33 lines
912 B
Python
33 lines
912 B
Python
import numpy as np
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def get_alignment(attn_probs, n_head):
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max_F = 0
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assert attn_probs[0].shape[0] % n_head == 0
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batch_size = int(attn_probs[0].shape[0] // n_head)
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for i in range(len(attn_probs)):
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multi_attn = attn_probs[i].numpy()
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for j in range(n_head):
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attn = multi_attn[j*batch_size:(j+1)*batch_size]
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F = score_F(attn)
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if max_F < F:
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max_F = F
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max_attn = attn
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alignment = compute_duration(max_attn)
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return alignment
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def score_F(attn):
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max = np.max(attn, axis=-1)
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mean = np.mean(max)
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return mean
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def compute_duration(attn):
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alignment = np.zeros([attn.shape[0],attn.shape[2]])
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for i in range(attn.shape[0]):
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for j in range(attn.shape[1]):
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max_index = attn[i,j].tolist().index(attn[i,j].max())
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alignment[i,max_index] += 1
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return alignment
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