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https://github.com/explosion/spaCy.git
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Improve efficiency of parser batching
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daac3e3573
commit
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@ -345,6 +345,7 @@ cdef cppclass StateC:
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this._s_i = src._s_i
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this._e_i = src._e_i
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this._break = src._break
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this.offset = src.offset
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void fast_forward() nogil:
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# space token attachement policy:
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@ -350,8 +350,15 @@ cdef class ArcEager(TransitionSystem):
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def __get__(self):
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return (SHIFT, REDUCE, LEFT, RIGHT, BREAK)
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def has_gold(self, GoldParse gold, start=0, end=None):
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end = end or len(gold.heads)
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if all([tag is None for tag in gold.heads[start:end]]):
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return False
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else:
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return True
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def preprocess_gold(self, GoldParse gold):
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if all([h is None for h in gold.heads]):
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if not self.has_gold(gold):
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return None
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for i in range(gold.length):
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if gold.heads[i] is None: # Missing values
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@ -95,8 +95,15 @@ cdef class BiluoPushDown(TransitionSystem):
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else:
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return MOVE_NAMES[move] + '-' + self.strings[label]
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def has_gold(self, GoldParse gold, start=0, end=None):
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end = end or len(gold.ner)
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if all([tag == '-' for tag in gold.ner[start:end]]):
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return False
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else:
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return True
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def preprocess_gold(self, GoldParse gold):
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if all([tag == '-' for tag in gold.ner]):
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if not self.has_gold(gold):
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return None
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for i in range(gold.length):
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gold.c.ner[i] = self.lookup_transition(gold.ner[i])
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@ -427,8 +427,7 @@ cdef class Parser:
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cuda_stream = get_cuda_stream()
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states, golds = self._init_gold_batch(docs, golds)
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max_length = min([len(doc) for doc in docs])
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states, golds, max_length = self._init_gold_batch(docs, golds)
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state2vec, vec2scores = self.get_batch_model(len(states), tokvecs, cuda_stream,
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0.0)
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todo = [(s, g) for (s, g) in zip(states, golds)
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@ -472,46 +471,36 @@ cdef class Parser:
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backprops, sgd, cuda_stream)
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return self.model[0].ops.unflatten(d_tokvecs, [len(d) for d in docs])
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def _init_gold_batch(self, docs, golds):
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def _init_gold_batch(self, whole_docs, whole_golds):
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"""Make a square batch, of length equal to the shortest doc. A long
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doc will get multiple states. Let's say we have a doc of length 2*N,
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where N is the shortest doc. We'll make two states, one representing
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long_doc[:N], and another representing long_doc[N:]."""
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cdef StateClass state
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lengths = [len(doc) for doc in docs]
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min_length = min(lengths)
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offset = 0
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cdef:
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StateClass state
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Transition action
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whole_states = self.moves.init_batch(whole_docs)
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max_length = max(5, min(20, min([len(doc) for doc in whole_docs])))
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states = []
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extra_golds = []
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cdef Pool mem = Pool()
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costs = <float*>mem.alloc(self.moves.n_moves, sizeof(float))
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is_valid = <int*>mem.alloc(self.moves.n_moves, sizeof(int))
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for doc, gold in zip(docs, golds):
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golds = []
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for doc, state, gold in zip(whole_docs, whole_states, whole_golds):
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gold = self.moves.preprocess_gold(gold)
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state = StateClass(doc, offset=offset)
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self.moves.initialize_state(state.c)
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if not state.is_final():
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states.append(state)
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extra_golds.append(gold)
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start = min(min_length, len(doc))
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if gold is None:
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continue
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oracle_actions = self.moves.get_oracle_sequence(doc, gold)
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start = 0
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while start < len(doc):
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length = min(min_length, len(doc)-start)
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state = StateClass(doc, offset=offset)
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self.moves.initialize_state(state.c)
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state = state.copy()
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while state.B(0) < start and not state.is_final():
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self.moves.set_costs(is_valid, costs, state, gold)
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for i in range(self.moves.n_moves):
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if is_valid[i] and costs[i] <= 0:
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self.moves.c[i].do(state.c, self.moves.c[i].label)
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break
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else:
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raise ValueError("Could not find gold move")
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start += length
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if not state.is_final():
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action = self.moves.c[oracle_actions.pop(0)]
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action.do(state.c, action.label)
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has_gold = self.moves.has_gold(gold, start=start,
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end=start+max_length)
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if not state.is_final() and has_gold:
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states.append(state)
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extra_golds.append(gold)
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offset += len(doc)
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return states, extra_golds
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golds.append(gold)
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start += min(max_length, len(doc)-start)
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return states, golds, max_length
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def _make_updates(self, d_tokvecs, backprops, sgd, cuda_stream=None):
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# Tells CUDA to block, so our async copies complete.
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@ -41,6 +41,11 @@ cdef class StateClass:
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def is_final(self):
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return self.c.is_final()
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def copy(self):
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cdef StateClass new_state = StateClass.init(self.c._sent, self.c.length)
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new_state.c.clone(self.c)
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return new_state
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def print_state(self, words):
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words = list(words) + ['_']
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top = words[self.S(0)] + '_%d' % self.S_(0).head
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@ -61,6 +61,24 @@ cdef class TransitionSystem:
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offset += len(doc)
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return states
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def get_oracle_sequence(self, doc, GoldParse gold):
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cdef Pool mem = Pool()
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costs = <float*>mem.alloc(self.n_moves, sizeof(float))
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is_valid = <int*>mem.alloc(self.n_moves, sizeof(int))
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cdef StateClass state = StateClass(doc, offset=0)
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self.initialize_state(state.c)
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history = []
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while not state.is_final():
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self.set_costs(is_valid, costs, state, gold)
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for i in range(self.n_moves):
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if is_valid[i] and costs[i] <= 0:
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action = self.c[i]
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history.append(i)
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action.do(state.c, action.label)
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break
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return history
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cdef int initialize_state(self, StateC* state) nogil:
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pass
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@ -92,11 +110,21 @@ cdef class TransitionSystem:
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StateClass stcls, GoldParse gold) except -1:
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cdef int i
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self.set_valid(is_valid, stcls.c)
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cdef int n_gold = 0
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for i in range(self.n_moves):
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if is_valid[i]:
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costs[i] = self.c[i].get_cost(stcls, &gold.c, self.c[i].label)
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n_gold += costs[i] <= 0
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else:
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costs[i] = 9000
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if n_gold <= 0:
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print(gold.words)
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print(gold.ner)
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raise ValueError(
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"Could not find a gold-standard action to supervise "
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"the entity recognizer\n"
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"The transition system has %d actions.\n"
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"%s" % (self.n_moves))
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def add_action(self, int action, label):
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if not isinstance(label, int):
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