def index(self, vocab: Vocabulary):
if not self._skip_indexing:
self._indexed_labels = [
vocab.get_token_index(label,
self._label_namespace) # type: ignore
for label in self.labels
]
def index(self, vocab: Vocabulary):
if self._label_ids is None:
self._label_ids = [
vocab.get_token_index(label, self._label_namespace) # type: ignore
for label in self.labels
]
if not self._num_labels:
self._num_labels = vocab.get_vocab_size(self._label_namespace)
def tokens_to_indices(self, tokens: List[Token],
vocabulary: Vocabulary) -> Dict[str, List[int]]:
indices: List[int] = []
for token in itertools.chain(self._start_tokens, tokens,
self._end_tokens):
text = self._get_feature_value(token)
if self.namespace is None:
# We could have a check here that `text` is an int; not sure it's worth it.
indices.append(text) # type: ignore
else:
if self.lowercase_tokens:
text = text.lower()
indices.append(vocabulary.get_token_index(
text, self.namespace))
return {"tokens": indices}
def tokens_to_indices(
self, tokens: List[Token],
vocabulary: Vocabulary) -> Dict[str, List[List[int]]]:
indices: List[List[int]] = []
for token in itertools.chain(self._start_tokens, tokens,
self._end_tokens):
token_indices: List[int] = []
if token.text is None:
raise ConfigurationError(
"TokenCharactersIndexer needs a tokenizer that retains text"
)
for character in self._character_tokenizer.tokenize(token.text):
if getattr(character, "text_id", None) is not None:
# `text_id` being set on the token means that we aren't using the vocab, we just
# use this id instead.
index = character.text_id
else:
index = vocabulary.get_token_index(character.text,
self._namespace)
token_indices.append(index)
indices.append(token_indices)
return {"token_characters": indices}
def index(self, vocab: Vocabulary):
if self.labels is not None:
self._indexed_labels = [
vocab.get_token_index(label, self._label_namespace)
for label in self.labels
]
def index(self, vocab: Vocabulary):
if not self._skip_indexing:
self._label_id = vocab.get_token_index(
self.label, self._label_namespace # type: ignore
)
def index(self, vocab: Vocabulary):
self._mapping_array = [
vocab.get_token_index(x.ensure_text(), self._target_namespace)
for x in self._source_tokens
]