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Restore use of Example object in parser.train

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This commit is contained in:
Matthew Honnibal 2016-08-29 14:26:43 +02:00
parent 14f3da2a2e
commit 1a1b2f9174
1 changed files with 13 additions and 13 deletions
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26
spacy/syntax/parser.pyx
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@ -29,6 +29,7 @@ from thinc.typedefs cimport weight_t, class_t, feat_t, atom_t, hash_t, idx_t
from thinc.linear.avgtron cimport AveragedPerceptron
from thinc.linalg cimport VecVec
from thinc.structs cimport NeuralNetC, SparseArrayC, ExampleC
from thinc.neural.nn cimport NeuralNet
from thinc.extra.eg cimport Example
from preshed.maps cimport MapStruct
@ -100,7 +101,9 @@ cdef class Parser:
update_step=cfg.update_step, eta=cfg.eta, rho=cfg.rho,
noise=cfg.noise)
else:
model = ParserPerceptron(get_templates(cfg.feat_set))
model = ParserPerceptron(get_templates(cfg.feat_set),
learn_rate=cfg.get('eta', 0.001),
l1_penalty=cfg.rho)
if path.exists(path.join(model_dir, 'model')):
model.load(path.join(model_dir, 'model'))
@ -165,14 +168,13 @@ cdef class Parser:
yield doc
cdef int parseC(self, TokenC* tokens, int length, int nr_feat, int nr_class) with gil:
cdef Example py_eg = Example(nr_class=nr_class, nr_atom=CONTEXT_SIZE, nr_feat=nr_feat,
widths=self.model.widths)
cdef Example py_eg = Example(nr_class=nr_class, nr_feat=nr_feat)
cdef ExampleC* eg = py_eg.c
state = new StateC(tokens, length)
self.moves.initialize_state(state)
cdef int i
while not state.is_final():
self.model.set_featuresC(eg, state)
eg.nr_feat = self.model.set_featuresC(eg.features, state)
self.moves.set_valid(eg.is_valid, state)
self.model.set_scoresC(eg.scores, eg.features, eg.nr_feat)
@ -190,25 +192,23 @@ cdef class Parser:
del state
return 0
def train(self, Doc tokens, GoldParse gold):
def train(self, Doc tokens, GoldParse gold, itn=0):
self.moves.preprocess_gold(gold)
cdef StateClass stcls = StateClass.init(tokens.c, tokens.length)
self.moves.initialize_state(stcls.c)
cdef Pool mem = Pool()
cdef Example eg = Example(
nr_class=self.moves.n_moves,
widths=self.model.widths,
nr_atom=CONTEXT_SIZE,
nr_feat=self.model.nr_feat)
loss = 0
cdef Transition action
while not stcls.is_final():
self.model.set_featuresC(eg.c, stcls.c)
eg.c.nr_feat = self.model.set_featuresC(eg.c.features, stcls.c)
self.model.set_scoresC(eg.c.scores, eg.c.features, eg.c.nr_feat)
self.moves.set_costs(eg.c.is_valid, eg.c.costs, stcls, gold)
guess = VecVec.arg_max_if_true(eg.c.scores, eg.c.is_valid, eg.c.nr_class)
assert guess >= 0
action = self.moves.c[guess]
for i in range(self.moves.n_moves):
if eg.c.costs[i] < 0:
eg.c.costs[i] = 0
action = self.moves.c[eg.guess]
action.do(stcls.c, action.label)
loss += self.model.update(eg)
@ -273,7 +273,7 @@ cdef class StepwiseState:
def predict(self):
self.eg.reset()
self.parser.model.set_featuresC(self.eg.c, self.stcls.c)
self.eg.c.nr_feat = self.parser.model.set_featuresC(self.eg.c.features, self.stcls.c)
self.parser.moves.set_valid(self.eg.c.is_valid, self.stcls.c)
self.parser.model.set_scoresC(self.eg.c.scores,
self.eg.c.features, self.eg.c.nr_feat)