def _get2(context, xi, span):
if len(xi) <= span[0][0]:
return ""
if len(xi[span[0][0]]) <= span[1][1]:
return ""
print(span)
return get_phrase(context, xi, span)
def ensemble3(context, wordss, y1_list, y2_list):
d = defaultdict(float)
for y1, y2 in zip(y1_list, y2_list):
span, score = get_best_span(y1, y2)
phrase = get_phrase(context, wordss, span)
d[phrase] += score
return max(d.items(), key=lambda pair: pair[1])[0]
def ensemble4(context, wordss, y1_list, y2_list):
d = defaultdict(lambda: 0.0)
for y1, y2 in zip(y1_list, y2_list):
for span, score in get_span_score_pairs(y1, y2):
d[span] += score
span = max(d.items(), key=lambda pair: pair[1])[0]
phrase = get_phrase(context, wordss, span)
return phrase
def _get2(context, xi, span):
if len(xi) <= span[0][0]:
return ""
if len(xi[span[0][0]]) <= span[1][1]:
return ""
if self.config.na:
start, stop = span
if start == (0, 0) and stop == (0, 1):
return ""
return get_phrase(context, xi, span)
def ensemble2(context, wordss, y1_list, y2_list):
start_dict = defaultdict(float)
stop_dict = defaultdict(float)
for y1, y2 in zip(y1_list, y2_list):
span, score = get_best_span(y1, y2)
start_dict[span[0]] += y1[span[0][0]][span[0][1]]
stop_dict[span[1]] += y2[span[1][0]][span[1][1]]
start = max(start_dict.items(), key=lambda pair: pair[1])[0]
stop = max(stop_dict.items(), key=lambda pair: pair[1])[0]
best_span = (start, stop)
return get_phrase(context, wordss, best_span)
def ensemble3_getAllSpans_Snigdha(context, wordss, y1_list, y2_list,
max_span_len):
d = defaultdict(float)
d_span = {} #Snigdha
for y1, y2 in zip(y1_list, y2_list):
d_span_scores = get_all_spans_Snigdha(y1, y2, context, wordss,
max_span_len)
for span in d_span_scores:
phrase = get_phrase(context, wordss, span)
d[phrase] += d_span_scores[span]
d_span[phrase] = span
return (d, d_span)
def ensemble1(context, wordss, y1_list, y2_list):
"""
:param context: Original context
:param wordss: tokenized words (nested 2D list)
:param y1_list: list of start index probs (each element corresponds to probs form single model)
:param y2_list: list of stop index probs
:return:
"""
sum_y1 = combine_y_list(y1_list)
sum_y2 = combine_y_list(y2_list)
span, score = get_best_span(sum_y1, sum_y2)
return get_phrase(context, wordss, span)
def ensemble3_Snigdha(context, wordss, y1_list, y2_list):
d = defaultdict(float)
d_span = {} #Snigdha
outputted = list() #Snigdha
for i in range(
0, no_of_top_candidates
): # Snigdha: Change here to determine how many candidates you want it to output
for y1, y2 in zip(y1_list, y2_list):
span, score = get_best_span_Snigdha(y1, y2, outputted)
phrase = get_phrase(context, wordss, span)
d[phrase] += score
d_span[phrase] = span
outputted.append(span) #Snigdha
return (d, d_span)
def _get2(context, xi, span):
if len(xi) <= span[0][0]:
return ""
if len(xi[span[0][0]]) <= span[1][1]:
return ""
return get_phrase(context, xi, span)