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Add learned missing values for parser

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This commit is contained in:
Matthew Honnibal 2017-10-28 16:45:14 +00:00
parent 64e4ff7c4b
commit df4803cc6d
1 changed files with 21 additions and 5 deletions
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26
spacy/_ml.py
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@ -88,7 +88,11 @@ def _preprocess_doc(docs, drop=0.):
lambda obj: (obj.nF, obj.nO, obj.nP, obj.nI)), lambda obj: (obj.nF, obj.nO, obj.nP, obj.nI)),
b=Biases("Bias vector", b=Biases("Bias vector",
lambda obj: (obj.nO, obj.nP)), lambda obj: (obj.nO, obj.nP)),
pad=Synapses("Pad",
lambda obj: (1, obj.nF, obj.nO, obj.nP),
lambda M, ops: ops.normal_init(M, 1.)),
d_W=Gradient("W"), d_W=Gradient("W"),
d_pad=Gradient("pad"),
d_b=Gradient("b")) d_b=Gradient("b"))
class PrecomputableAffine(Model): class PrecomputableAffine(Model):
def __init__(self, nO=None, nI=None, nF=None, nP=None, **kwargs): def __init__(self, nO=None, nI=None, nF=None, nP=None, **kwargs):
@ -99,13 +103,14 @@ class PrecomputableAffine(Model):
self.nF = nF self.nF = nF
def begin_update(self, X, drop=0.): def begin_update(self, X, drop=0.):
Yf = self.ops.dot(X, Yf = self.ops.xp.dot(X,
self.W.reshape((self.nF*self.nO*self.nP, self.nI)).T) self.W.reshape((self.nF*self.nO*self.nP, self.nI)).T)
Yf = Yf.reshape((Yf.shape[0], self.nF, self.nO, self.nP))
Yf = Yf.reshape((X.shape[0], self.nF, self.nO, self.nP)) Yf = self._add_padding(Yf)
def backward(dY_ids, sgd=None): def backward(dY_ids, sgd=None):
dY, ids = dY_ids dY, ids = dY_ids
dY, ids = self._backprop_padding(dY, ids)
Xf = X[ids] Xf = X[ids]
Xf = Xf.reshape((Xf.shape[0], self.nF * self.nI)) Xf = Xf.reshape((Xf.shape[0], self.nF * self.nI))
@ -116,7 +121,7 @@ class PrecomputableAffine(Model):
Wopfi = self.ops.xp.ascontiguousarray(Wopfi) Wopfi = self.ops.xp.ascontiguousarray(Wopfi)
Wopfi = Wopfi.reshape((self.nO*self.nP, self.nF * self.nI)) Wopfi = Wopfi.reshape((self.nO*self.nP, self.nF * self.nI))
dXf = self.ops.dot(dY.reshape((dY.shape[0], self.nO*self.nP)), Wopfi) dXf = self.ops.dot(dY.reshape((dY.shape[0], self.nO*self.nP)), Wopfi)
# Reuse the buffer # Reuse the buffer
dWopfi = Wopfi; dWopfi.fill(0.) dWopfi = Wopfi; dWopfi.fill(0.)
self.ops.xp.dot(dY.T, Xf, out=dWopfi) self.ops.xp.dot(dY.T, Xf, out=dWopfi)
@ -128,6 +133,17 @@ class PrecomputableAffine(Model):
sgd(self._mem.weights, self._mem.gradient, key=self.id) sgd(self._mem.weights, self._mem.gradient, key=self.id)
return dXf.reshape((dXf.shape[0], self.nF, self.nI)) return dXf.reshape((dXf.shape[0], self.nF, self.nI))
return Yf, backward return Yf, backward
def _add_padding(self, Yf):
Yf_padded = self.ops.xp.vstack((self.pad, Yf))
return Yf_padded[1:]
def _backprop_padding(self, dY, ids):
for i in range(ids.shape[0]):
for j in range(ids.shape[1]):
if ids[i, j] < 0:
self.d_pad[0, j] += dY[i, j]
return dY, ids
@staticmethod @staticmethod
def init_weights(model): def init_weights(model):