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[feat]: add build faiss index for easyrec processor (#445)
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| Original file line number | Diff line number | Diff line change |
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| # -*- encoding:utf-8 -*- | ||
| # Copyright (c) Alibaba, Inc. and its affiliates. | ||
| from __future__ import print_function | ||
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| import logging | ||
| import os | ||
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| import faiss | ||
| import numpy as np | ||
| import tensorflow as tf | ||
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| logging.basicConfig( | ||
| level=logging.INFO, format='[%(asctime)s][%(levelname)s] %(message)s') | ||
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| tf.app.flags.DEFINE_string('tables', '', 'tables passed by pai command') | ||
| tf.app.flags.DEFINE_integer('batch_size', 1024, 'batch size') | ||
| tf.app.flags.DEFINE_integer('embedding_dim', 32, 'embedding dimension') | ||
| tf.app.flags.DEFINE_string('index_output_dir', '', 'index output directory') | ||
| tf.app.flags.DEFINE_string('index_type', 'IVFFlat', 'index type') | ||
| tf.app.flags.DEFINE_integer('ivf_nlist', 1000, 'nlist') | ||
| tf.app.flags.DEFINE_integer('hnsw_M', 32, 'hnsw M') | ||
| tf.app.flags.DEFINE_integer('hnsw_efConstruction', 200, 'hnsw efConstruction') | ||
| tf.app.flags.DEFINE_integer('debug', 0, 'debug index') | ||
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| FLAGS = tf.app.flags.FLAGS | ||
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| def main(argv): | ||
| reader = tf.python_io.TableReader( | ||
| FLAGS.tables, slice_id=0, slice_count=1, capacity=FLAGS.batch_size * 2) | ||
| i = 0 | ||
| id_map_f = tf.gfile.GFile( | ||
| os.path.join(FLAGS.index_output_dir, 'id_mapping'), 'w') | ||
| embeddings = [] | ||
| while True: | ||
| try: | ||
| records = reader.read(FLAGS.batch_size) | ||
| for j, record in enumerate(records): | ||
| if isinstance(record[0], bytes): | ||
| eid = record[0].decode('utf-8') | ||
| id_map_f.write('%s\n' % eid) | ||
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| embeddings.extend( | ||
| [list(map(float, record[1].split(b','))) for record in records]) | ||
| i += 1 | ||
| if i % 100 == 0: | ||
| logging.info('read %d embeddings.' % (i * FLAGS.batch_size)) | ||
| except tf.python_io.OutOfRangeException: | ||
| break | ||
| reader.close() | ||
| id_map_f.close() | ||
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| logging.info('Building faiss index..') | ||
| if FLAGS.index_type == 'IVFFlat': | ||
| quantizer = faiss.IndexFlatIP(FLAGS.embedding_dim) | ||
| index = faiss.IndexIVFFlat(quantizer, FLAGS.embedding_dim, FLAGS.ivf_nlist, | ||
| faiss.METRIC_INNER_PRODUCT) | ||
| elif FLAGS.index_type == 'HNSWFlat': | ||
| index = faiss.IndexHNSWFlat(FLAGS.embedding_dim, FLAGS.hnsw_M, | ||
| faiss.METRIC_INNER_PRODUCT) | ||
| index.hnsw.efConstruction = FLAGS.hnsw_efConstruction | ||
| else: | ||
| raise NotImplementedError | ||
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| embeddings = np.array(embeddings) | ||
| if FLAGS.index_type == 'IVFFlat': | ||
| logging.info('train embeddings...') | ||
| index.train(embeddings) | ||
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| logging.info('build embeddings...') | ||
| index.add(embeddings) | ||
| faiss.write_index(index, 'faiss_index') | ||
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| with tf.gfile.GFile( | ||
| os.path.join(FLAGS.index_output_dir, 'faiss_index'), 'wb') as f_out: | ||
| with open('faiss_index', 'rb') as f_in: | ||
| f_out.write(f_in.read()) | ||
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| if FLAGS.debug != 0: | ||
| # IVFFlat | ||
| for ivf_nlist in [100, 500, 1000, 2000]: | ||
| quantizer = faiss.IndexFlatIP(FLAGS.embedding_dim) | ||
| index = faiss.IndexIVFFlat(quantizer, FLAGS.embedding_dim, ivf_nlist, | ||
| faiss.METRIC_INNER_PRODUCT) | ||
| index.train(embeddings) | ||
| index.add(embeddings) | ||
| index_name = 'faiss_index_ivfflat_nlist%d' % ivf_nlist | ||
| faiss.write_index(index, index_name) | ||
| with tf.gfile.GFile( | ||
| os.path.join(FLAGS.index_output_dir, index_name), 'wb') as f_out: | ||
| with open(index_name, 'rb') as f_in: | ||
| f_out.write(f_in.read()) | ||
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| # HNSWFlat | ||
| for hnsw_M in [16, 32, 64, 128]: | ||
| for hnsw_efConstruction in [64, 128, 256, 512, 1024, 2048, 4096, 8196]: | ||
| if hnsw_efConstruction < hnsw_M * 2: | ||
| continue | ||
| index = faiss.IndexHNSWFlat(FLAGS.embedding_dim, hnsw_M, | ||
| faiss.METRIC_INNER_PRODUCT) | ||
| index.hnsw.efConstruction = hnsw_efConstruction | ||
| index.add(embeddings) | ||
| index_name = 'faiss_index_hnsw_M%d_ef%d' % (hnsw_M, hnsw_efConstruction) | ||
| faiss.write_index(index, index_name) | ||
| with tf.gfile.GFile( | ||
| os.path.join(FLAGS.index_output_dir, index_name), 'wb') as f_out: | ||
| with open(index_name, 'rb') as f_in: | ||
| f_out.write(f_in.read()) | ||
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| if __name__ == '__main__': | ||
| tf.app.run() |
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