mirror of https://github.com/explosion/spaCy.git
Fix beam parse. Not sure if working
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24b45b45c6
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@ -87,8 +87,9 @@ cdef class ParserBeam(object):
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def _set_scores(self, Beam beam, scores):
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for i in range(beam.size):
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state = <StateClass>beam.at(i)
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for j in range(beam.nr_class):
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beam.scores[i][j] = scores[i, j]
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if not state.is_final():
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for j in range(beam.nr_class):
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beam.scores[i][j] = scores[i, j]
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self.moves.set_valid(beam.is_valid[i], state.c)
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def _set_costs(self, Beam beam, GoldParse gold, int follow_gold=False):
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@ -137,8 +138,8 @@ def update_beam(TransitionSystem moves, int nr_feature, int max_steps,
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backprops.append((token_ids, bp_vectors, bp_scores))
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p_scores = [scores[indices] for indices in p_indices]
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g_scores = [scores[indices] for indices in g_indices]
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p_scores = [numpy.ascontiguousarray(scores[indices], dtype='f') for indices in p_indices]
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g_scores = [numpy.ascontiguousarray(scores[indices], dtype='f') for indices in g_indices]
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pbeam.advance(p_scores)
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gbeam.advance(g_scores, follow_gold=True)
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@ -176,8 +177,8 @@ def get_states(pbeams, gbeams, beam_map):
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beam_map[key] = len(states)
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states.append(<StateClass>gbeam.at(i))
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p_indices = numpy.asarray(p_indices, dtype='i')
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g_indices = numpy.asarray(g_indices, dtype='i')
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p_indices = [numpy.asarray(idx, dtype='i') for idx in p_indices]
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g_indices = [numpy.asarray(idx, dtype='i') for idx in g_indices]
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return states, p_indices, g_indices
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@ -203,7 +204,9 @@ def get_gradient(nr_class, beam_maps, histories, losses):
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key = tuple([eg_id])
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for j, clas in enumerate(hist):
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i = beam_maps[j][key]
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grads[j][i, clas] = loss
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# In step j, at state i action clas
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# resulted in loss
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grads[j][i, clas] += loss
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key = key + tuple([clas])
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return grads
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