Yet Another Accuracy Func For LSTM+CTC (in mxnet/example/warpctc)

gistfile1.txt

# When processing Sequence Tagging problems,
# An accuracy func which is too strict is not convergence-friendly.
# This Func is the solution of a naive leetcode problem LCS (Largest Common Subsequence),
# Original All-Correct-Or-Nothing accuracy function takes 7x times long to achieve certain accuracy.

def LCS(p,l):
    if len(p)==0:
        return 0
    P = np.array(list(p)).reshape((1,len(p)))
    L = np.array(list(l)).reshape((len(l),1))
    M = np.int32(P==L)
    for i in range(M.shape[0]):
        for j in range(M.shape[1]):
            up = 0 if i==0 else M[i-1,j]
            left = 0 if j==0 else M[i,j-1]
            M[i,j] = max(up,left, M[i,j] if (i==0 or j==0) else M[i,j]+M[i-1,j-1])
    return M.max()


def Accuracy_LCS(label, pred):
    global BATCH_SIZE
    global SEQ_LENGTH
    #global CTX_LENGTH
    hit = 0.
    total = 0.
    for i in range(BATCH_SIZE):
        l = remove_blank(label[i])
        p = []
        for k in range(SEQ_LENGTH):
            p.append(np.argmax(pred[k * BATCH_SIZE + i]))
        p = ctc_label(p)
        
        ## Dynamic Programming Finding LCS
        hit += LCS(p,l)*1.0/len(l)
        total += 1.0
    return hit / total