_encoder.py
View File

@ -149,8 +149,7 @@ fsmn_layers: no. of sequential fsmn layers
class FSMN(nn.Module): class FSMN(nn.Module):
def __init__( def __init__(
self, self, model,
model,
): ):
super(FSMN, self).__init__() super(FSMN, self).__init__()
@ -177,10 +176,10 @@ class FSMN(nn.Module):
self.out_linear1 = model.out_linear1 self.out_linear1 = model.out_linear1
self.out_linear2 = model.out_linear2 self.out_linear2 = model.out_linear2
self.softmax = model.softmax self.softmax = model.softmax
self.fsmn = model.fsmn
for i, d in enumerate(self.model.fsmn): for i, d in enumerate(model.fsmn):
if isinstance(d, BasicBlock): if isinstance(d, BasicBlock):
self.model.fsmn[i] = BasicBlock_export(d) self.fsmn[i] = BasicBlock_export(d)
def fuse_modules(self): def fuse_modules(self):
pass pass
@ -202,7 +201,7 @@ class FSMN(nn.Module):
x = self.relu(x) x = self.relu(x)
# x4 = self.fsmn(x3, in_cache) # self.in_cache will update automatically in self.fsmn # x4 = self.fsmn(x3, in_cache) # self.in_cache will update automatically in self.fsmn
out_caches = list() out_caches = list()
for i, d in enumerate(self.model.fsmn): for i, d in enumerate(self.fsmn):
in_cache = args[i] in_cache = args[i]
x, out_cache = d(x, in_cache) x, out_cache = d(x, in_cache)
out_caches.append(out_cache) out_caches.append(out_cache)
@ -210,7 +209,7 @@ class FSMN(nn.Module):
x = self.out_linear2(x) x = self.out_linear2(x)
x = self.softmax(x) x = self.softmax(x)
return x, *out_caches return x, out_caches
''' '''