# Copyright 2022 Cerebras Systems.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import logging
import os
import pickle
from glob import glob
import networkit as nk
import tqdm
[docs]def construct_graph(set_of_duplicate_pairs):
G = nk.Graph()
mapper = {}
for pair in tqdm.tqdm(set_of_duplicate_pairs):
node1_name, node2_name = pair
if node1_name not in mapper:
mapper[node1_name] = G.addNode()
if node2_name not in mapper:
mapper[node2_name] = G.addNode()
G.addEdge(mapper[node1_name], mapper[node2_name])
return G, mapper
[docs]def find_connected_components(G):
cc = nk.components.ConnectedComponents(G)
cc.run()
return cc.getComponents(), cc.numberOfComponents()
[docs]def generate_connected_components_mp(args):
files = glob(f"{args.input_dir}/*")
logging.info("Started graph building...")
# load pickled duplicate pairs
set_of_duplicate_pairs = set()
for fp in files:
with open(fp, "r") as f:
for line in tqdm.tqdm(f):
pair = tuple(line.strip().split(" :: "))
if pair[0] != pair[1]:
set_of_duplicate_pairs.add(pair)
length = len(set_of_duplicate_pairs)
logging.info(f"Length of the set of duplicates: {length}")
output_directory = os.path.dirname(args.input_dir)
pickle_file = os.path.join(output_directory, 'duplicate_pairs.pickle')
with open(pickle_file, 'wb') as file:
pickle.dump(set_of_duplicate_pairs, file)
# Generate a graph using IDs as nodes and a pair of IDs as an edge
nk.setNumberOfThreads(60)
G, mapper = construct_graph(set_of_duplicate_pairs)
components, n_components = find_connected_components(G)
logging.info(f"Number of connected components: {n_components}")
reversed_mapper = {value: key for key, value in mapper.items()}
# Dump pickled connected components on disk and load if needed
with open(args.out_file, "wb") as fout:
pickle.dump((components, n_components, reversed_mapper), fout)
logging.info("Finished generating duplicates list.")
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO)
parser = argparse.ArgumentParser()
parser.add_argument(
"--input_dir",
type=str,
help="Input directory where duplicates generated in previous step are present",
)
parser.add_argument(
"--out_file", type=str, help="Name of the output .pickle file"
)
args = parser.parse_args()
generate_connected_components_mp(args)