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Restore optimized hidden_depth=0 for parser
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c10f63bf10
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@ -14,4 +14,8 @@ cdef class Parser:
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cdef readonly TransitionSystem moves
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cdef readonly object cfg
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cdef void _parse_step(self, StateC* state,
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const float* feat_weights,
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int nr_class, int nr_feat, int nr_piece) nogil
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#cdef int parseC(self, TokenC* tokens, int length, int nr_feat) nogil
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@ -257,10 +257,15 @@ cdef class Parser:
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nI=token_vector_width)
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with Model.use_device('cpu'):
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upper = chain(
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clone(Maxout(hidden_width), (depth-1)),
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zero_init(Affine(nr_class, drop_factor=0.0))
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)
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if depth == 0:
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upper = chain()
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upper.is_noop = True
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else:
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upper = chain(
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clone(Maxout(hidden_width), (depth-1)),
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zero_init(Affine(nr_class, drop_factor=0.0))
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)
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upper.is_noop = False
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# TODO: This is an unfortunate hack atm!
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# Used to set input dimensions in network.
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lower.begin_training(lower.ops.allocate((500, token_vector_width)))
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@ -412,20 +417,27 @@ cdef class Parser:
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cdef np.ndarray scores
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c_token_ids = <int*>token_ids.data
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c_is_valid = <int*>is_valid.data
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cdef int has_hidden = not getattr(vec2scores, 'is_noop', False)
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while not next_step.empty():
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for i in range(next_step.size()):
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st = next_step[i]
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st.set_context_tokens(&c_token_ids[i*nr_feat], nr_feat)
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self.moves.set_valid(&c_is_valid[i*nr_class], st)
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vectors = state2vec(token_ids[:next_step.size()])
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scores = vec2scores(vectors)
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c_scores = <float*>scores.data
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for i in range(next_step.size()):
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st = next_step[i]
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guess = arg_max_if_valid(
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&c_scores[i*nr_class], &c_is_valid[i*nr_class], nr_class)
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action = self.moves.c[guess]
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action.do(st, action.label)
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if not has_hidden:
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for i in cython.parallel.prange(
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next_step.size(), num_threads=6, nogil=True):
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self._parse_step(next_step[i],
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feat_weights, nr_class, nr_feat, nr_piece)
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else:
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for i in range(next_step.size()):
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st = next_step[i]
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st.set_context_tokens(&c_token_ids[i*nr_feat], nr_feat)
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self.moves.set_valid(&c_is_valid[i*nr_class], st)
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vectors = state2vec(token_ids[:next_step.size()])
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scores = vec2scores(vectors)
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c_scores = <float*>scores.data
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for i in range(next_step.size()):
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st = next_step[i]
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guess = arg_max_if_valid(
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&c_scores[i*nr_class], &c_is_valid[i*nr_class], nr_class)
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action = self.moves.c[guess]
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action.do(st, action.label)
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this_step, next_step = next_step, this_step
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next_step.clear()
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for st in this_step:
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@ -482,6 +494,28 @@ cdef class Parser:
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beams.append(beam)
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return beams
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cdef void _parse_step(self, StateC* state,
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const float* feat_weights,
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int nr_class, int nr_feat, int nr_piece) nogil:
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'''This only works with no hidden layers -- fast but inaccurate'''
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#for i in cython.parallel.prange(next_step.size(), num_threads=4, nogil=True):
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# self._parse_step(next_step[i], feat_weights, nr_class, nr_feat)
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token_ids = <int*>calloc(nr_feat, sizeof(int))
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scores = <float*>calloc(nr_class * nr_piece, sizeof(float))
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is_valid = <int*>calloc(nr_class, sizeof(int))
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state.set_context_tokens(token_ids, nr_feat)
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sum_state_features(scores,
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feat_weights, token_ids, 1, nr_feat, nr_class * nr_piece)
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self.moves.set_valid(is_valid, state)
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guess = arg_maxout_if_valid(scores, is_valid, nr_class, nr_piece)
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action = self.moves.c[guess]
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action.do(state, action.label)
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free(is_valid)
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free(scores)
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free(token_ids)
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def update(self, docs_tokvecs, golds, drop=0., sgd=None, losses=None):
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if not any(self.moves.has_gold(gold) for gold in golds):
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return None
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