def test_nkf_acc(nkfdict,inputlist,tgtlist,model,tokenizer,nkflog,k=5,bert=True):
correct = []
tot_score = []
tok_preds,top_probs = tp.get_predictions(inputlist,model,tokenizer,k=k,bert=bert)
tok_probs = tp.get_probabilities(inputlist,tgtlist,model,tokenizer,bert=bert)
for i,pred in enumerate(tok_preds):
nkfdict[i]['toppreds'] = pred
nkfdict[i]['tgtprob'] = tok_probs[i]
nkfdict[i]['topprobs'] = top_probs[i]
score = 0
for candidate in pred:
if candidate.strip() in nkfdict[i]['exp']:
score = 1
if score == 1:
ctup = (nkfdict[i]['sent'],nkfdict[i]['exp'],pred,nkfdict[i]['cond'])
if ctup not in correct:
correct.append(ctup)
if nkfdict[i]['cond'] == 'TA':
tot_score.append(score)
conddict = make_conddict(nkfdict)
n4report = sim_nkf_N400(conddict,nkflog,k=k,bert=bert)
report = "\nPrediction 'accuracy':\n"
report += 'TRUE TGT in top %s preds: %s (%s/%s)\n'%(k,get_acc(tot_score),sum(tot_score),len(tot_score))
return report,n4report,correct
def test_fk_acc(hldict,inputlist,tgtlist,model,tokenizer,setting,fklog,k=5,bert=True):
tok_preds,top_probs = tp.get_predictions(inputlist,model,tokenizer,k=k,bert=bert)
tok_probs = tp.get_probabilities(inputlist,tgtlist,model,tokenizer,bert=bert)
tot_score = []
by_constraint_score = {}
by_constraint_score['H'] = []
by_constraint_score['L'] = []
correct = []
used = []
for i,pr in enumerate(tok_preds):
sent = hldict[i]['sent'][setting]
hldict[i]['toppreds'] = pr
hldict[i]['tgtprob'] = tok_probs[i]
hldict[i]['topprobs'] = top_probs[i]
score = 0
if sent in used: continue
used.append(sent)
for candidate in pr:
if candidate.strip() in hldict[i]['exp']:
score = 1
if score == 1:
ctup = (hldict[i]['sent'][setting],hldict[i]['exp'],pr,hldict[i]['constraint'])
if ctup not in correct:
correct.append(ctup)
tot_score.append(score)
by_constraint_score[hldict[i]['constraint']].append(score)
conddict = make_conddict(hldict)
n4report = sim_fk_N400(conddict,fklog,setting,k=k,bert=bert)
tot_acc = get_acc(tot_score)
report = '\nPrediction accuracies:\n'
report += 'EXP TGT in TOP %s preds: %s (%s/%s)\n'%(k,tot_acc,sum(tot_score),len(tot_score))
report += 'in TOP %s for H: %s\n'%(k,get_acc(by_constraint_score['H']))
report += 'in TOP %s for L: %s\n'%(k,get_acc(by_constraint_score['L']))
return report,n4report,correct,tot_acc
def test_rr_acc(clozedict,inputlist,tgtlist,clozelist,model,tokenizer,rrlog,k=5,bert=True,scat=None):
tok_preds,top_probs = tp.get_predictions(inputlist,model,tokenizer,k=k,bert=bert)
tok_probs = tp.get_probabilities(inputlist,tgtlist,model,tokenizer,bert=bert)
tot_score = []
correct = []
correct_by_quartile = {'q1_corr':[],'q2_corr':[],'q3_corr':[],'q4_corr':[]}
avgcloze = np.average(clozelist)
q1 = np.percentile(clozelist,25)
q3 = np.percentile(clozelist,75)
q2 = np.percentile(clozelist,50)
q4 = max(clozelist)
predcounts = Counter()
for i,pred in enumerate(tok_preds):
clozedict[i]['toppreds'] = pred
clozedict[i]['tgtprob'] = tok_probs[i]
clozedict[i]['topprobs'] = top_probs[i]
score = 0
itm = clozedict[i]['item']
cond = clozedict[i]['cond']
for candidate in pred:
if candidate.strip() in [e.split()[0] for e in clozedict[i]['exp']]:
score = 1
if score == 1:
ctup = (clozedict[i]['sent'],clozedict[i]['exp'],pred,clozedict[i]['maxcloze'])
if ctup not in correct:
correct.append(ctup)
tot_score.append(score)
if clozedict[i]['maxcloze'] <= q1:
correct_by_quartile['q1_corr'].append(score)
elif clozedict[i]['maxcloze'] <= q2:
correct_by_quartile['q2_corr'].append(score)
elif clozedict[i]['maxcloze'] <= q3:
correct_by_quartile['q3_corr'].append(score)
else:
correct_by_quartile['q4_corr'].append(score)
conddict = make_conddict(clozedict)
n4report = sim_rr_N400(conddict,rrlog,scat=scat,k=k,bert=bert)
report = '\nPrediction accuracies:\n'
report += 'TGT in top %s preds: %s (%s/%s)\n'%(k,get_acc(tot_score),sum(tot_score),len(tot_score))
report += 'TGT in top %s for Q1: %s (%s upper, %s items)\n'%(k,get_acc(correct_by_quartile['q1_corr']),q1,len(correct_by_quartile['q1_corr']))
report += 'TGT in top %s for Q2: %s (%s upper, %s items)\n'%(k,get_acc(correct_by_quartile['q2_corr']),q2,len(correct_by_quartile['q2_corr']))
report += 'TGT in top %s for Q3: %s (%s upper, %s items)\n'%(k,get_acc(correct_by_quartile['q3_corr']),q3,len(correct_by_quartile['q3_corr']))
report += 'TGT in top %s for Q4: %s (%s upper, %s items)\n'%(k,get_acc(correct_by_quartile['q4_corr']),q4,len(correct_by_quartile['q4_corr']))
report += 'AVG CLOZE: %s\n'%avgcloze
report += 'MED CLOZE: %s\n'%q2
return report,n4report,correct,predcounts
def get_model_responses(inputlist,
tgtlist,
modeliname,
model,
tokenizer,
k=5,
bert=True):
top_preds, top_probs = tp.get_predictions(inputlist,
model,
tokenizer,
k=k,
bert=bert)
tgt_probs = tp.get_probabilities(inputlist,
tgtlist,
model,
tokenizer,
bert=bert)
return top_preds, top_probs, tgt_probs
