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from inputs.fields.field import Field
import logging
logger = logging.getLogger(__name__)
class MapTokenField(Field):
"""Map token field: preocess maping tokens
"""
def __init__(self, namespace, vocab_namespace, source_key, is_counting=True):
"""This function sets namesapce of field, vocab namespace for indexing, dataset source key
Arguments:
namespace {str} -- namesapce of field, counter namespace if constructing a counter
vocab_namespace {str} -- vocab namespace for indexing
source_key {str} -- indicate key in text data
Keyword Arguments:
is_counting {bool} -- decide constructing a counter or not (default: {True})
"""
super().__init__()
self.namespace = str(namespace)
self.counter_namespace = str(namespace)
self.vocab_namespace = str(vocab_namespace)
self.source_key = str(source_key)
self.is_counting = is_counting
def count_vocab_items(self, counter, sentences):
"""This function counts dict's values in sentences,
then update counter, each sentence is a dict
Arguments:
counter {dict} -- counter
sentences {list} -- text content after preprocessing, list of dict
"""
if self.is_counting:
for sentence in sentences:
for value in sentence[self.source_key].values():
counter[self.counter_namespace][str(value)] += 1
logger.info("Count sentences {} to update counter namespace {} successfully.".format(
self.source_key, self.counter_namespace))
def index(self, instance, vocab, sentences):
"""This function indexes token using vocabulary, then update instance
Arguments:
instance {dict} -- numerical represenration of text data
vocab {Vocabulary} -- vocabulary
sentences {list} -- text content after preprocessing
"""
for sentence in sentences:
instance[self.namespace].append({
key: vocab.get_token_index(value, self.vocab_namespace)
for key, value in sentence[self.source_key].items()
})
logger.info("Index sentences {} to construct instance namespace {} successfully.".format(
self.source_key, self.namespace))
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