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https://github.com/explosion/spaCy.git
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Refactor morphologizer class map
This commit is contained in:
Matthew Honnibal
parent
f742900f83
commit
41a3016019
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@ -20,6 +20,7 @@ cdef class Morphology:
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cdef readonly object tag_names
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cdef readonly object reverse_index
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cdef readonly object exc
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cdef readonly object _feat_map
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cdef readonly PreshMapArray _cache
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cdef readonly int n_tags
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@ -36,6 +37,5 @@ cdef class Morphology:
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cdef int check_feature(const MorphAnalysisC* tag, attr_t feature) nogil
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cdef attr_t get_field(const MorphAnalysisC* tag, int field) nogil
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cdef list list_features(const MorphAnalysisC* tag)
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cdef int attribute_to_field(unicode attribute)
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cdef tag_to_json(const MorphAnalysisC* tag)
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@ -93,26 +93,34 @@ def _normalize_props(props):
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return out
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def parse_feature(feature):
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field = FEATURE_FIELDS[feature]
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offset = FEATURE_OFFSETS[feature]
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return (field, offset)
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class MorphologyClassMap(object):
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def __init__(self, features, fields):
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self.features = tuple(features)
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self.fields = tuple(fields)
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self.id2feat = {get_string_id(name): name for name in features}
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self.feat2field = {feature: fields[feature.split('_', 1)[0]] for feature in features}
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self.field2feats = {}
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self.col2info = []
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self.attr2field = dict(LOWER_FIELDS.items())
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for feature in features:
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field = self.feat2field[feature]
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if field not in self.field2feats:
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self.col2info.append((field, 0, 'NIL'))
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self.field2feats.setdefault(field, []).append(feature)
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self.col2info.append((field, len(self.field2feats[field]), feature))
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@property
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def field_sizes(self):
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return [len(self.field2feats[field]) for field in self.fields]
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cdef int attribute_to_field(unicode attribute_name):
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return LOWER_FIELDS[attribute_name]
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def get_field_id(feature):
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return FEATURE_FIELDS[feature]
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def get_field_size(field):
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return FIELD_SIZES[FIELDS[field]]
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def get_field_offset(field):
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return FIELD_OFFSETS[FIELDS[field]]
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def get_field_offset(self, field):
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n = 0
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for f in self.fields:
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if f == field:
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return n
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n += len(self.field2feats[f])
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else:
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return -1
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cdef class Morphology:
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@ -139,9 +147,11 @@ cdef class Morphology:
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self.lemmatizer = lemmatizer
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self.n_tags = len(tag_map)
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self.reverse_index = {}
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self._feat_map = MorphologyClassMap(FEATURES, FIELDS)
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for i, (tag_str, attrs) in enumerate(sorted(tag_map.items())):
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attrs = _normalize_props(attrs)
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self.add({FEATURE_NAMES[feat] for feat in attrs if feat in FEATURE_NAMES})
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self.add({self._feat_map.id2feat[feat] for feat in attrs
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if feat in self._feat_map.id2feat})
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self.tag_map[tag_str] = dict(attrs)
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self.reverse_index[self.strings.add(tag_str)] = i
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@ -167,7 +177,7 @@ cdef class Morphology:
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features = intify_features(features)
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cdef attr_t feature
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for feature in features:
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if feature != 0 and feature not in FEATURE_NAMES:
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if feature != 0 and feature not in self._feat_map.id2feat:
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raise KeyError("Unknown feature: %s" % self.strings[feature])
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cdef MorphAnalysisC tag
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tag = create_rich_tag(features)
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@ -187,7 +197,7 @@ cdef class Morphology:
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features = intify_features(features)
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cdef attr_t feature
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for feature in features:
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field = get_field_id(feature)
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field = FEATURE_FIELDS[FEATURE_NAMES[feature]]
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set_feature(&tag, field, feature, 1)
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morph = self.insert(tag)
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return morph
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@ -224,7 +234,8 @@ cdef class Morphology:
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"""
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attrs = dict(attrs)
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attrs = _normalize_props(attrs)
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self.add({FEATURE_NAMES[feat] for feat in attrs if feat in FEATURE_NAMES})
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self.add({self._feat_map.id2feat[feat] for feat in attrs
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if feat in self._feat_map.id2feat})
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attrs = intify_attrs(attrs, self.strings, _do_deprecated=True)
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self.exc[(tag_str, self.strings.add(orth_str))] = attrs
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@ -313,6 +324,10 @@ cdef class Morphology:
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def from_disk(self, path):
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raise NotImplementedError
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@classmethod
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def create_class_map(cls):
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return MorphologyClassMap(FEATURES, FIELDS)
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cpdef univ_pos_t get_int_tag(pos_):
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return <univ_pos_t>0
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@ -324,17 +339,12 @@ cdef hash_t hash_tag(MorphAnalysisC tag) nogil:
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return mrmr.hash64(&tag, sizeof(tag), 0)
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def get_feature_field(feature):
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cdef attr_t key = get_string_id(feature)
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return FEATURE_FIELDS[feature]
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cdef MorphAnalysisC create_rich_tag(features) except *:
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cdef MorphAnalysisC tag
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cdef attr_t feature
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memset(&tag, 0, sizeof(tag))
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for feature in features:
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field = get_field_id(feature)
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field = FEATURE_FIELDS[FEATURE_NAMES[feature]]
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set_feature(&tag, field, feature, 1)
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return tag
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@ -519,8 +529,7 @@ cdef attr_t get_field(const MorphAnalysisC* tag, int field_id) nogil:
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elif field == Field_VerbType:
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return tag.verb_type
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else:
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raise ValueError("Unknown feature: %s (%d)" % (FEATURE_NAMES.get(feature), feature))
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raise ValueError("Unknown field: (%d)" % field_id)
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cdef int check_feature(const MorphAnalysisC* tag, attr_t feature) nogil:
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@ -1090,22 +1099,5 @@ FEATURES = [
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"Voice_int",
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]
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FEATURE_NAMES = {get_string_id(name): name for name in FEATURES}
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FEATURE_FIELDS = {feature: FIELDS[feature.split('_', 1)[0]] for feature in FEATURES}
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FIELD_SIZES = Counter(FEATURE_FIELDS.values())
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for field in FIELD_SIZES:
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FIELD_SIZES[field] += 1
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for feat_id, name in FEATURE_NAMES.items():
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FEATURE_FIELDS[feat_id] = FEATURE_FIELDS[name]
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# Mapping of feature names to their position in total vector
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FEATURE_OFFSETS = {}
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# Mapping of field names to their first position in total vector.
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FIELD_OFFSETS = {}
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_seen_fields = Counter()
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for i, feature in enumerate(FEATURES):
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field = FEATURE_FIELDS[feature]
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# Add 1 for the NIL class, on each field
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FEATURE_OFFSETS[feature] = _seen_fields[field] + 1
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if _seen_fields[field] == 0:
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FIELD_OFFSETS[field] = i
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_seen_fields[field] += 1
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FEATURE_NAMES = {get_string_id(f): f for f in FEATURES}
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FEATURE_FIELDS = {f: FIELDS[f.split('_', 1)[0]] for f in FEATURES}
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@ -16,26 +16,24 @@ from ..compat import basestring_
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from ..tokens.doc cimport Doc
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from ..vocab cimport Vocab
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from ..morphology cimport Morphology
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from ..morphology import get_field_size, get_field_offset, parse_feature, FIELDS
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from ..morphology import FEATURES
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class Morphologizer(Pipe):
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name = 'morphologizer'
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@classmethod
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def Model(cls, attr_nums=None, **cfg):
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def Model(cls, **cfg):
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if cfg.get('pretrained_dims') and not cfg.get('pretrained_vectors'):
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raise ValueError(TempErrors.T008)
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if attr_nums is None:
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attr_nums = [get_field_size(name) for name in FIELDS]
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return build_morphologizer_model(attr_nums, **cfg)
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class_map = Morphology.create_class_map()
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return build_morphologizer_model(class_map.field_sizes, **cfg)
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def __init__(self, vocab, model=True, **cfg):
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self.vocab = vocab
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self.model = model
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self.cfg = OrderedDict(sorted(cfg.items()))
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self.cfg.setdefault('cnn_maxout_pieces', 2)
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self._class_map = self.vocab.morphology.create_class_map()
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@property
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def labels(self):
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@ -76,13 +74,13 @@ class Morphologizer(Pipe):
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docs = [docs]
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cdef Doc doc
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cdef Vocab vocab = self.vocab
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field_names = list(FIELDS)
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offsets = [get_field_offset(field) for field in field_names]
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offsets = [self._class_map.get_field_offset(field)
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for field in self._class_map.fields]
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for i, doc in enumerate(docs):
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doc_scores = batch_scores[i]
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doc_guesses = scores_to_guesses(doc_scores, self.model.softmax.out_sizes)
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# Convert the neuron indices into feature IDs.
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doc_feat_ids = numpy.zeros((len(doc), len(field_names)), dtype='i')
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doc_feat_ids = numpy.zeros((len(doc), len(self._class_map.fields)), dtype='i')
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for j in range(len(doc)):
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for k, offset in enumerate(offsets):
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if doc_guesses[j, k] == 0:
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@ -90,7 +88,8 @@ class Morphologizer(Pipe):
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else:
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doc_feat_ids[j, k] = offset + (doc_guesses[j, k]-1)
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# Get the set of feature names.
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feats = {FEATURES[f] for f in doc_feat_ids[j] if f != 0}
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feats = {self._class_map.col2info[f][2] for f in doc_feat_ids[j]
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if f != 0}
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# Now add the analysis, and set the hash.
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try:
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doc.c[j].morph = self.vocab.morphology.add(feats)
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@ -132,14 +131,15 @@ class Morphologizer(Pipe):
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if features is None:
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target[idx] = scores[idx]
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else:
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by_field = {}
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gold_fields = {}
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for feature in features:
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field, column = parse_feature(feature)
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by_field[field] = column
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field = self.get_field(feature)
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column = self.get_column(feature)
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gold_fields[field] = column
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col_offset = 0
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for field, field_size in enumerate(field_sizes):
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if field in by_field:
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target[idx, col_offset + by_field[field]] = 1.
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if field in gold_fields:
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target[idx, col_offset + gold_fields[field]] = 1.
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else:
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target[idx, col_offset] = 1.
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col_offset += field_size
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@ -3,7 +3,6 @@ from libc.string cimport memset
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from ..vocab cimport Vocab
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from ..typedefs cimport hash_t, attr_t
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from ..morphology cimport list_features, check_feature, get_field, tag_to_json
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from ..morphology cimport attribute_to_field
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from ..strings import get_string_id
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@ -53,7 +52,7 @@ cdef class MorphAnalysis:
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return self.key
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def get(self, unicode field):
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cdef int field_id = attribute_to_field(field)
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cdef int field_id = self.vocab.morphology._feat_map.attr2field[field]
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return self.vocab.strings[get_field(&self.c, field_id)]
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def to_json(self):
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