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def extract_example_features(example, config, resources):
"""Extracts feature dicts for each token in an example.
Args:
example (mindmeld.core.Query): A query.
config (ModelConfig): The ModelConfig which may contain information used for feature \
extraction.
resources (dict): Resources which may be used for this model's feature extraction.
Returns:
(list[dict]): Features.
"""
return extract_sequence_features(
example, config.example_type, config.features, resources
)
def extract_example_features(example, config, resources):
"""Extracts feature dicts for each token in an example.
Args:
example (mindmeld.core.Query): A query.
config (ModelConfig): The ModelConfig which may contain information used for feature \
extraction.
resources (dict): Resources which may be used for this model's feature extraction.
Returns:
list[dict]: Features.
"""
return extract_sequence_features(
example, config.example_type, config.features, resources
)
def _extract_features(self, example):
"""Extracts feature dicts for each token in an example.
Args:
example (mindmeld.core.Query): an query
Returns:
(list of dict): features
"""
default_gaz_one_hot = self._gaz_transform([DEFAULT_GAZ_LABEL]).tolist()[0]
extracted_gaz_tokens = [default_gaz_one_hot] * self.padding_length
extracted_sequence_features = extract_sequence_features(
example, self.example_type, self.features, self.resources
)
for index, extracted_gaz in enumerate(extracted_sequence_features):
if index >= self.padding_length:
break
if extracted_gaz == {}:
continue
combined_gaz_features = set()
for key in extracted_gaz.keys():
regex_match = re.match(GAZ_PATTERN_MATCH, key)
if regex_match:
# Examples of gaz features here are:
# in-gaz|type:city|pos:start|p_fe,