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Clean up unused parser code

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Matthew Honnibal 2017-05-08 15:42:04 +02:00
parent 17efb1c001
commit b44f7e259c
1 changed files with 0 additions and 76 deletions
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76
spacy/syntax/parser.pyx
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@ -353,62 +353,6 @@ cdef class Parser:
self.cfg.setdefault('extra_labels', []).append(label) self.cfg.setdefault('extra_labels', []).append(label)
def _begin_update(self, model, states, tokvecs, drop=0.):
nr_class = self.moves.n_moves
attr_names = self.model.ops.allocate((2,), dtype='i')
attr_names[0] = TAG
attr_names[1] = DEP
features = self._get_features(states, tokvecs, attr_names)
scores, finish_update = self.model.begin_update(features, drop=drop)
assert scores.shape[0] == len(states), (len(states), scores.shape)
assert len(scores.shape) == 2
is_valid = self.model.ops.allocate((len(states), nr_class), dtype='i')
self._validate_batch(is_valid, states)
softmaxed = self.model.ops.softmax(scores)
softmaxed *= is_valid
softmaxed /= softmaxed.sum(axis=1).reshape((softmaxed.shape[0], 1))
def backward(golds, sgd=None, losses=[], force_gold=False):
nonlocal softmaxed
costs = self.model.ops.allocate((len(states), nr_class), dtype='f')
d_scores = self.model.ops.allocate((len(states), nr_class), dtype='f')
self._cost_batch(costs, is_valid, states, golds)
self._set_gradient(d_scores, scores, is_valid, costs)
losses.append(numpy.abs(d_scores).sum())
if force_gold:
softmaxed *= costs <= 0
return finish_update(d_scores, sgd=sgd)
return softmaxed, backward
def _get_features(self, states, all_tokvecs, attr_names,
nF=1, nB=0, nS=2, nL=2, nR=2):
n_tokens = states[0].nr_context_tokens(nF, nB, nS, nL, nR)
vector_length = all_tokvecs[0].shape[1]
tokens = self.model.ops.allocate((len(states), n_tokens), dtype='int32')
features = self.model.ops.allocate((len(states), n_tokens, attr_names.shape[0]), dtype='uint64')
tokvecs = self.model.ops.allocate((len(states), n_tokens, vector_length), dtype='f')
for i, state in enumerate(states):
state.set_context_tokens(tokens[i], nF, nB, nS, nL, nR)
state.set_attributes(features[i], tokens[i], attr_names)
state.set_token_vectors(tokvecs[i], all_tokvecs[i], tokens[i])
return (tokens, features, tokvecs)
cdef int dropout(FeatureC* feats, int nr_feat, float prob) except -1:
if prob <= 0 or prob >= 1.:
return 0
cdef double[::1] py_probs = numpy.random.uniform(0., 1., nr_feat)
cdef double* probs = &py_probs[0]
for i in range(nr_feat):
if probs[i] >= prob:
feats[i].value /= prob
else:
feats[i].value = 0.
cdef class StepwiseState: cdef class StepwiseState:
cdef readonly StateClass stcls cdef readonly StateClass stcls
cdef readonly Example eg cdef readonly Example eg
@ -520,23 +464,3 @@ class ParserStateError(ValueError):
"https://github.com/spacy-io/spaCy/issues/429\n" "https://github.com/spacy-io/spaCy/issues/429\n"
"Please include the text that the parser failed on, which is:\n" "Please include the text that the parser failed on, which is:\n"
"%s" % repr(doc.text)) "%s" % repr(doc.text))
cdef int arg_max_if_gold(const weight_t* scores, const weight_t* costs, int n) nogil:
cdef int best = -1
for i in range(n):
if costs[i] <= 0:
if best == -1 or scores[i] > scores[best]:
best = i
return best
cdef int _arg_max_clas(const weight_t* scores, int move, const Transition* actions,
int nr_class) except -1:
cdef weight_t score = 0
cdef int mode = -1
cdef int i
for i in range(nr_class):
if actions[i].move == move and (mode == -1 or scores[i] >= score):
mode = i
score = scores[i]
return mode