def load_trie(language_path):
trie_index2indices_values = OffsetArray.load(
join(language_path, "trie_index2indices"))
trie_index2indices_counts = OffsetArray(
np.load(join(language_path, "trie_index2indices_counts.npy")),
trie_index2indices_values.offsets)
trie = marisa_trie.Trie().load(join(language_path, "trie.marisa"))
return trie_index2indices_values, trie_index2indices_counts, trie
def fix_and_parse_tags(config, collection, size):
trie_index2indices = OffsetArray.load(join(config.language_path,
"trie_index2indices"),
compress=True)
trie_index2indices_counts = OffsetArray(
np.load(join(config.language_path, "trie_index2indices_counts.npy")),
trie_index2indices.offsets)
if exists(
join(config.language_path,
"trie_index2indices_transition_values.npy")):
trie_index2indices_transitions = OffsetArray(
np.load(
join(config.language_path,
"trie_index2indices_transition_values.npy")),
np.load(
join(config.language_path,
"trie_index2indices_transition_offsets.npy")),
)
else:
trie_index2indices_transitions = None
anchor_trie = marisa_trie.Trie().load(
join(config.language_path, "trie.marisa"))
wiki_trie = marisa_trie.RecordTrie('i').load(
join(config.wikidata, "wikititle2wikidata.marisa"))
prefix = get_prefix(config)
redirections = load_redirections(config.redirections)
docs = load_wikipedia_docs(config.wiki, size)
while True:
try:
collection.load_blacklist(join(SCRIPT_DIR, "blacklist.json"))
except (ValueError, ) as e:
print("issue reading blacklist, please fix.")
print(str(e))
enter_or_quit()
continue
break
print("Load first_names")
with open(join(PROJECT_DIR, "data", "first_names.txt"), "rt") as fin:
first_names = set(fin.read().splitlines())
all_tags = []
for doc in get_progress_bar('fixing links', item='article')(docs):
tags = obtain_tags(
doc,
wiki_trie=wiki_trie,
anchor_trie=anchor_trie,
trie_index2indices=trie_index2indices,
trie_index2indices_counts=trie_index2indices_counts,
trie_index2indices_transitions=trie_index2indices_transitions,
redirections=redirections,
prefix=prefix,
first_names=first_names,
collection=collection,
fix_destination=fix_destination,
min_count=config.min_count,
min_percent=config.min_percent)
if any(x is not None for _, x in tags):
all_tags.append(tags)
collection.reset_cache()
return all_tags
def main():
args = parse_args()
config = load_config(args.config,
["wiki", "language_path", "wikidata", "redirections"],
defaults={
"num_names_to_load": 0,
"prefix": None,
"sample_size": 100
},
relative_to=args.relative_to)
prefix = config.prefix or induce_wikipedia_prefix(config.wiki)
collection = TypeCollection(config.wikidata, num_names_to_load=0)
collection.load_blacklist(join(SCRIPT_DIR, "blacklist.json"))
trie_index2indices = OffsetArray.load(join(config.language_path,
"trie_index2indices"),
compress=True)
trie_index2indices_counts = OffsetArray(
np.load(join(config.language_path, "trie_index2indices_counts.npy")),
trie_index2indices.offsets)
if exists(
join(config.language_path,
"trie_index2indices_transition_values.npy")):
trie_index2indices_transitions = OffsetArray(
np.load(
join(config.language_path,
"trie_index2indices_transition_values.npy")),
np.load(
join(config.language_path,
"trie_index2indices_transition_offsets.npy")),
)
else:
trie_index2indices_transitions = None
anchor_trie = marisa_trie.Trie().load(
join(config.language_path, "trie.marisa"))
wiki_trie = marisa_trie.RecordTrie('i').load(
join(config.wikidata, "wikititle2wikidata.marisa"))
redirections = load_redirections(config.redirections)
seen = 0
with open(args.out, "wt") as fout:
try:
for i, (article_name,
article) in tqdm(enumerate(iterate_articles(config.wiki))):
if i == 5409:
continue
fixed_article, article_qid = convert(
article_name,
article,
collection=collection,
anchor_trie=anchor_trie,
wiki_trie=wiki_trie,
trie_index2indices=trie_index2indices,
trie_index2indices_counts=trie_index2indices_counts,
trie_index2indices_transitions=
trie_index2indices_transitions,
redirections=redirections,
prefix=prefix)
if fixed_article is False:
continue
for paragraph in fixed_article:
for word, qids in paragraph:
if len(qids) > 0:
fout.write(word.rstrip() + "\t" +
"\t".join(qids + [article_qid]) + "\n")
else:
fout.write(word.rstrip() + "\n")
fout.write("\n")
seen += 1
if seen >= config.sample_size:
break
finally:
fout.flush()
fout.close()
def main():
args = parse_args()
if args.new_language_path == args.language_path:
raise ValueError("new_language_path and language_path must be "
"different: cannot generate a fixed trie in "
"the same directory as the original trie.")
c = TypeCollection(args.wikidata, num_names_to_load=0)
c.load_blacklist(join(SCRIPT_DIR, "blacklist.json"))
original_values = np.load(
join(args.language_path, "trie_index2indices_values.npy"))
original_offsets = np.load(
join(args.language_path, "trie_index2indices_offsets.npy"))
original_counts = np.load(
join(args.language_path, "trie_index2indices_counts.npy"))
original_trie_path = join(args.language_path, 'trie.marisa')
trie = marisa_trie.Trie().load(original_trie_path)
initialize_globals(c)
t0 = time.time()
old_location_shift = None
values, offsets, counts = original_values, original_offsets, original_counts
for step in range(args.steps):
anchor_length = get_trie_properties(trie, offsets, values)
(offsets, values,
counts), location_shift = fix(collection=c,
offsets=offsets,
values=values,
counts=counts,
anchor_length=anchor_length,
num_category_link=8)
if old_location_shift is not None:
# see where newly shifted values are now pointing
# to (extra indirection level):
location_shift = location_shift[old_location_shift]
location_shift[old_location_shift == -1] = -1
old_location_shift = location_shift
pre_reduced_values = values[location_shift]
pre_reduced_values[location_shift == -1] = -1
num_changes = int((pre_reduced_values != original_values).sum())
change_volume = int(
(original_counts[pre_reduced_values != original_values].sum()))
print("step %d with %d changes, %d total links" %
(step, num_changes, change_volume))
pre_reduced_values = values[location_shift]
pre_reduced_values[location_shift == -1] = -1
t1 = time.time()
num_changes = int((pre_reduced_values != original_values).sum())
print("Done with link fixing in %.3fs, with %d changes." %
(t1 - t0, num_changes))
# show some remappings:
np.random.seed(1234)
num_samples = 10
samples = np.random.choice(np.where(
np.logical_and(
np.logical_and(pre_reduced_values != original_values,
pre_reduced_values != -1),
original_values != -1))[0],
size=num_samples,
replace=False)
print("Sample fixes:")
for index in samples:
print(" %r (%d) -> %r (%d)" %
(c.get_name(int(
original_values[index])), int(original_values[index]),
c.get_name(int(pre_reduced_values[index])),
int(pre_reduced_values[index])))
print("")
samples = np.random.choice(
np.where(OffsetArray(values, offsets).edges() == 0)[0],
size=num_samples,
replace=False)
print("Sample deletions:")
for index in samples:
print(" %r" % (trie.restore_key(int(index))))
# prune out anchors where there are no more linked items:
print("Removing empty anchors from trie...")
t0 = time.time()
non_empty_offsets = np.where(OffsetArray(values, offsets).edges() != 0)[0]
fixed_trie = filter_trie(trie, non_empty_offsets)
contexts_found = true_exists(
join(args.language_path, "trie_index2contexts_values.npy"))
if contexts_found:
contexts_values = np.load(
join(args.language_path, "trie_index2contexts_values.npy"))
contexts_offsets = np.load(
join(args.language_path, "trie_index2contexts_offsets.npy"))
contexts_counts = np.load(
join(args.language_path, "trie_index2contexts_counts.npy"))
to_port = [(offsets, values, counts),
(original_offsets, pre_reduced_values, original_values)]
if contexts_found:
to_port.append((contexts_offsets, contexts_values, contexts_counts))
ported = remap_trie_offset_array(trie, fixed_trie, to_port)
offsets, values, counts = ported[0]
original_offsets, pre_reduced_values, original_values = ported[1]
t1 = time.time()
print("Removed %d empty anchors from trie in %.3fs" % (
len(trie) - len(fixed_trie),
t1 - t0,
))
print("Saving...")
makedirs(args.new_language_path, exist_ok=True)
np.save(join(args.new_language_path, "trie_index2indices_values.npy"),
values)
np.save(join(args.new_language_path, "trie_index2indices_offsets.npy"),
offsets)
np.save(join(args.new_language_path, "trie_index2indices_counts.npy"),
counts)
if contexts_found:
contexts_offsets, contexts_values, contexts_counts = ported[2]
np.save(join(args.new_language_path, "trie_index2contexts_values.npy"),
contexts_values)
np.save(
join(args.new_language_path, "trie_index2contexts_offsets.npy"),
contexts_offsets)
np.save(join(args.new_language_path, "trie_index2contexts_counts.npy"),
contexts_counts)
new_trie_path = join(args.new_language_path, 'trie.marisa')
fixed_trie.save(new_trie_path)
transition = np.vstack([original_values, pre_reduced_values]).T
np.save(
join(args.new_language_path,
"trie_index2indices_transition_values.npy"), transition)
np.save(
join(args.new_language_path,
"trie_index2indices_transition_offsets.npy"), original_offsets)
print("Done.")