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Fix parser for GPU

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Matthew Honnibal 2018-05-19 17:24:34 +00:00
parent 260707a4c3
commit 7431e9c87f
2 changed files with 2 additions and 9 deletions
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2
spacy/syntax/_parser_model.pxd
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@ -19,12 +19,10 @@ cdef struct WeightsC:
const float* feat_bias const float* feat_bias
const float* hidden_bias const float* hidden_bias
const float* hidden_weights const float* hidden_weights
const float* vectors
cdef struct ActivationsC: cdef struct ActivationsC:
int* token_ids int* token_ids
float* vectors
float* unmaxed float* unmaxed
float* scores float* scores
float* hiddens float* hiddens

9
spacy/syntax/_parser_model.pyx
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@ -50,8 +50,6 @@ cdef WeightsC get_c_weights(model) except *:
cdef np.ndarray vec2scores_b = model.vec2scores.b cdef np.ndarray vec2scores_b = model.vec2scores.b
output.hidden_weights = <const float*>vec2scores_W.data output.hidden_weights = <const float*>vec2scores_W.data
output.hidden_bias = <const float*>vec2scores_b.data output.hidden_bias = <const float*>vec2scores_b.data
cdef np.ndarray tokvecs = model.tokvecs
output.vectors = <float*>tokvecs.data
return output return output
@ -72,7 +70,6 @@ cdef void resize_activations(ActivationsC* A, SizesC n) nogil:
return return
if A._max_size == 0: if A._max_size == 0:
A.token_ids = <int*>calloc(n.states * n.feats, sizeof(A.token_ids[0])) A.token_ids = <int*>calloc(n.states * n.feats, sizeof(A.token_ids[0]))
A.vectors = <float*>calloc(n.states * n.embed_width, sizeof(A.vectors[0]))
A.scores = <float*>calloc(n.states * n.classes, sizeof(A.scores[0])) A.scores = <float*>calloc(n.states * n.classes, sizeof(A.scores[0]))
A.unmaxed = <float*>calloc(n.states * n.hiddens * n.pieces, sizeof(A.unmaxed[0])) A.unmaxed = <float*>calloc(n.states * n.hiddens * n.pieces, sizeof(A.unmaxed[0]))
A.hiddens = <float*>calloc(n.states * n.hiddens, sizeof(A.hiddens[0])) A.hiddens = <float*>calloc(n.states * n.hiddens, sizeof(A.hiddens[0]))
@ -81,8 +78,6 @@ cdef void resize_activations(ActivationsC* A, SizesC n) nogil:
else: else:
A.token_ids = <int*>realloc(A.token_ids, A.token_ids = <int*>realloc(A.token_ids,
n.states * n.feats * sizeof(A.token_ids[0])) n.states * n.feats * sizeof(A.token_ids[0]))
A.vectors = <float*>realloc(A.vectors,
n.states * n.embed_width * sizeof(A.vectors[0]))
A.scores = <float*>realloc(A.scores, A.scores = <float*>realloc(A.scores,
n.states * n.classes * sizeof(A.scores[0])) n.states * n.classes * sizeof(A.scores[0]))
A.unmaxed = <float*>realloc(A.unmaxed, A.unmaxed = <float*>realloc(A.unmaxed,
@ -242,7 +237,7 @@ class ParserStepModel(Model):
def begin_update(self, states, drop=0.): def begin_update(self, states, drop=0.):
token_ids = self.get_token_ids(states) token_ids = self.get_token_ids(states)
vector, get_d_tokvecs = self.state2vec.begin_update(token_ids, drop=0.0) vector, get_d_tokvecs = self.state2vec.begin_update(token_ids, drop=0.0)
mask = self.ops.get_dropout_mask(vector.shape, drop) mask = self.vec2scores.ops.get_dropout_mask(vector.shape, drop)
if mask is not None: if mask is not None:
vector *= mask vector *= mask
scores, get_d_vector = self.vec2scores.begin_update(vector, drop=drop) scores, get_d_vector = self.vec2scores.begin_update(vector, drop=drop)
@ -251,7 +246,7 @@ class ParserStepModel(Model):
d_vector = get_d_vector(d_scores, sgd=sgd) d_vector = get_d_vector(d_scores, sgd=sgd)
if mask is not None: if mask is not None:
d_vector *= mask d_vector *= mask
if isinstance(self.ops, CupyOps) \ if isinstance(self.state2vec.ops, CupyOps) \
and not isinstance(token_ids, self.state2vec.ops.xp.ndarray): and not isinstance(token_ids, self.state2vec.ops.xp.ndarray):
# Move token_ids and d_vector to GPU, asynchronously # Move token_ids and d_vector to GPU, asynchronously
self.backprops.append(( self.backprops.append((