def prepare_worker_(document_path):
reader = trec_utils.TRECTextReader([document_path],
encoding=prepare_worker.encoding)
num_documents = 0
for doc_id, doc_text in reader.iter_documents(replace_digits=True,
strip_html=True):
# Values to be returned.
instances_and_labels = []
if doc_id not in prepare_worker.document_assocs:
logging.debug('Document "%s" does not exist in associations.',
doc_id)
continue
def _callback(num_yielded_windows, remaining_tokens):
if not num_yielded_windows:
logging.error('Document "%s" (%s) yielded zero instances; '
'remaining tokens: %s.',
doc_id, doc_text, remaining_tokens)
padding_token = (
'</s>' if not prepare_worker.args.no_padding else None)
# Ignore end-of-sentence.
windowed_word_stream = io_utils.windowed_translated_token_stream(
io_utils.replace_numeric_tokens_stream(
io_utils.token_stream(
io_utils.lowercased_stream(
io_utils.filter_non_latin_stream(
io_utils.filter_non_alphanumeric_stream(
iter(doc_text)))),
eos_chars=[])),
prepare_worker.args.window_size,
prepare_worker.words,
stride=prepare_worker.args.stride,
padding_token=padding_token,
callback=_callback)
# To determine the matrix indices of the entities associated with
# the document.
entity_ids = [entity_id for entity_id in
prepare_worker.document_assocs[doc_id]]
label = _candidate_centric_label(entity_ids)
partition_function = float(sum(label.values()))
for index in label:
label[index] /= partition_function
for instance in windowed_word_stream:
instances_and_labels.append((doc_id, instance, label))
prepare_worker.result_queue.put(
(doc_id, instances_and_labels, label))
num_documents += 1
return num_documents
def parse_query(unsplitted_terms):
assert isinstance(unsplitted_terms, str)
unsplitted_terms = remove_parentheses_re.sub(
r'\1', unsplitted_terms.strip())
unsplitted_terms = unsplitted_terms.replace('/', ' ')
unsplitted_terms = unsplitted_terms.replace('-', ' ')
return list(io_utils.token_stream(
io_utils.lowercased_stream(
io_utils.filter_non_latin_stream(
io_utils.filter_non_alphanumeric_stream(
iter(unsplitted_terms)))), eos_chars=[]))