Commit
•
b96cf19
1
Parent(s):
d8ebfde
root analysis improved
Browse files
README.md
CHANGED
@@ -32,16 +32,16 @@ class UDgoeswith(object):
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import numpy,torch,ufal.chu_liu_edmonds
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w=self.tokenizer(text,return_offsets_mapping=True)
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v=w["input_ids"]
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-
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with torch.no_grad():
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e[
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m=numpy.full((
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m[1:,1:]=numpy.nanmax(e,axis=2).transpose()
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p=numpy.zeros(
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p[1:,1:]=numpy.nanargmax(e,axis=2).transpose()
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for i in range(1,
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m[i,0],m[i,i],p[i,0]=m[i,i],numpy.nan,p[i,i]
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h=ufal.chu_liu_edmonds.chu_liu_edmonds(m)[0]
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u="# text = "+text+"\n"
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import numpy,torch,ufal.chu_liu_edmonds
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w=self.tokenizer(text,return_offsets_mapping=True)
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v=w["input_ids"]
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x=[v[0:i]+[self.tokenizer.mask_token_id]+v[i+1:]+[j] for i,j in enumerate(v[1:-1],1)]
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with torch.no_grad():
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e=self.model(input_ids=torch.tensor(x)).logits.numpy()[:,1:-2,:]
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r=[1 if i==0 else -1 if j.endswith("|root") else 0 for i,j in sorted(self.model.config.id2label.items())]
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e+=numpy.where(numpy.add.outer(numpy.identity(e.shape[0]),r)==0,0,numpy.nan)
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m=numpy.full((e.shape[0]+1,e.shape[1]+1),numpy.nan)
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m[1:,1:]=numpy.nanmax(e,axis=2).transpose()
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p=numpy.zeros(m.shape)
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p[1:,1:]=numpy.nanargmax(e,axis=2).transpose()
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for i in range(1,m.shape[0]):
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m[i,0],m[i,i],p[i,0]=m[i,i],numpy.nan,p[i,i]
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h=ufal.chu_liu_edmonds.chu_liu_edmonds(m)[0]
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u="# text = "+text+"\n"
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