Draft support of regression loss in parser

This commit is contained in:
Matthew Honnibal 2017-05-13 17:17:27 -05:00
parent 827b5af697
commit f85c8464f7

View File

@ -182,17 +182,39 @@ cdef void cpu_log_loss(float* d_scores,
for i in range(O):
if is_valid[i]:
Z += exp(scores[i] - max_)
if costs[i] <= 0:
if costs[i] <= costs[best]:
gZ += exp(scores[i] - gmax)
for i in range(O):
if not is_valid[i]:
d_scores[i] = 0.
elif costs[i] <= 0:
elif costs[i] <= costs[best]:
d_scores[i] = (exp(scores[i]-max_) / Z) - (exp(scores[i]-gmax)/gZ)
else:
d_scores[i] = exp(scores[i]-max_) / Z
cdef void cpu_regression_loss(float* d_scores,
const float* costs, const int* is_valid, const float* scores,
int O) nogil:
cdef float eps = 2.
best = arg_max_if_gold(scores, costs, is_valid, O)
for i in range(O):
if not is_valid[i]:
d_scores[i] = 0.
elif scores[i] < scores[best]:
d_scores[i] = 0.
else:
# I doubt this is correct?
# Looking for something like Huber loss
diff = scores[i] - -costs[i]
if diff > eps:
d_scores[i] = eps
elif diff < -eps:
d_scores[i] = -eps
else:
d_scores[i] = diff
def init_states(TransitionSystem moves, docs):
cdef Doc doc
cdef StateClass state