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nuswide_WSDQH_nbits=16_adaMargin_gamma=1_lambda=0.0001_0006.log
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nuswide_WSDQH_nbits=16_adaMargin_gamma=1_lambda=0.0001_0006.log
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2022-10-19 00:08:58,908 prepare dataset.
2022-10-19 00:09:03,369 prepare data loader.
2022-10-19 00:09:03,370 Initializing DataLoader.
2022-10-19 00:09:03,372 DataLoader already.
2022-10-19 00:09:03,372 prepare model.
2022-10-19 00:09:03,555 Number of semantic embeddings: 928.
2022-10-19 00:09:11,370 From /data/wangjinpeng/anaconda3/envs/py37torch/lib/python3.7/site-packages/tensorflow_core/python/ops/math_grad.py:1424: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where.
2022-10-19 00:09:24,331 begin training.
2022-10-19 00:09:39,033 step [ 1], lr [0.0003000], embedding loss [ 0.8909], quantization loss [ 0.0000], 13.05 sec/batch.
2022-10-19 00:09:41,217 step [ 2], lr [0.0003000], embedding loss [ 0.8572], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:09:43,316 step [ 3], lr [0.0003000], embedding loss [ 0.8549], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:09:45,392 step [ 4], lr [0.0003000], embedding loss [ 0.8436], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:09:47,529 step [ 5], lr [0.0003000], embedding loss [ 0.8339], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:09:49,665 step [ 6], lr [0.0003000], embedding loss [ 0.8331], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:09:51,801 step [ 7], lr [0.0003000], embedding loss [ 0.8267], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:09:53,894 step [ 8], lr [0.0003000], embedding loss [ 0.8194], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:09:56,029 step [ 9], lr [0.0003000], embedding loss [ 0.8068], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:09:58,129 step [ 10], lr [0.0003000], embedding loss [ 0.8153], quantization loss [ 0.0000], 0.53 sec/batch.
2022-10-19 00:10:00,299 step [ 11], lr [0.0003000], embedding loss [ 0.8151], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:02,393 step [ 12], lr [0.0003000], embedding loss [ 0.8042], quantization loss [ 0.0000], 0.53 sec/batch.
2022-10-19 00:10:04,534 step [ 13], lr [0.0003000], embedding loss [ 0.8058], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:06,695 step [ 14], lr [0.0003000], embedding loss [ 0.8056], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:08,857 step [ 15], lr [0.0003000], embedding loss [ 0.8034], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:10,967 step [ 16], lr [0.0003000], embedding loss [ 0.8005], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:13,187 step [ 17], lr [0.0003000], embedding loss [ 0.7960], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:10:15,367 step [ 18], lr [0.0003000], embedding loss [ 0.7955], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:10:17,615 step [ 19], lr [0.0003000], embedding loss [ 0.7862], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:19,810 step [ 20], lr [0.0003000], embedding loss [ 0.7941], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:21,976 step [ 21], lr [0.0003000], embedding loss [ 0.7943], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:10:24,137 step [ 22], lr [0.0003000], embedding loss [ 0.7970], quantization loss [ 0.0000], 0.56 sec/batch.
2022-10-19 00:10:26,323 step [ 23], lr [0.0003000], embedding loss [ 0.7915], quantization loss [ 0.0000], 0.57 sec/batch.
2022-10-19 00:10:28,739 step [ 24], lr [0.0003000], embedding loss [ 0.7871], quantization loss [ 0.0000], 0.77 sec/batch.
2022-10-19 00:10:30,864 step [ 25], lr [0.0003000], embedding loss [ 0.7832], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:10:33,035 step [ 26], lr [0.0003000], embedding loss [ 0.7830], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:10:35,156 step [ 27], lr [0.0003000], embedding loss [ 0.7892], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:10:37,268 step [ 28], lr [0.0003000], embedding loss [ 0.7943], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:10:39,436 step [ 29], lr [0.0003000], embedding loss [ 0.7914], quantization loss [ 0.0000], 0.53 sec/batch.
2022-10-19 00:10:41,571 step [ 30], lr [0.0003000], embedding loss [ 0.7770], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:10:43,669 step [ 31], lr [0.0003000], embedding loss [ 0.7733], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:10:45,784 step [ 32], lr [0.0003000], embedding loss [ 0.7703], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:10:47,942 step [ 33], lr [0.0003000], embedding loss [ 0.7734], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:10:50,015 step [ 34], lr [0.0003000], embedding loss [ 0.7720], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:10:52,137 step [ 35], lr [0.0003000], embedding loss [ 0.7729], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:10:54,239 step [ 36], lr [0.0003000], embedding loss [ 0.7717], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:10:56,341 step [ 37], lr [0.0003000], embedding loss [ 0.7765], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:10:58,468 step [ 38], lr [0.0003000], embedding loss [ 0.7726], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:00,540 step [ 39], lr [0.0003000], embedding loss [ 0.7767], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:02,271 step [ 40], lr [0.0003000], embedding loss [ 0.7635], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:04,026 step [ 41], lr [0.0003000], embedding loss [ 0.7793], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:05,799 step [ 42], lr [0.0003000], embedding loss [ 0.7622], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:07,582 step [ 43], lr [0.0003000], embedding loss [ 0.7738], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:09,317 step [ 44], lr [0.0003000], embedding loss [ 0.7615], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:11,059 step [ 45], lr [0.0003000], embedding loss [ 0.7685], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:12,862 step [ 46], lr [0.0003000], embedding loss [ 0.7635], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:11:14,671 step [ 47], lr [0.0003000], embedding loss [ 0.7673], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:16,423 step [ 48], lr [0.0003000], embedding loss [ 0.7702], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:18,167 step [ 49], lr [0.0003000], embedding loss [ 0.7673], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:19,901 step [ 50], lr [0.0003000], embedding loss [ 0.7671], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:21,699 step [ 51], lr [0.0003000], embedding loss [ 0.7621], quantization loss [ 0.0000], 0.55 sec/batch.
2022-10-19 00:11:23,468 step [ 52], lr [0.0003000], embedding loss [ 0.7636], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:25,366 step [ 53], lr [0.0003000], embedding loss [ 0.7600], quantization loss [ 0.0000], 0.58 sec/batch.
2022-10-19 00:11:27,351 step [ 54], lr [0.0003000], embedding loss [ 0.7639], quantization loss [ 0.0000], 0.60 sec/batch.
2022-10-19 00:11:29,054 step [ 55], lr [0.0003000], embedding loss [ 0.7576], quantization loss [ 0.0000], 0.50 sec/batch.
2022-10-19 00:11:30,860 step [ 56], lr [0.0003000], embedding loss [ 0.7550], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:32,710 step [ 57], lr [0.0003000], embedding loss [ 0.7647], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:11:34,449 step [ 58], lr [0.0003000], embedding loss [ 0.7564], quantization loss [ 0.0000], 0.50 sec/batch.
2022-10-19 00:11:36,211 step [ 59], lr [0.0003000], embedding loss [ 0.7708], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:38,089 step [ 60], lr [0.0003000], embedding loss [ 0.7567], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:39,892 step [ 61], lr [0.0003000], embedding loss [ 0.7602], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:41,751 step [ 62], lr [0.0003000], embedding loss [ 0.7517], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:43,556 step [ 63], lr [0.0003000], embedding loss [ 0.7596], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:45,401 step [ 64], lr [0.0003000], embedding loss [ 0.7581], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:47,290 step [ 65], lr [0.0003000], embedding loss [ 0.7573], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:11:49,105 step [ 66], lr [0.0003000], embedding loss [ 0.7557], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:50,955 step [ 67], lr [0.0003000], embedding loss [ 0.7503], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:52,800 step [ 68], lr [0.0003000], embedding loss [ 0.7600], quantization loss [ 0.0000], 0.51 sec/batch.
2022-10-19 00:11:54,667 step [ 69], lr [0.0003000], embedding loss [ 0.7512], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:11:56,528 step [ 70], lr [0.0003000], embedding loss [ 0.7599], quantization loss [ 0.0000], 0.54 sec/batch.
2022-10-19 00:11:58,368 step [ 71], lr [0.0003000], embedding loss [ 0.7588], quantization loss [ 0.0000], 0.53 sec/batch.
2022-10-19 00:12:00,122 step [ 72], lr [0.0003000], embedding loss [ 0.7525], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:01,993 step [ 73], lr [0.0003000], embedding loss [ 0.7446], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:03,782 step [ 74], lr [0.0003000], embedding loss [ 0.7551], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:06,518 step [ 75], lr [0.0003000], embedding loss [ 0.7433], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:08,399 step [ 76], lr [0.0003000], embedding loss [ 0.7523], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:10,223 step [ 77], lr [0.0003000], embedding loss [ 0.7445], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:12,103 step [ 78], lr [0.0003000], embedding loss [ 0.7580], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:13,968 step [ 79], lr [0.0003000], embedding loss [ 0.7414], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:15,847 step [ 80], lr [0.0003000], embedding loss [ 0.7569], quantization loss [ 0.0000], 0.52 sec/batch.
2022-10-19 00:12:17,710 step [ 81], lr [0.0003000], embedding loss [ 0.7368], quantization loss [ 0.0000], 0.53 sec/batch.
2022-10-19 00:12:17,710 initialize centers iter(1/1).
2022-10-19 00:12:22,588 finish center initialization, duration: 4.88 sec.
2022-10-19 00:12:22,589 update codes and centers iter(1/1).
2022-10-19 00:12:25,003 number of update_code wrong: 0.
2022-10-19 00:12:29,082 non zero codewords: 512.
2022-10-19 00:12:29,082 finish center update, duration: 6.49 sec.
2022-10-19 00:12:30,833 step [ 82], lr [0.0003000], embedding loss [ 0.7417], quantization loss [ 0.4215], 0.52 sec/batch.
2022-10-19 00:12:32,710 step [ 83], lr [0.0003000], embedding loss [ 0.7863], quantization loss [ 1.1080], 0.53 sec/batch.
2022-10-19 00:12:34,550 step [ 84], lr [0.0003000], embedding loss [ 0.7674], quantization loss [ 0.6227], 0.52 sec/batch.
2022-10-19 00:12:36,476 step [ 85], lr [0.0003000], embedding loss [ 0.7862], quantization loss [ 1.0598], 0.54 sec/batch.
2022-10-19 00:12:38,336 step [ 86], lr [0.0003000], embedding loss [ 0.7615], quantization loss [ 0.5582], 0.52 sec/batch.
2022-10-19 00:12:40,219 step [ 87], lr [0.0003000], embedding loss [ 0.7826], quantization loss [ 0.8999], 0.52 sec/batch.
2022-10-19 00:12:42,034 step [ 88], lr [0.0003000], embedding loss [ 0.7696], quantization loss [ 0.6610], 0.52 sec/batch.
2022-10-19 00:12:43,870 step [ 89], lr [0.0003000], embedding loss [ 0.7714], quantization loss [ 0.6214], 0.53 sec/batch.
2022-10-19 00:12:45,910 step [ 90], lr [0.0003000], embedding loss [ 0.7650], quantization loss [ 0.5449], 0.59 sec/batch.
2022-10-19 00:12:48,110 step [ 91], lr [0.0003000], embedding loss [ 0.7591], quantization loss [ 0.4994], 0.56 sec/batch.
2022-10-19 00:12:50,125 step [ 92], lr [0.0003000], embedding loss [ 0.7587], quantization loss [ 0.4196], 0.57 sec/batch.
2022-10-19 00:12:52,253 step [ 93], lr [0.0003000], embedding loss [ 0.7605], quantization loss [ 0.5028], 0.59 sec/batch.
2022-10-19 00:12:54,427 step [ 94], lr [0.0003000], embedding loss [ 0.7735], quantization loss [ 0.4358], 0.59 sec/batch.
2022-10-19 00:12:56,500 step [ 95], lr [0.0003000], embedding loss [ 0.7691], quantization loss [ 0.4300], 0.60 sec/batch.
2022-10-19 00:12:58,726 step [ 96], lr [0.0003000], embedding loss [ 0.7597], quantization loss [ 0.3879], 0.55 sec/batch.
2022-10-19 00:13:00,778 step [ 97], lr [0.0003000], embedding loss [ 0.7622], quantization loss [ 0.3928], 0.55 sec/batch.
2022-10-19 00:13:02,785 step [ 98], lr [0.0003000], embedding loss [ 0.7539], quantization loss [ 0.3631], 0.61 sec/batch.
2022-10-19 00:13:04,747 step [ 99], lr [0.0003000], embedding loss [ 0.7549], quantization loss [ 0.3685], 0.56 sec/batch.
2022-10-19 00:13:06,680 step [ 100], lr [0.0003000], embedding loss [ 0.7549], quantization loss [ 0.3568], 0.55 sec/batch.
2022-10-19 00:13:08,659 step [ 101], lr [0.0003000], embedding loss [ 0.7561], quantization loss [ 0.4402], 0.56 sec/batch.
2022-10-19 00:13:10,649 step [ 102], lr [0.0003000], embedding loss [ 0.7611], quantization loss [ 0.3394], 0.55 sec/batch.
2022-10-19 00:13:12,603 step [ 103], lr [0.0003000], embedding loss [ 0.7514], quantization loss [ 0.3472], 0.54 sec/batch.
2022-10-19 00:13:14,529 step [ 104], lr [0.0003000], embedding loss [ 0.7675], quantization loss [ 0.3445], 0.55 sec/batch.
2022-10-19 00:13:16,482 step [ 105], lr [0.0003000], embedding loss [ 0.7459], quantization loss [ 0.3307], 0.56 sec/batch.
2022-10-19 00:13:18,415 step [ 106], lr [0.0003000], embedding loss [ 0.7571], quantization loss [ 0.3655], 0.55 sec/batch.
2022-10-19 00:13:20,318 step [ 107], lr [0.0003000], embedding loss [ 0.7693], quantization loss [ 0.4057], 0.55 sec/batch.
2022-10-19 00:13:22,314 step [ 108], lr [0.0003000], embedding loss [ 0.7520], quantization loss [ 0.3505], 0.57 sec/batch.
2022-10-19 00:13:24,282 step [ 109], lr [0.0003000], embedding loss [ 0.7561], quantization loss [ 0.3927], 0.58 sec/batch.
2022-10-19 00:13:26,246 step [ 110], lr [0.0003000], embedding loss [ 0.7603], quantization loss [ 0.3608], 0.57 sec/batch.
2022-10-19 00:13:28,194 step [ 111], lr [0.0003000], embedding loss [ 0.7559], quantization loss [ 0.3465], 0.57 sec/batch.
2022-10-19 00:13:30,125 step [ 112], lr [0.0003000], embedding loss [ 0.7465], quantization loss [ 0.3483], 0.55 sec/batch.
2022-10-19 00:13:32,078 step [ 113], lr [0.0003000], embedding loss [ 0.7594], quantization loss [ 0.2896], 0.56 sec/batch.
2022-10-19 00:13:33,979 step [ 114], lr [0.0003000], embedding loss [ 0.7594], quantization loss [ 0.3285], 0.56 sec/batch.
2022-10-19 00:13:35,853 step [ 115], lr [0.0003000], embedding loss [ 0.7559], quantization loss [ 0.3336], 0.55 sec/batch.
2022-10-19 00:13:37,804 step [ 116], lr [0.0003000], embedding loss [ 0.7638], quantization loss [ 0.3237], 0.57 sec/batch.
2022-10-19 00:13:39,753 step [ 117], lr [0.0003000], embedding loss [ 0.7597], quantization loss [ 0.3365], 0.56 sec/batch.
2022-10-19 00:13:41,683 step [ 118], lr [0.0003000], embedding loss [ 0.7504], quantization loss [ 0.3423], 0.56 sec/batch.
2022-10-19 00:13:43,583 step [ 119], lr [0.0003000], embedding loss [ 0.7620], quantization loss [ 0.3490], 0.55 sec/batch.
2022-10-19 00:13:45,504 step [ 120], lr [0.0003000], embedding loss [ 0.7529], quantization loss [ 0.3356], 0.55 sec/batch.
2022-10-19 00:13:47,341 step [ 121], lr [0.0003000], embedding loss [ 0.7587], quantization loss [ 0.2913], 0.55 sec/batch.
2022-10-19 00:13:49,214 step [ 122], lr [0.0003000], embedding loss [ 0.7567], quantization loss [ 0.3387], 0.55 sec/batch.
2022-10-19 00:13:51,055 step [ 123], lr [0.0003000], embedding loss [ 0.7506], quantization loss [ 0.2900], 0.55 sec/batch.
2022-10-19 00:13:53,005 step [ 124], lr [0.0003000], embedding loss [ 0.7569], quantization loss [ 0.3138], 0.56 sec/batch.
2022-10-19 00:13:54,878 step [ 125], lr [0.0003000], embedding loss [ 0.7605], quantization loss [ 0.2939], 0.55 sec/batch.
2022-10-19 00:13:56,805 step [ 126], lr [0.0003000], embedding loss [ 0.7596], quantization loss [ 0.2840], 0.56 sec/batch.
2022-10-19 00:13:58,675 step [ 127], lr [0.0003000], embedding loss [ 0.7688], quantization loss [ 0.2815], 0.55 sec/batch.
2022-10-19 00:14:00,598 step [ 128], lr [0.0003000], embedding loss [ 0.7493], quantization loss [ 0.2747], 0.56 sec/batch.
2022-10-19 00:14:02,467 step [ 129], lr [0.0003000], embedding loss [ 0.7586], quantization loss [ 0.3416], 0.55 sec/batch.
2022-10-19 00:14:04,383 step [ 130], lr [0.0003000], embedding loss [ 0.7609], quantization loss [ 0.2969], 0.56 sec/batch.
2022-10-19 00:14:06,249 step [ 131], lr [0.0003000], embedding loss [ 0.7561], quantization loss [ 0.2989], 0.55 sec/batch.
2022-10-19 00:14:08,147 step [ 132], lr [0.0003000], embedding loss [ 0.7585], quantization loss [ 0.2777], 0.56 sec/batch.
2022-10-19 00:14:10,044 step [ 133], lr [0.0003000], embedding loss [ 0.7486], quantization loss [ 0.2713], 0.55 sec/batch.
2022-10-19 00:14:11,964 step [ 134], lr [0.0003000], embedding loss [ 0.7596], quantization loss [ 0.2680], 0.56 sec/batch.
2022-10-19 00:14:13,898 step [ 135], lr [0.0003000], embedding loss [ 0.7589], quantization loss [ 0.2401], 0.56 sec/batch.
2022-10-19 00:14:15,812 step [ 136], lr [0.0003000], embedding loss [ 0.7418], quantization loss [ 0.3088], 0.55 sec/batch.
2022-10-19 00:14:17,731 step [ 137], lr [0.0003000], embedding loss [ 0.7434], quantization loss [ 0.2663], 0.55 sec/batch.
2022-10-19 00:14:19,612 step [ 138], lr [0.0003000], embedding loss [ 0.7444], quantization loss [ 0.2727], 0.55 sec/batch.
2022-10-19 00:14:21,546 step [ 139], lr [0.0003000], embedding loss [ 0.7488], quantization loss [ 0.2665], 0.56 sec/batch.
2022-10-19 00:14:23,368 step [ 140], lr [0.0003000], embedding loss [ 0.7429], quantization loss [ 0.2597], 0.55 sec/batch.
2022-10-19 00:14:25,291 step [ 141], lr [0.0003000], embedding loss [ 0.7553], quantization loss [ 0.2973], 0.55 sec/batch.
2022-10-19 00:14:27,186 step [ 142], lr [0.0003000], embedding loss [ 0.7490], quantization loss [ 0.2804], 0.55 sec/batch.
2022-10-19 00:14:29,130 step [ 143], lr [0.0003000], embedding loss [ 0.7402], quantization loss [ 0.2719], 0.56 sec/batch.
2022-10-19 00:14:31,066 step [ 144], lr [0.0003000], embedding loss [ 0.7485], quantization loss [ 0.2516], 0.56 sec/batch.
2022-10-19 00:14:33,018 step [ 145], lr [0.0003000], embedding loss [ 0.7526], quantization loss [ 0.2618], 0.56 sec/batch.
2022-10-19 00:14:34,937 step [ 146], lr [0.0003000], embedding loss [ 0.7496], quantization loss [ 0.2693], 0.55 sec/batch.
2022-10-19 00:14:36,819 step [ 147], lr [0.0003000], embedding loss [ 0.7476], quantization loss [ 0.2779], 0.54 sec/batch.
2022-10-19 00:14:38,718 step [ 148], lr [0.0003000], embedding loss [ 0.7402], quantization loss [ 0.2298], 0.55 sec/batch.
2022-10-19 00:14:40,649 step [ 149], lr [0.0003000], embedding loss [ 0.7501], quantization loss [ 0.2580], 0.56 sec/batch.
2022-10-19 00:14:42,575 step [ 150], lr [0.0003000], embedding loss [ 0.7513], quantization loss [ 0.2818], 0.55 sec/batch.
2022-10-19 00:14:44,447 step [ 151], lr [0.0003000], embedding loss [ 0.7510], quantization loss [ 0.2811], 0.54 sec/batch.
2022-10-19 00:14:46,345 step [ 152], lr [0.0003000], embedding loss [ 0.7510], quantization loss [ 0.3259], 0.54 sec/batch.
2022-10-19 00:14:48,314 step [ 153], lr [0.0003000], embedding loss [ 0.7484], quantization loss [ 0.2337], 0.56 sec/batch.
2022-10-19 00:14:50,232 step [ 154], lr [0.0003000], embedding loss [ 0.7425], quantization loss [ 0.2585], 0.55 sec/batch.
2022-10-19 00:14:52,150 step [ 155], lr [0.0003000], embedding loss [ 0.7466], quantization loss [ 0.2688], 0.56 sec/batch.
2022-10-19 00:14:54,072 step [ 156], lr [0.0003000], embedding loss [ 0.7369], quantization loss [ 0.2638], 0.55 sec/batch.
2022-10-19 00:14:55,958 step [ 157], lr [0.0003000], embedding loss [ 0.7540], quantization loss [ 0.3167], 0.53 sec/batch.
2022-10-19 00:14:57,837 step [ 158], lr [0.0003000], embedding loss [ 0.7408], quantization loss [ 0.2872], 0.55 sec/batch.
2022-10-19 00:14:59,766 step [ 159], lr [0.0003000], embedding loss [ 0.7541], quantization loss [ 0.2802], 0.58 sec/batch.
2022-10-19 00:15:01,695 step [ 160], lr [0.0003000], embedding loss [ 0.7552], quantization loss [ 0.2405], 0.55 sec/batch.
2022-10-19 00:15:03,551 step [ 161], lr [0.0003000], embedding loss [ 0.7539], quantization loss [ 0.2539], 0.53 sec/batch.
2022-10-19 00:15:03,551 update codes and centers iter(1/1).
2022-10-19 00:15:05,274 number of update_code wrong: 0.
2022-10-19 00:15:07,857 non zero codewords: 512.
2022-10-19 00:15:07,857 finish center update, duration: 4.31 sec.
2022-10-19 00:15:09,672 step [ 162], lr [0.0003000], embedding loss [ 0.7499], quantization loss [ 0.1735], 0.56 sec/batch.
2022-10-19 00:15:11,605 step [ 163], lr [0.0003000], embedding loss [ 0.7529], quantization loss [ 0.1771], 0.62 sec/batch.
2022-10-19 00:15:13,653 step [ 164], lr [0.0003000], embedding loss [ 0.7521], quantization loss [ 0.1993], 0.63 sec/batch.
2022-10-19 00:15:15,652 step [ 165], lr [0.0003000], embedding loss [ 0.7483], quantization loss [ 0.1957], 0.62 sec/batch.
2022-10-19 00:15:17,641 step [ 166], lr [0.0003000], embedding loss [ 0.7499], quantization loss [ 0.1709], 0.62 sec/batch.
2022-10-19 00:15:19,687 step [ 167], lr [0.0003000], embedding loss [ 0.7468], quantization loss [ 0.1694], 0.64 sec/batch.
2022-10-19 00:15:21,671 step [ 168], lr [0.0003000], embedding loss [ 0.7639], quantization loss [ 0.2067], 0.62 sec/batch.
2022-10-19 00:15:23,681 step [ 169], lr [0.0003000], embedding loss [ 0.7488], quantization loss [ 0.1693], 0.62 sec/batch.
2022-10-19 00:15:25,682 step [ 170], lr [0.0003000], embedding loss [ 0.7440], quantization loss [ 0.1891], 0.62 sec/batch.
2022-10-19 00:15:27,648 step [ 171], lr [0.0003000], embedding loss [ 0.7510], quantization loss [ 0.1737], 0.60 sec/batch.
2022-10-19 00:15:29,649 step [ 172], lr [0.0003000], embedding loss [ 0.7531], quantization loss [ 0.1703], 0.62 sec/batch.
2022-10-19 00:15:31,717 step [ 173], lr [0.0003000], embedding loss [ 0.7545], quantization loss [ 0.1679], 0.65 sec/batch.
2022-10-19 00:15:33,785 step [ 174], lr [0.0003000], embedding loss [ 0.7585], quantization loss [ 0.1731], 0.62 sec/batch.
2022-10-19 00:15:35,804 step [ 175], lr [0.0003000], embedding loss [ 0.7535], quantization loss [ 0.1724], 0.63 sec/batch.
2022-10-19 00:15:37,822 step [ 176], lr [0.0003000], embedding loss [ 0.7482], quantization loss [ 0.1712], 0.63 sec/batch.
2022-10-19 00:15:39,817 step [ 177], lr [0.0003000], embedding loss [ 0.7554], quantization loss [ 0.1486], 0.61 sec/batch.
2022-10-19 00:15:41,822 step [ 178], lr [0.0003000], embedding loss [ 0.7585], quantization loss [ 0.1615], 0.62 sec/batch.
2022-10-19 00:15:43,822 step [ 179], lr [0.0003000], embedding loss [ 0.7470], quantization loss [ 0.1572], 0.62 sec/batch.
2022-10-19 00:15:45,781 step [ 180], lr [0.0003000], embedding loss [ 0.7481], quantization loss [ 0.1422], 0.61 sec/batch.
2022-10-19 00:15:47,758 step [ 181], lr [0.0003000], embedding loss [ 0.7554], quantization loss [ 0.1380], 0.61 sec/batch.
2022-10-19 00:15:49,781 step [ 182], lr [0.0003000], embedding loss [ 0.7487], quantization loss [ 0.1624], 0.62 sec/batch.
2022-10-19 00:15:51,847 step [ 183], lr [0.0003000], embedding loss [ 0.7541], quantization loss [ 0.1498], 0.62 sec/batch.
2022-10-19 00:15:53,930 step [ 184], lr [0.0003000], embedding loss [ 0.7380], quantization loss [ 0.1428], 0.63 sec/batch.
2022-10-19 00:15:55,959 step [ 185], lr [0.0003000], embedding loss [ 0.7435], quantization loss [ 0.1393], 0.62 sec/batch.
2022-10-19 00:15:57,935 step [ 186], lr [0.0003000], embedding loss [ 0.7439], quantization loss [ 0.1670], 0.61 sec/batch.
2022-10-19 00:15:59,951 step [ 187], lr [0.0003000], embedding loss [ 0.7484], quantization loss [ 0.1442], 0.62 sec/batch.
2022-10-19 00:16:01,977 step [ 188], lr [0.0003000], embedding loss [ 0.7433], quantization loss [ 0.1442], 0.62 sec/batch.
2022-10-19 00:16:04,045 step [ 189], lr [0.0003000], embedding loss [ 0.7462], quantization loss [ 0.1484], 0.63 sec/batch.
2022-10-19 00:16:06,097 step [ 190], lr [0.0003000], embedding loss [ 0.7523], quantization loss [ 0.1702], 0.63 sec/batch.
2022-10-19 00:16:08,133 step [ 191], lr [0.0003000], embedding loss [ 0.7432], quantization loss [ 0.1393], 0.61 sec/batch.
2022-10-19 00:16:10,173 step [ 192], lr [0.0003000], embedding loss [ 0.7365], quantization loss [ 0.1546], 0.63 sec/batch.
2022-10-19 00:16:12,219 step [ 193], lr [0.0003000], embedding loss [ 0.7437], quantization loss [ 0.1407], 0.63 sec/batch.
2022-10-19 00:16:14,252 step [ 194], lr [0.0003000], embedding loss [ 0.7498], quantization loss [ 0.1634], 0.63 sec/batch.
2022-10-19 00:16:16,281 step [ 195], lr [0.0003000], embedding loss [ 0.7403], quantization loss [ 0.1529], 0.63 sec/batch.
2022-10-19 00:16:18,319 step [ 196], lr [0.0003000], embedding loss [ 0.7561], quantization loss [ 0.1583], 0.62 sec/batch.
2022-10-19 00:16:20,402 step [ 197], lr [0.0003000], embedding loss [ 0.7405], quantization loss [ 0.1522], 0.63 sec/batch.
2022-10-19 00:16:22,446 step [ 198], lr [0.0003000], embedding loss [ 0.7510], quantization loss [ 0.1414], 0.62 sec/batch.
2022-10-19 00:16:24,457 step [ 199], lr [0.0003000], embedding loss [ 0.7574], quantization loss [ 0.1576], 0.62 sec/batch.
2022-10-19 00:16:26,466 step [ 200], lr [0.0003000], embedding loss [ 0.7423], quantization loss [ 0.1385], 0.63 sec/batch.
2022-10-19 00:16:28,492 step [ 201], lr [0.0003000], embedding loss [ 0.7612], quantization loss [ 0.1205], 0.62 sec/batch.
2022-10-19 00:16:30,508 step [ 202], lr [0.0003000], embedding loss [ 0.7463], quantization loss [ 0.1459], 0.63 sec/batch.
2022-10-19 00:16:32,568 step [ 203], lr [0.0003000], embedding loss [ 0.7425], quantization loss [ 0.1245], 0.62 sec/batch.
2022-10-19 00:16:34,570 step [ 204], lr [0.0003000], embedding loss [ 0.7393], quantization loss [ 0.1299], 0.62 sec/batch.
2022-10-19 00:16:36,583 step [ 205], lr [0.0003000], embedding loss [ 0.7562], quantization loss [ 0.1305], 0.62 sec/batch.
2022-10-19 00:16:38,594 step [ 206], lr [0.0003000], embedding loss [ 0.7495], quantization loss [ 0.1280], 0.61 sec/batch.
2022-10-19 00:16:40,581 step [ 207], lr [0.0003000], embedding loss [ 0.7376], quantization loss [ 0.1200], 0.61 sec/batch.
2022-10-19 00:16:42,535 step [ 208], lr [0.0003000], embedding loss [ 0.7509], quantization loss [ 0.1640], 0.61 sec/batch.
2022-10-19 00:16:44,565 step [ 209], lr [0.0003000], embedding loss [ 0.7401], quantization loss [ 0.1076], 0.62 sec/batch.
2022-10-19 00:16:46,568 step [ 210], lr [0.0003000], embedding loss [ 0.7508], quantization loss [ 0.1203], 0.62 sec/batch.
2022-10-19 00:16:48,615 step [ 211], lr [0.0003000], embedding loss [ 0.7434], quantization loss [ 0.1335], 0.63 sec/batch.
2022-10-19 00:16:50,665 step [ 212], lr [0.0003000], embedding loss [ 0.7466], quantization loss [ 0.1335], 0.63 sec/batch.
2022-10-19 00:16:52,759 step [ 213], lr [0.0003000], embedding loss [ 0.7501], quantization loss [ 0.1307], 0.62 sec/batch.
2022-10-19 00:16:54,744 step [ 214], lr [0.0003000], embedding loss [ 0.7399], quantization loss [ 0.1350], 0.60 sec/batch.
2022-10-19 00:16:56,715 step [ 215], lr [0.0003000], embedding loss [ 0.7357], quantization loss [ 0.1125], 0.58 sec/batch.
2022-10-19 00:16:58,716 step [ 216], lr [0.0003000], embedding loss [ 0.7494], quantization loss [ 0.1255], 0.60 sec/batch.
2022-10-19 00:17:00,762 step [ 217], lr [0.0003000], embedding loss [ 0.7508], quantization loss [ 0.1250], 0.61 sec/batch.
2022-10-19 00:17:02,774 step [ 218], lr [0.0003000], embedding loss [ 0.7446], quantization loss [ 0.1313], 0.60 sec/batch.
2022-10-19 00:17:04,810 step [ 219], lr [0.0003000], embedding loss [ 0.7581], quantization loss [ 0.1322], 0.58 sec/batch.
2022-10-19 00:17:06,785 step [ 220], lr [0.0003000], embedding loss [ 0.7491], quantization loss [ 0.1290], 0.59 sec/batch.
2022-10-19 00:17:08,770 step [ 221], lr [0.0003000], embedding loss [ 0.7494], quantization loss [ 0.1216], 0.59 sec/batch.
2022-10-19 00:17:10,708 step [ 222], lr [0.0003000], embedding loss [ 0.7559], quantization loss [ 0.1251], 0.58 sec/batch.
2022-10-19 00:17:12,738 step [ 223], lr [0.0003000], embedding loss [ 0.7462], quantization loss [ 0.1264], 0.60 sec/batch.
2022-10-19 00:17:14,717 step [ 224], lr [0.0003000], embedding loss [ 0.7490], quantization loss [ 0.1371], 0.60 sec/batch.
2022-10-19 00:17:16,752 step [ 225], lr [0.0003000], embedding loss [ 0.7473], quantization loss [ 0.1281], 0.60 sec/batch.
2022-10-19 00:17:18,768 step [ 226], lr [0.0003000], embedding loss [ 0.7505], quantization loss [ 0.1333], 0.61 sec/batch.
2022-10-19 00:17:20,797 step [ 227], lr [0.0003000], embedding loss [ 0.7393], quantization loss [ 0.1365], 0.61 sec/batch.
2022-10-19 00:17:22,772 step [ 228], lr [0.0003000], embedding loss [ 0.7427], quantization loss [ 0.1337], 0.59 sec/batch.
2022-10-19 00:17:24,797 step [ 229], lr [0.0003000], embedding loss [ 0.7489], quantization loss [ 0.1292], 0.60 sec/batch.
2022-10-19 00:17:26,796 step [ 230], lr [0.0003000], embedding loss [ 0.7403], quantization loss [ 0.1351], 0.60 sec/batch.
2022-10-19 00:17:28,797 step [ 231], lr [0.0003000], embedding loss [ 0.7427], quantization loss [ 0.1206], 0.60 sec/batch.
2022-10-19 00:17:30,792 step [ 232], lr [0.0003000], embedding loss [ 0.7524], quantization loss [ 0.1167], 0.61 sec/batch.
2022-10-19 00:17:32,789 step [ 233], lr [0.0003000], embedding loss [ 0.7506], quantization loss [ 0.1358], 0.60 sec/batch.
2022-10-19 00:17:34,797 step [ 234], lr [0.0003000], embedding loss [ 0.7392], quantization loss [ 0.1285], 0.61 sec/batch.
2022-10-19 00:17:36,790 step [ 235], lr [0.0003000], embedding loss [ 0.7546], quantization loss [ 0.1427], 0.59 sec/batch.
2022-10-19 00:17:38,803 step [ 236], lr [0.0003000], embedding loss [ 0.7570], quantization loss [ 0.1245], 0.60 sec/batch.
2022-10-19 00:17:40,798 step [ 237], lr [0.0003000], embedding loss [ 0.7438], quantization loss [ 0.1291], 0.59 sec/batch.
2022-10-19 00:17:42,790 step [ 238], lr [0.0003000], embedding loss [ 0.7539], quantization loss [ 0.1314], 0.59 sec/batch.
2022-10-19 00:17:44,783 step [ 239], lr [0.0003000], embedding loss [ 0.7449], quantization loss [ 0.1243], 0.59 sec/batch.
2022-10-19 00:17:46,763 step [ 240], lr [0.0003000], embedding loss [ 0.7366], quantization loss [ 0.1159], 0.59 sec/batch.
2022-10-19 00:17:48,769 step [ 241], lr [0.0003000], embedding loss [ 0.7498], quantization loss [ 0.1101], 0.60 sec/batch.
2022-10-19 00:17:48,769 update codes and centers iter(1/1).
2022-10-19 00:17:50,688 number of update_code wrong: 0.
2022-10-19 00:17:53,652 non zero codewords: 512.
2022-10-19 00:17:53,652 finish center update, duration: 4.88 sec.
2022-10-19 00:17:55,597 step [ 242], lr [0.0003000], embedding loss [ 0.7480], quantization loss [ 0.0937], 0.59 sec/batch.
2022-10-19 00:17:57,581 step [ 243], lr [0.0003000], embedding loss [ 0.7492], quantization loss [ 0.1213], 0.59 sec/batch.
2022-10-19 00:17:59,600 step [ 244], lr [0.0003000], embedding loss [ 0.7383], quantization loss [ 0.1009], 0.62 sec/batch.
2022-10-19 00:18:01,648 step [ 245], lr [0.0003000], embedding loss [ 0.7450], quantization loss [ 0.1041], 0.61 sec/batch.
2022-10-19 00:18:03,703 step [ 246], lr [0.0003000], embedding loss [ 0.7493], quantization loss [ 0.0993], 0.61 sec/batch.
2022-10-19 00:18:05,823 step [ 247], lr [0.0003000], embedding loss [ 0.7549], quantization loss [ 0.1063], 0.62 sec/batch.
2022-10-19 00:18:07,888 step [ 248], lr [0.0003000], embedding loss [ 0.7488], quantization loss [ 0.1011], 0.61 sec/batch.
2022-10-19 00:18:09,916 step [ 249], lr [0.0003000], embedding loss [ 0.7472], quantization loss [ 0.0968], 0.61 sec/batch.
2022-10-19 00:18:11,937 step [ 250], lr [0.0003000], embedding loss [ 0.7403], quantization loss [ 0.0971], 0.60 sec/batch.
2022-10-19 00:18:14,001 step [ 251], lr [0.0003000], embedding loss [ 0.7623], quantization loss [ 0.1142], 0.61 sec/batch.
2022-10-19 00:18:16,059 step [ 252], lr [0.0003000], embedding loss [ 0.7409], quantization loss [ 0.1093], 0.61 sec/batch.
2022-10-19 00:18:18,081 step [ 253], lr [0.0003000], embedding loss [ 0.7606], quantization loss [ 0.1030], 0.60 sec/batch.
2022-10-19 00:18:20,102 step [ 254], lr [0.0003000], embedding loss [ 0.7483], quantization loss [ 0.1034], 0.60 sec/batch.
2022-10-19 00:18:22,117 step [ 255], lr [0.0003000], embedding loss [ 0.7542], quantization loss [ 0.1054], 0.60 sec/batch.
2022-10-19 00:18:24,121 step [ 256], lr [0.0003000], embedding loss [ 0.7424], quantization loss [ 0.1103], 0.60 sec/batch.
2022-10-19 00:18:26,133 step [ 257], lr [0.0003000], embedding loss [ 0.7559], quantization loss [ 0.1088], 0.60 sec/batch.
2022-10-19 00:18:28,011 step [ 258], lr [0.0003000], embedding loss [ 0.7527], quantization loss [ 0.0918], 0.60 sec/batch.
2022-10-19 00:18:30,042 step [ 259], lr [0.0003000], embedding loss [ 0.7514], quantization loss [ 0.1011], 0.60 sec/batch.
2022-10-19 00:18:32,089 step [ 260], lr [0.0003000], embedding loss [ 0.7341], quantization loss [ 0.0984], 0.61 sec/batch.
2022-10-19 00:18:34,097 step [ 261], lr [0.0003000], embedding loss [ 0.7468], quantization loss [ 0.1138], 0.61 sec/batch.
2022-10-19 00:18:36,113 step [ 262], lr [0.0003000], embedding loss [ 0.7289], quantization loss [ 0.0972], 0.61 sec/batch.
2022-10-19 00:18:38,160 step [ 263], lr [0.0003000], embedding loss [ 0.7429], quantization loss [ 0.0945], 0.61 sec/batch.
2022-10-19 00:18:40,143 step [ 264], lr [0.0003000], embedding loss [ 0.7482], quantization loss [ 0.1152], 0.58 sec/batch.
2022-10-19 00:18:42,104 step [ 265], lr [0.0003000], embedding loss [ 0.7390], quantization loss [ 0.1123], 0.58 sec/batch.
2022-10-19 00:18:44,071 step [ 266], lr [0.0003000], embedding loss [ 0.7471], quantization loss [ 0.1110], 0.59 sec/batch.
2022-10-19 00:18:46,031 step [ 267], lr [0.0003000], embedding loss [ 0.7346], quantization loss [ 0.1159], 0.58 sec/batch.
2022-10-19 00:18:48,016 step [ 268], lr [0.0003000], embedding loss [ 0.7474], quantization loss [ 0.0940], 0.59 sec/batch.
2022-10-19 00:18:49,998 step [ 269], lr [0.0003000], embedding loss [ 0.7513], quantization loss [ 0.1057], 0.59 sec/batch.
2022-10-19 00:18:51,967 step [ 270], lr [0.0003000], embedding loss [ 0.7385], quantization loss [ 0.0987], 0.57 sec/batch.
2022-10-19 00:18:54,003 step [ 271], lr [0.0003000], embedding loss [ 0.7367], quantization loss [ 0.0966], 0.58 sec/batch.
2022-10-19 00:18:55,978 step [ 272], lr [0.0003000], embedding loss [ 0.7526], quantization loss [ 0.0995], 0.57 sec/batch.
2022-10-19 00:18:58,010 step [ 273], lr [0.0003000], embedding loss [ 0.7528], quantization loss [ 0.0914], 0.59 sec/batch.
2022-10-19 00:19:00,017 step [ 274], lr [0.0003000], embedding loss [ 0.7443], quantization loss [ 0.0969], 0.60 sec/batch.
2022-10-19 00:19:02,060 step [ 275], lr [0.0003000], embedding loss [ 0.7452], quantization loss [ 0.0888], 0.60 sec/batch.
2022-10-19 00:19:04,086 step [ 276], lr [0.0003000], embedding loss [ 0.7525], quantization loss [ 0.0968], 0.60 sec/batch.
2022-10-19 00:19:06,101 step [ 277], lr [0.0003000], embedding loss [ 0.7312], quantization loss [ 0.0941], 0.60 sec/batch.
2022-10-19 00:19:08,156 step [ 278], lr [0.0003000], embedding loss [ 0.7397], quantization loss [ 0.1007], 0.60 sec/batch.
2022-10-19 00:19:10,162 step [ 279], lr [0.0003000], embedding loss [ 0.7462], quantization loss [ 0.0927], 0.60 sec/batch.
2022-10-19 00:19:12,176 step [ 280], lr [0.0003000], embedding loss [ 0.7430], quantization loss [ 0.1015], 0.61 sec/batch.
2022-10-19 00:19:14,157 step [ 281], lr [0.0003000], embedding loss [ 0.7460], quantization loss [ 0.1123], 0.59 sec/batch.
2022-10-19 00:19:16,164 step [ 282], lr [0.0003000], embedding loss [ 0.7311], quantization loss [ 0.0907], 0.60 sec/batch.
2022-10-19 00:19:18,172 step [ 283], lr [0.0003000], embedding loss [ 0.7463], quantization loss [ 0.0815], 0.60 sec/batch.
2022-10-19 00:19:20,214 step [ 284], lr [0.0003000], embedding loss [ 0.7446], quantization loss [ 0.0896], 0.60 sec/batch.
2022-10-19 00:19:22,203 step [ 285], lr [0.0003000], embedding loss [ 0.7494], quantization loss [ 0.0908], 0.56 sec/batch.
2022-10-19 00:19:24,218 step [ 286], lr [0.0003000], embedding loss [ 0.7435], quantization loss [ 0.0897], 0.58 sec/batch.
2022-10-19 00:19:26,191 step [ 287], lr [0.0003000], embedding loss [ 0.7597], quantization loss [ 0.0962], 0.57 sec/batch.
2022-10-19 00:19:28,191 step [ 288], lr [0.0003000], embedding loss [ 0.7484], quantization loss [ 0.0892], 0.57 sec/batch.
2022-10-19 00:19:30,176 step [ 289], lr [0.0003000], embedding loss [ 0.7518], quantization loss [ 0.0908], 0.58 sec/batch.
2022-10-19 00:19:32,095 step [ 290], lr [0.0003000], embedding loss [ 0.7485], quantization loss [ 0.0920], 0.57 sec/batch.
2022-10-19 00:19:34,067 step [ 291], lr [0.0003000], embedding loss [ 0.7479], quantization loss [ 0.0829], 0.57 sec/batch.
2022-10-19 00:19:36,024 step [ 292], lr [0.0003000], embedding loss [ 0.7458], quantization loss [ 0.0856], 0.58 sec/batch.
2022-10-19 00:19:37,995 step [ 293], lr [0.0003000], embedding loss [ 0.7493], quantization loss [ 0.0844], 0.57 sec/batch.
2022-10-19 00:19:39,975 step [ 294], lr [0.0003000], embedding loss [ 0.7440], quantization loss [ 0.0852], 0.58 sec/batch.
2022-10-19 00:19:41,998 step [ 295], lr [0.0003000], embedding loss [ 0.7400], quantization loss [ 0.0858], 0.60 sec/batch.
2022-10-19 00:19:44,004 step [ 296], lr [0.0003000], embedding loss [ 0.7397], quantization loss [ 0.0793], 0.60 sec/batch.
2022-10-19 00:19:46,000 step [ 297], lr [0.0003000], embedding loss [ 0.7525], quantization loss [ 0.0941], 0.60 sec/batch.
2022-10-19 00:19:47,996 step [ 298], lr [0.0003000], embedding loss [ 0.7505], quantization loss [ 0.0863], 0.61 sec/batch.
2022-10-19 00:19:50,009 step [ 299], lr [0.0003000], embedding loss [ 0.7367], quantization loss [ 0.0843], 0.60 sec/batch.
2022-10-19 00:19:52,014 step [ 300], lr [0.0003000], embedding loss [ 0.7401], quantization loss [ 0.0842], 0.59 sec/batch.
2022-10-19 00:19:54,030 step [ 301], lr [0.0001500], embedding loss [ 0.7324], quantization loss [ 0.0931], 0.60 sec/batch.
2022-10-19 00:19:56,049 step [ 302], lr [0.0001500], embedding loss [ 0.7430], quantization loss [ 0.0840], 0.60 sec/batch.
2022-10-19 00:19:58,039 step [ 303], lr [0.0001500], embedding loss [ 0.7509], quantization loss [ 0.1033], 0.60 sec/batch.
2022-10-19 00:20:00,059 step [ 304], lr [0.0001500], embedding loss [ 0.7386], quantization loss [ 0.0891], 0.60 sec/batch.
2022-10-19 00:20:02,074 step [ 305], lr [0.0001500], embedding loss [ 0.7354], quantization loss [ 0.0853], 0.60 sec/batch.
2022-10-19 00:20:04,096 step [ 306], lr [0.0001500], embedding loss [ 0.7458], quantization loss [ 0.0894], 0.61 sec/batch.
2022-10-19 00:20:06,119 step [ 307], lr [0.0001500], embedding loss [ 0.7425], quantization loss [ 0.0877], 0.60 sec/batch.
2022-10-19 00:20:08,142 step [ 308], lr [0.0001500], embedding loss [ 0.7385], quantization loss [ 0.0767], 0.60 sec/batch.
2022-10-19 00:20:10,166 step [ 309], lr [0.0001500], embedding loss [ 0.7469], quantization loss [ 0.0909], 0.61 sec/batch.
2022-10-19 00:20:12,217 step [ 310], lr [0.0001500], embedding loss [ 0.7486], quantization loss [ 0.0758], 0.60 sec/batch.
2022-10-19 00:20:14,269 step [ 311], lr [0.0001500], embedding loss [ 0.7466], quantization loss [ 0.0795], 0.60 sec/batch.
2022-10-19 00:20:16,286 step [ 312], lr [0.0001500], embedding loss [ 0.7458], quantization loss [ 0.0898], 0.61 sec/batch.
2022-10-19 00:20:18,294 step [ 313], lr [0.0001500], embedding loss [ 0.7434], quantization loss [ 0.0862], 0.60 sec/batch.
2022-10-19 00:20:20,332 step [ 314], lr [0.0001500], embedding loss [ 0.7444], quantization loss [ 0.0844], 0.59 sec/batch.
2022-10-19 00:20:22,343 step [ 315], lr [0.0001500], embedding loss [ 0.7411], quantization loss [ 0.0816], 0.60 sec/batch.
2022-10-19 00:20:24,354 step [ 316], lr [0.0001500], embedding loss [ 0.7547], quantization loss [ 0.0967], 0.60 sec/batch.
2022-10-19 00:20:26,316 step [ 317], lr [0.0001500], embedding loss [ 0.7504], quantization loss [ 0.0812], 0.59 sec/batch.
2022-10-19 00:20:28,329 step [ 318], lr [0.0001500], embedding loss [ 0.7409], quantization loss [ 0.0846], 0.60 sec/batch.
2022-10-19 00:20:30,353 step [ 319], lr [0.0001500], embedding loss [ 0.7464], quantization loss [ 0.0859], 0.61 sec/batch.
2022-10-19 00:20:32,398 step [ 320], lr [0.0001500], embedding loss [ 0.7425], quantization loss [ 0.0796], 0.60 sec/batch.
2022-10-19 00:20:34,421 step [ 321], lr [0.0001500], embedding loss [ 0.7390], quantization loss [ 0.0760], 0.60 sec/batch.
2022-10-19 00:20:34,421 update codes and centers iter(1/1).
2022-10-19 00:20:36,390 number of update_code wrong: 0.
2022-10-19 00:20:39,066 non zero codewords: 512.
2022-10-19 00:20:39,067 finish center update, duration: 4.65 sec.
2022-10-19 00:20:40,961 step [ 322], lr [0.0001500], embedding loss [ 0.7453], quantization loss [ 0.0799], 0.60 sec/batch.
2022-10-19 00:20:42,986 step [ 323], lr [0.0001500], embedding loss [ 0.7355], quantization loss [ 0.0765], 0.60 sec/batch.
2022-10-19 00:20:45,062 step [ 324], lr [0.0001500], embedding loss [ 0.7471], quantization loss [ 0.0737], 0.64 sec/batch.
2022-10-19 00:20:47,141 step [ 325], lr [0.0001500], embedding loss [ 0.7354], quantization loss [ 0.0718], 0.63 sec/batch.
2022-10-19 00:20:49,102 step [ 326], lr [0.0001500], embedding loss [ 0.7436], quantization loss [ 0.0742], 0.62 sec/batch.
2022-10-19 00:20:51,180 step [ 327], lr [0.0001500], embedding loss [ 0.7485], quantization loss [ 0.0818], 0.65 sec/batch.
2022-10-19 00:20:53,238 step [ 328], lr [0.0001500], embedding loss [ 0.7208], quantization loss [ 0.0842], 0.63 sec/batch.
2022-10-19 00:20:55,300 step [ 329], lr [0.0001500], embedding loss [ 0.7459], quantization loss [ 0.0773], 0.63 sec/batch.
2022-10-19 00:20:57,366 step [ 330], lr [0.0001500], embedding loss [ 0.7563], quantization loss [ 0.0797], 0.63 sec/batch.
2022-10-19 00:20:59,404 step [ 331], lr [0.0001500], embedding loss [ 0.7554], quantization loss [ 0.0870], 0.64 sec/batch.
2022-10-19 00:21:01,514 step [ 332], lr [0.0001500], embedding loss [ 0.7412], quantization loss [ 0.0771], 0.69 sec/batch.
2022-10-19 00:21:03,574 step [ 333], lr [0.0001500], embedding loss [ 0.7363], quantization loss [ 0.0739], 0.64 sec/batch.
2022-10-19 00:21:05,734 step [ 334], lr [0.0001500], embedding loss [ 0.7465], quantization loss [ 0.0793], 0.64 sec/batch.
2022-10-19 00:21:07,785 step [ 335], lr [0.0001500], embedding loss [ 0.7352], quantization loss [ 0.0799], 0.63 sec/batch.
2022-10-19 00:21:09,829 step [ 336], lr [0.0001500], embedding loss [ 0.7447], quantization loss [ 0.0737], 0.64 sec/batch.
2022-10-19 00:21:11,865 step [ 337], lr [0.0001500], embedding loss [ 0.7446], quantization loss [ 0.0702], 0.62 sec/batch.
2022-10-19 00:21:13,851 step [ 338], lr [0.0001500], embedding loss [ 0.7553], quantization loss [ 0.0740], 0.56 sec/batch.
2022-10-19 00:21:15,971 step [ 339], lr [0.0001500], embedding loss [ 0.7486], quantization loss [ 0.0766], 0.57 sec/batch.
2022-10-19 00:21:17,955 step [ 340], lr [0.0001500], embedding loss [ 0.7352], quantization loss [ 0.0636], 0.57 sec/batch.
2022-10-19 00:21:19,982 step [ 341], lr [0.0001500], embedding loss [ 0.7382], quantization loss [ 0.0739], 0.56 sec/batch.
2022-10-19 00:21:21,923 step [ 342], lr [0.0001500], embedding loss [ 0.7448], quantization loss [ 0.0677], 0.57 sec/batch.
2022-10-19 00:21:23,806 step [ 343], lr [0.0001500], embedding loss [ 0.7334], quantization loss [ 0.0762], 0.55 sec/batch.
2022-10-19 00:21:25,767 step [ 344], lr [0.0001500], embedding loss [ 0.7449], quantization loss [ 0.0750], 0.57 sec/batch.
2022-10-19 00:21:27,683 step [ 345], lr [0.0001500], embedding loss [ 0.7448], quantization loss [ 0.0927], 0.56 sec/batch.
2022-10-19 00:21:29,576 step [ 346], lr [0.0001500], embedding loss [ 0.7421], quantization loss [ 0.0724], 0.53 sec/batch.
2022-10-19 00:21:31,485 step [ 347], lr [0.0001500], embedding loss [ 0.7454], quantization loss [ 0.0865], 0.53 sec/batch.
2022-10-19 00:21:33,558 step [ 348], lr [0.0001500], embedding loss [ 0.7355], quantization loss [ 0.0712], 0.66 sec/batch.
2022-10-19 00:21:35,601 step [ 349], lr [0.0001500], embedding loss [ 0.7606], quantization loss [ 0.0745], 0.63 sec/batch.
2022-10-19 00:21:37,666 step [ 350], lr [0.0001500], embedding loss [ 0.7457], quantization loss [ 0.0702], 0.63 sec/batch.
2022-10-19 00:21:39,838 step [ 351], lr [0.0001500], embedding loss [ 0.7494], quantization loss [ 0.0630], 0.65 sec/batch.
2022-10-19 00:21:41,916 step [ 352], lr [0.0001500], embedding loss [ 0.7441], quantization loss [ 0.0734], 0.64 sec/batch.
2022-10-19 00:21:43,995 step [ 353], lr [0.0001500], embedding loss [ 0.7424], quantization loss [ 0.0758], 0.63 sec/batch.
2022-10-19 00:21:46,063 step [ 354], lr [0.0001500], embedding loss [ 0.7287], quantization loss [ 0.0711], 0.64 sec/batch.
2022-10-19 00:21:48,159 step [ 355], lr [0.0001500], embedding loss [ 0.7490], quantization loss [ 0.0750], 0.64 sec/batch.
2022-10-19 00:21:50,302 step [ 356], lr [0.0001500], embedding loss [ 0.7442], quantization loss [ 0.0742], 0.64 sec/batch.
2022-10-19 00:21:52,340 step [ 357], lr [0.0001500], embedding loss [ 0.7460], quantization loss [ 0.0682], 0.62 sec/batch.
2022-10-19 00:21:54,417 step [ 358], lr [0.0001500], embedding loss [ 0.7472], quantization loss [ 0.0662], 0.64 sec/batch.
2022-10-19 00:21:56,490 step [ 359], lr [0.0001500], embedding loss [ 0.7370], quantization loss [ 0.0703], 0.63 sec/batch.
2022-10-19 00:21:58,536 step [ 360], lr [0.0001500], embedding loss [ 0.7429], quantization loss [ 0.0686], 0.64 sec/batch.
2022-10-19 00:22:00,575 step [ 361], lr [0.0001500], embedding loss [ 0.7488], quantization loss [ 0.0718], 0.63 sec/batch.
2022-10-19 00:22:02,659 step [ 362], lr [0.0001500], embedding loss [ 0.7389], quantization loss [ 0.0620], 0.64 sec/batch.
2022-10-19 00:22:04,739 step [ 363], lr [0.0001500], embedding loss [ 0.7448], quantization loss [ 0.0599], 0.63 sec/batch.
2022-10-19 00:22:06,834 step [ 364], lr [0.0001500], embedding loss [ 0.7507], quantization loss [ 0.0635], 0.64 sec/batch.
2022-10-19 00:22:08,888 step [ 365], lr [0.0001500], embedding loss [ 0.7608], quantization loss [ 0.0656], 0.61 sec/batch.
2022-10-19 00:22:10,935 step [ 366], lr [0.0001500], embedding loss [ 0.7441], quantization loss [ 0.0732], 0.64 sec/batch.
2022-10-19 00:22:13,087 step [ 367], lr [0.0001500], embedding loss [ 0.7509], quantization loss [ 0.0748], 0.64 sec/batch.
2022-10-19 00:22:15,136 step [ 368], lr [0.0001500], embedding loss [ 0.7521], quantization loss [ 0.0691], 0.64 sec/batch.
2022-10-19 00:22:17,204 step [ 369], lr [0.0001500], embedding loss [ 0.7431], quantization loss [ 0.0652], 0.64 sec/batch.
2022-10-19 00:22:19,193 step [ 370], lr [0.0001500], embedding loss [ 0.7417], quantization loss [ 0.0724], 0.63 sec/batch.
2022-10-19 00:22:21,282 step [ 371], lr [0.0001500], embedding loss [ 0.7456], quantization loss [ 0.0728], 0.64 sec/batch.
2022-10-19 00:22:23,393 step [ 372], lr [0.0001500], embedding loss [ 0.7273], quantization loss [ 0.0667], 0.66 sec/batch.
2022-10-19 00:22:25,505 step [ 373], lr [0.0001500], embedding loss [ 0.7433], quantization loss [ 0.0666], 0.64 sec/batch.
2022-10-19 00:22:27,589 step [ 374], lr [0.0001500], embedding loss [ 0.7352], quantization loss [ 0.0637], 0.64 sec/batch.
2022-10-19 00:22:29,683 step [ 375], lr [0.0001500], embedding loss [ 0.7370], quantization loss [ 0.0670], 0.64 sec/batch.
2022-10-19 00:22:31,691 step [ 376], lr [0.0001500], embedding loss [ 0.7343], quantization loss [ 0.0730], 0.63 sec/batch.
2022-10-19 00:22:33,653 step [ 377], lr [0.0001500], embedding loss [ 0.7388], quantization loss [ 0.0740], 0.56 sec/batch.
2022-10-19 00:22:35,704 step [ 378], lr [0.0001500], embedding loss [ 0.7376], quantization loss [ 0.0663], 0.56 sec/batch.
2022-10-19 00:22:37,689 step [ 379], lr [0.0001500], embedding loss [ 0.7402], quantization loss [ 0.0581], 0.54 sec/batch.
2022-10-19 00:22:39,777 step [ 380], lr [0.0001500], embedding loss [ 0.7478], quantization loss [ 0.0654], 0.56 sec/batch.
2022-10-19 00:22:41,800 step [ 381], lr [0.0001500], embedding loss [ 0.7431], quantization loss [ 0.0662], 0.56 sec/batch.
2022-10-19 00:22:43,759 step [ 382], lr [0.0001500], embedding loss [ 0.7494], quantization loss [ 0.0639], 0.55 sec/batch.
2022-10-19 00:22:45,718 step [ 383], lr [0.0001500], embedding loss [ 0.7476], quantization loss [ 0.0705], 0.55 sec/batch.
2022-10-19 00:22:47,675 step [ 384], lr [0.0001500], embedding loss [ 0.7520], quantization loss [ 0.0635], 0.55 sec/batch.
2022-10-19 00:22:49,641 step [ 385], lr [0.0001500], embedding loss [ 0.7464], quantization loss [ 0.0618], 0.56 sec/batch.
2022-10-19 00:22:51,602 step [ 386], lr [0.0001500], embedding loss [ 0.7465], quantization loss [ 0.0639], 0.55 sec/batch.
2022-10-19 00:22:53,788 step [ 387], lr [0.0001500], embedding loss [ 0.7405], quantization loss [ 0.0678], 0.54 sec/batch.
2022-10-19 00:22:55,747 step [ 388], lr [0.0001500], embedding loss [ 0.7374], quantization loss [ 0.0664], 0.56 sec/batch.
2022-10-19 00:22:57,716 step [ 389], lr [0.0001500], embedding loss [ 0.7396], quantization loss [ 0.0725], 0.56 sec/batch.
2022-10-19 00:22:59,661 step [ 390], lr [0.0001500], embedding loss [ 0.7473], quantization loss [ 0.0661], 0.54 sec/batch.
2022-10-19 00:23:01,652 step [ 391], lr [0.0001500], embedding loss [ 0.7330], quantization loss [ 0.0725], 0.57 sec/batch.
2022-10-19 00:23:03,652 step [ 392], lr [0.0001500], embedding loss [ 0.7446], quantization loss [ 0.0672], 0.56 sec/batch.
2022-10-19 00:23:05,675 step [ 393], lr [0.0001500], embedding loss [ 0.7394], quantization loss [ 0.0629], 0.55 sec/batch.
2022-10-19 00:23:07,716 step [ 394], lr [0.0001500], embedding loss [ 0.7524], quantization loss [ 0.0618], 0.57 sec/batch.
2022-10-19 00:23:09,751 step [ 395], lr [0.0001500], embedding loss [ 0.7308], quantization loss [ 0.0684], 0.56 sec/batch.
2022-10-19 00:23:11,677 step [ 396], lr [0.0001500], embedding loss [ 0.7401], quantization loss [ 0.0660], 0.55 sec/batch.
2022-10-19 00:23:13,671 step [ 397], lr [0.0001500], embedding loss [ 0.7453], quantization loss [ 0.0742], 0.56 sec/batch.
2022-10-19 00:23:15,556 step [ 398], lr [0.0001500], embedding loss [ 0.7329], quantization loss [ 0.0699], 0.55 sec/batch.
2022-10-19 00:23:17,495 step [ 399], lr [0.0001500], embedding loss [ 0.7334], quantization loss [ 0.0715], 0.56 sec/batch.
2022-10-19 00:23:19,394 step [ 400], lr [0.0001500], embedding loss [ 0.7554], quantization loss [ 0.0635], 0.55 sec/batch.
2022-10-19 00:23:21,382 step [ 401], lr [0.0001500], embedding loss [ 0.7426], quantization loss [ 0.0561], 0.56 sec/batch.
2022-10-19 00:23:21,382 update codes and centers iter(1/1).
2022-10-19 00:23:23,150 number of update_code wrong: 0.
2022-10-19 00:23:26,218 non zero codewords: 512.
2022-10-19 00:23:26,219 finish center update, duration: 4.84 sec.
2022-10-19 00:23:28,421 step [ 402], lr [0.0001500], embedding loss [ 0.7399], quantization loss [ 0.0605], 0.78 sec/batch.
2022-10-19 00:23:30,384 step [ 403], lr [0.0001500], embedding loss [ 0.7308], quantization loss [ 0.0548], 0.52 sec/batch.
2022-10-19 00:23:32,372 step [ 404], lr [0.0001500], embedding loss [ 0.7290], quantization loss [ 0.0626], 0.51 sec/batch.
2022-10-19 00:23:34,338 step [ 405], lr [0.0001500], embedding loss [ 0.7503], quantization loss [ 0.0618], 0.53 sec/batch.
2022-10-19 00:23:36,335 step [ 406], lr [0.0001500], embedding loss [ 0.7419], quantization loss [ 0.0591], 0.53 sec/batch.
2022-10-19 00:23:38,309 step [ 407], lr [0.0001500], embedding loss [ 0.7399], quantization loss [ 0.0532], 0.52 sec/batch.
2022-10-19 00:23:40,300 step [ 408], lr [0.0001500], embedding loss [ 0.7339], quantization loss [ 0.0524], 0.53 sec/batch.
2022-10-19 00:23:42,343 step [ 409], lr [0.0001500], embedding loss [ 0.7269], quantization loss [ 0.0558], 0.58 sec/batch.
2022-10-19 00:23:44,351 step [ 410], lr [0.0001500], embedding loss [ 0.7458], quantization loss [ 0.0632], 0.53 sec/batch.
2022-10-19 00:23:46,399 step [ 411], lr [0.0001500], embedding loss [ 0.7471], quantization loss [ 0.0733], 0.53 sec/batch.
2022-10-19 00:23:48,359 step [ 412], lr [0.0001500], embedding loss [ 0.7515], quantization loss [ 0.0630], 0.53 sec/batch.
2022-10-19 00:23:50,321 step [ 413], lr [0.0001500], embedding loss [ 0.7343], quantization loss [ 0.0610], 0.53 sec/batch.
2022-10-19 00:23:52,280 step [ 414], lr [0.0001500], embedding loss [ 0.7517], quantization loss [ 0.0659], 0.53 sec/batch.
2022-10-19 00:23:54,237 step [ 415], lr [0.0001500], embedding loss [ 0.7405], quantization loss [ 0.0676], 0.52 sec/batch.
2022-10-19 00:23:56,165 step [ 416], lr [0.0001500], embedding loss [ 0.7485], quantization loss [ 0.0712], 0.52 sec/batch.
2022-10-19 00:23:58,143 step [ 417], lr [0.0001500], embedding loss [ 0.7444], quantization loss [ 0.0550], 0.53 sec/batch.
2022-10-19 00:24:00,113 step [ 418], lr [0.0001500], embedding loss [ 0.7467], quantization loss [ 0.0588], 0.53 sec/batch.
2022-10-19 00:24:02,127 step [ 419], lr [0.0001500], embedding loss [ 0.7474], quantization loss [ 0.0604], 0.52 sec/batch.
2022-10-19 00:24:04,100 step [ 420], lr [0.0001500], embedding loss [ 0.7397], quantization loss [ 0.0630], 0.53 sec/batch.
2022-10-19 00:24:06,058 step [ 421], lr [0.0001500], embedding loss [ 0.7356], quantization loss [ 0.0595], 0.52 sec/batch.
2022-10-19 00:24:08,017 step [ 422], lr [0.0001500], embedding loss [ 0.7345], quantization loss [ 0.0554], 0.53 sec/batch.
2022-10-19 00:24:09,977 step [ 423], lr [0.0001500], embedding loss [ 0.7501], quantization loss [ 0.0562], 0.53 sec/batch.
2022-10-19 00:24:11,935 step [ 424], lr [0.0001500], embedding loss [ 0.7428], quantization loss [ 0.0617], 0.53 sec/batch.
2022-10-19 00:24:13,897 step [ 425], lr [0.0001500], embedding loss [ 0.7393], quantization loss [ 0.0621], 0.53 sec/batch.
2022-10-19 00:24:15,863 step [ 426], lr [0.0001500], embedding loss [ 0.7378], quantization loss [ 0.0582], 0.53 sec/batch.
2022-10-19 00:24:17,822 step [ 427], lr [0.0001500], embedding loss [ 0.7465], quantization loss [ 0.0637], 0.53 sec/batch.
2022-10-19 00:24:19,761 step [ 428], lr [0.0001500], embedding loss [ 0.7381], quantization loss [ 0.0567], 0.51 sec/batch.
2022-10-19 00:24:21,723 step [ 429], lr [0.0001500], embedding loss [ 0.7453], quantization loss [ 0.0614], 0.53 sec/batch.
2022-10-19 00:24:23,674 step [ 430], lr [0.0001500], embedding loss [ 0.7383], quantization loss [ 0.0629], 0.52 sec/batch.
2022-10-19 00:24:25,608 step [ 431], lr [0.0001500], embedding loss [ 0.7556], quantization loss [ 0.0611], 0.52 sec/batch.
2022-10-19 00:24:27,575 step [ 432], lr [0.0001500], embedding loss [ 0.7432], quantization loss [ 0.0616], 0.53 sec/batch.
2022-10-19 00:24:29,542 step [ 433], lr [0.0001500], embedding loss [ 0.7328], quantization loss [ 0.0638], 0.52 sec/batch.
2022-10-19 00:24:31,497 step [ 434], lr [0.0001500], embedding loss [ 0.7315], quantization loss [ 0.0568], 0.52 sec/batch.
2022-10-19 00:24:33,518 step [ 435], lr [0.0001500], embedding loss [ 0.7339], quantization loss [ 0.0586], 0.52 sec/batch.
2022-10-19 00:24:35,423 step [ 436], lr [0.0001500], embedding loss [ 0.7338], quantization loss [ 0.0672], 0.53 sec/batch.
2022-10-19 00:24:37,382 step [ 437], lr [0.0001500], embedding loss [ 0.7407], quantization loss [ 0.0595], 0.53 sec/batch.
2022-10-19 00:24:39,289 step [ 438], lr [0.0001500], embedding loss [ 0.7458], quantization loss [ 0.0590], 0.52 sec/batch.
2022-10-19 00:24:41,258 step [ 439], lr [0.0001500], embedding loss [ 0.7508], quantization loss [ 0.0629], 0.53 sec/batch.
2022-10-19 00:24:43,218 step [ 440], lr [0.0001500], embedding loss [ 0.7389], quantization loss [ 0.0632], 0.53 sec/batch.
2022-10-19 00:24:45,220 step [ 441], lr [0.0001500], embedding loss [ 0.7431], quantization loss [ 0.0564], 0.53 sec/batch.
2022-10-19 00:24:47,190 step [ 442], lr [0.0001500], embedding loss [ 0.7477], quantization loss [ 0.0562], 0.52 sec/batch.
2022-10-19 00:24:49,122 step [ 443], lr [0.0001500], embedding loss [ 0.7271], quantization loss [ 0.0555], 0.51 sec/batch.
2022-10-19 00:24:51,085 step [ 444], lr [0.0001500], embedding loss [ 0.7390], quantization loss [ 0.0523], 0.52 sec/batch.
2022-10-19 00:24:53,004 step [ 445], lr [0.0001500], embedding loss [ 0.7364], quantization loss [ 0.0607], 0.51 sec/batch.
2022-10-19 00:24:54,950 step [ 446], lr [0.0001500], embedding loss [ 0.7398], quantization loss [ 0.0582], 0.52 sec/batch.
2022-10-19 00:24:56,921 step [ 447], lr [0.0001500], embedding loss [ 0.7448], quantization loss [ 0.0591], 0.53 sec/batch.
2022-10-19 00:24:58,833 step [ 448], lr [0.0001500], embedding loss [ 0.7324], quantization loss [ 0.0608], 0.52 sec/batch.
2022-10-19 00:25:00,777 step [ 449], lr [0.0001500], embedding loss [ 0.7380], quantization loss [ 0.0516], 0.51 sec/batch.
2022-10-19 00:25:02,714 step [ 450], lr [0.0001500], embedding loss [ 0.7372], quantization loss [ 0.0564], 0.52 sec/batch.
2022-10-19 00:25:04,639 step [ 451], lr [0.0001500], embedding loss [ 0.7450], quantization loss [ 0.0537], 0.52 sec/batch.
2022-10-19 00:25:06,603 step [ 452], lr [0.0001500], embedding loss [ 0.7461], quantization loss [ 0.0526], 0.53 sec/batch.
2022-10-19 00:25:08,614 step [ 453], lr [0.0001500], embedding loss [ 0.7452], quantization loss [ 0.0585], 0.53 sec/batch.
2022-10-19 00:25:10,604 step [ 454], lr [0.0001500], embedding loss [ 0.7441], quantization loss [ 0.0537], 0.52 sec/batch.
2022-10-19 00:25:12,569 step [ 455], lr [0.0001500], embedding loss [ 0.7426], quantization loss [ 0.0553], 0.52 sec/batch.
2022-10-19 00:25:14,540 step [ 456], lr [0.0001500], embedding loss [ 0.7384], quantization loss [ 0.0546], 0.52 sec/batch.
2022-10-19 00:25:16,556 step [ 457], lr [0.0001500], embedding loss [ 0.7436], quantization loss [ 0.0514], 0.53 sec/batch.
2022-10-19 00:25:18,536 step [ 458], lr [0.0001500], embedding loss [ 0.7449], quantization loss [ 0.0544], 0.52 sec/batch.
2022-10-19 00:25:20,479 step [ 459], lr [0.0001500], embedding loss [ 0.7386], quantization loss [ 0.0579], 0.52 sec/batch.
2022-10-19 00:25:22,468 step [ 460], lr [0.0001500], embedding loss [ 0.7557], quantization loss [ 0.0591], 0.53 sec/batch.
2022-10-19 00:25:24,488 step [ 461], lr [0.0001500], embedding loss [ 0.7476], quantization loss [ 0.0553], 0.54 sec/batch.
2022-10-19 00:25:26,425 step [ 462], lr [0.0001500], embedding loss [ 0.7509], quantization loss [ 0.0552], 0.51 sec/batch.
2022-10-19 00:25:28,343 step [ 463], lr [0.0001500], embedding loss [ 0.7370], quantization loss [ 0.0570], 0.51 sec/batch.
2022-10-19 00:25:30,332 step [ 464], lr [0.0001500], embedding loss [ 0.7462], quantization loss [ 0.0538], 0.52 sec/batch.
2022-10-19 00:25:32,350 step [ 465], lr [0.0001500], embedding loss [ 0.7395], quantization loss [ 0.0526], 0.53 sec/batch.
2022-10-19 00:25:34,310 step [ 466], lr [0.0001500], embedding loss [ 0.7412], quantization loss [ 0.0506], 0.52 sec/batch.
2022-10-19 00:25:36,342 step [ 467], lr [0.0001500], embedding loss [ 0.7395], quantization loss [ 0.0552], 0.53 sec/batch.
2022-10-19 00:25:38,373 step [ 468], lr [0.0001500], embedding loss [ 0.7364], quantization loss [ 0.0534], 0.55 sec/batch.
2022-10-19 00:25:40,404 step [ 469], lr [0.0001500], embedding loss [ 0.7323], quantization loss [ 0.0581], 0.53 sec/batch.
2022-10-19 00:25:42,407 step [ 470], lr [0.0001500], embedding loss [ 0.7294], quantization loss [ 0.0536], 0.52 sec/batch.
2022-10-19 00:25:44,372 step [ 471], lr [0.0001500], embedding loss [ 0.7369], quantization loss [ 0.0553], 0.53 sec/batch.
2022-10-19 00:25:46,317 step [ 472], lr [0.0001500], embedding loss [ 0.7453], quantization loss [ 0.0614], 0.50 sec/batch.
2022-10-19 00:25:48,290 step [ 473], lr [0.0001500], embedding loss [ 0.7429], quantization loss [ 0.0578], 0.53 sec/batch.
2022-10-19 00:25:50,316 step [ 474], lr [0.0001500], embedding loss [ 0.7336], quantization loss [ 0.0565], 0.52 sec/batch.
2022-10-19 00:25:52,305 step [ 475], lr [0.0001500], embedding loss [ 0.7439], quantization loss [ 0.0634], 0.53 sec/batch.
2022-10-19 00:25:54,294 step [ 476], lr [0.0001500], embedding loss [ 0.7294], quantization loss [ 0.0527], 0.53 sec/batch.
2022-10-19 00:25:56,275 step [ 477], lr [0.0001500], embedding loss [ 0.7371], quantization loss [ 0.0505], 0.53 sec/batch.
2022-10-19 00:25:58,256 step [ 478], lr [0.0001500], embedding loss [ 0.7247], quantization loss [ 0.0573], 0.53 sec/batch.
2022-10-19 00:26:00,218 step [ 479], lr [0.0001500], embedding loss [ 0.7433], quantization loss [ 0.0543], 0.51 sec/batch.
2022-10-19 00:26:02,181 step [ 480], lr [0.0001500], embedding loss [ 0.7490], quantization loss [ 0.0524], 0.53 sec/batch.
2022-10-19 00:26:04,166 step [ 481], lr [0.0001500], embedding loss [ 0.7428], quantization loss [ 0.0560], 0.53 sec/batch.
2022-10-19 00:26:04,166 update codes and centers iter(1/1).
2022-10-19 00:26:05,763 number of update_code wrong: 0.
2022-10-19 00:26:08,815 non zero codewords: 512.
2022-10-19 00:26:08,815 finish center update, duration: 4.65 sec.
2022-10-19 00:26:10,698 step [ 482], lr [0.0001500], embedding loss [ 0.7459], quantization loss [ 0.0544], 0.55 sec/batch.
2022-10-19 00:26:12,682 step [ 483], lr [0.0001500], embedding loss [ 0.7436], quantization loss [ 0.0470], 0.54 sec/batch.
2022-10-19 00:26:14,731 step [ 484], lr [0.0001500], embedding loss [ 0.7472], quantization loss [ 0.0511], 0.56 sec/batch.
2022-10-19 00:26:16,813 step [ 485], lr [0.0001500], embedding loss [ 0.7493], quantization loss [ 0.0643], 0.56 sec/batch.
2022-10-19 00:26:18,823 step [ 486], lr [0.0001500], embedding loss [ 0.7385], quantization loss [ 0.0578], 0.55 sec/batch.
2022-10-19 00:26:20,884 step [ 487], lr [0.0001500], embedding loss [ 0.7440], quantization loss [ 0.0612], 0.55 sec/batch.
2022-10-19 00:26:22,886 step [ 488], lr [0.0001500], embedding loss [ 0.7436], quantization loss [ 0.0609], 0.54 sec/batch.
2022-10-19 00:26:24,926 step [ 489], lr [0.0001500], embedding loss [ 0.7393], quantization loss [ 0.0584], 0.56 sec/batch.
2022-10-19 00:26:27,021 step [ 490], lr [0.0001500], embedding loss [ 0.7406], quantization loss [ 0.0543], 0.56 sec/batch.
2022-10-19 00:26:29,032 step [ 491], lr [0.0001500], embedding loss [ 0.7460], quantization loss [ 0.0564], 0.52 sec/batch.
2022-10-19 00:26:30,911 step [ 492], lr [0.0001500], embedding loss [ 0.7381], quantization loss [ 0.0515], 0.50 sec/batch.
2022-10-19 00:26:32,909 step [ 493], lr [0.0001500], embedding loss [ 0.7316], quantization loss [ 0.0556], 0.50 sec/batch.
2022-10-19 00:26:34,809 step [ 494], lr [0.0001500], embedding loss [ 0.7374], quantization loss [ 0.0540], 0.49 sec/batch.
2022-10-19 00:26:36,772 step [ 495], lr [0.0001500], embedding loss [ 0.7376], quantization loss [ 0.0629], 0.53 sec/batch.
2022-10-19 00:26:38,760 step [ 496], lr [0.0001500], embedding loss [ 0.7352], quantization loss [ 0.0563], 0.52 sec/batch.
2022-10-19 00:26:40,741 step [ 497], lr [0.0001500], embedding loss [ 0.7363], quantization loss [ 0.0560], 0.53 sec/batch.
2022-10-19 00:26:42,742 step [ 498], lr [0.0001500], embedding loss [ 0.7310], quantization loss [ 0.0524], 0.53 sec/batch.
2022-10-19 00:26:44,742 step [ 499], lr [0.0001500], embedding loss [ 0.7433], quantization loss [ 0.0556], 0.52 sec/batch.
2022-10-19 00:26:46,717 step [ 500], lr [0.0001500], embedding loss [ 0.7422], quantization loss [ 0.0542], 0.52 sec/batch.
2022-10-19 00:26:48,712 step [ 501], lr [0.0001500], embedding loss [ 0.7437], quantization loss [ 0.0575], 0.53 sec/batch.
2022-10-19 00:26:50,727 step [ 502], lr [0.0001500], embedding loss [ 0.7337], quantization loss [ 0.0520], 0.52 sec/batch.
2022-10-19 00:26:52,701 step [ 503], lr [0.0001500], embedding loss [ 0.7487], quantization loss [ 0.0498], 0.53 sec/batch.
2022-10-19 00:26:54,656 step [ 504], lr [0.0001500], embedding loss [ 0.7311], quantization loss [ 0.0528], 0.52 sec/batch.
2022-10-19 00:26:56,623 step [ 505], lr [0.0001500], embedding loss [ 0.7389], quantization loss [ 0.0606], 0.53 sec/batch.
2022-10-19 00:26:58,654 step [ 506], lr [0.0001500], embedding loss [ 0.7315], quantization loss [ 0.0567], 0.52 sec/batch.
2022-10-19 00:27:00,740 step [ 507], lr [0.0001500], embedding loss [ 0.7297], quantization loss [ 0.0529], 0.53 sec/batch.
2022-10-19 00:27:02,716 step [ 508], lr [0.0001500], embedding loss [ 0.7398], quantization loss [ 0.0500], 0.52 sec/batch.
2022-10-19 00:27:04,738 step [ 509], lr [0.0001500], embedding loss [ 0.7335], quantization loss [ 0.0597], 0.53 sec/batch.
2022-10-19 00:27:06,703 step [ 510], lr [0.0001500], embedding loss [ 0.7342], quantization loss [ 0.0607], 0.52 sec/batch.
2022-10-19 00:27:08,738 step [ 511], lr [0.0001500], embedding loss [ 0.7429], quantization loss [ 0.0582], 0.53 sec/batch.
2022-10-19 00:27:10,718 step [ 512], lr [0.0001500], embedding loss [ 0.7337], quantization loss [ 0.0503], 0.53 sec/batch.
2022-10-19 00:27:12,719 step [ 513], lr [0.0001500], embedding loss [ 0.7408], quantization loss [ 0.0521], 0.53 sec/batch.
2022-10-19 00:27:14,693 step [ 514], lr [0.0001500], embedding loss [ 0.7317], quantization loss [ 0.0530], 0.52 sec/batch.
2022-10-19 00:27:16,690 step [ 515], lr [0.0001500], embedding loss [ 0.7473], quantization loss [ 0.0594], 0.53 sec/batch.
2022-10-19 00:27:18,699 step [ 516], lr [0.0001500], embedding loss [ 0.7375], quantization loss [ 0.0608], 0.53 sec/batch.
2022-10-19 00:27:20,688 step [ 517], lr [0.0001500], embedding loss [ 0.7338], quantization loss [ 0.0542], 0.53 sec/batch.
2022-10-19 00:27:22,663 step [ 518], lr [0.0001500], embedding loss [ 0.7399], quantization loss [ 0.0557], 0.52 sec/batch.
2022-10-19 00:27:24,720 step [ 519], lr [0.0001500], embedding loss [ 0.7522], quantization loss [ 0.0573], 0.52 sec/batch.
2022-10-19 00:27:26,765 step [ 520], lr [0.0001500], embedding loss [ 0.7422], quantization loss [ 0.0567], 0.52 sec/batch.
2022-10-19 00:27:28,793 step [ 521], lr [0.0001500], embedding loss [ 0.7310], quantization loss [ 0.0538], 0.52 sec/batch.
2022-10-19 00:27:30,840 step [ 522], lr [0.0001500], embedding loss [ 0.7499], quantization loss [ 0.0520], 0.52 sec/batch.
2022-10-19 00:27:32,868 step [ 523], lr [0.0001500], embedding loss [ 0.7471], quantization loss [ 0.0493], 0.53 sec/batch.
2022-10-19 00:27:34,858 step [ 524], lr [0.0001500], embedding loss [ 0.7365], quantization loss [ 0.0519], 0.52 sec/batch.
2022-10-19 00:27:36,836 step [ 525], lr [0.0001500], embedding loss [ 0.7251], quantization loss [ 0.0495], 0.53 sec/batch.
2022-10-19 00:27:38,805 step [ 526], lr [0.0001500], embedding loss [ 0.7432], quantization loss [ 0.0509], 0.52 sec/batch.
2022-10-19 00:27:40,835 step [ 527], lr [0.0001500], embedding loss [ 0.7450], quantization loss [ 0.0525], 0.53 sec/batch.
2022-10-19 00:27:42,831 step [ 528], lr [0.0001500], embedding loss [ 0.7457], quantization loss [ 0.0460], 0.52 sec/batch.
2022-10-19 00:27:44,811 step [ 529], lr [0.0001500], embedding loss [ 0.7402], quantization loss [ 0.0534], 0.53 sec/batch.
2022-10-19 00:27:46,781 step [ 530], lr [0.0001500], embedding loss [ 0.7406], quantization loss [ 0.0470], 0.52 sec/batch.
2022-10-19 00:27:48,858 step [ 531], lr [0.0001500], embedding loss [ 0.7444], quantization loss [ 0.0534], 0.52 sec/batch.
2022-10-19 00:27:50,824 step [ 532], lr [0.0001500], embedding loss [ 0.7288], quantization loss [ 0.0455], 0.53 sec/batch.
2022-10-19 00:27:52,857 step [ 533], lr [0.0001500], embedding loss [ 0.7444], quantization loss [ 0.0572], 0.53 sec/batch.
2022-10-19 00:27:54,841 step [ 534], lr [0.0001500], embedding loss [ 0.7351], quantization loss [ 0.0542], 0.53 sec/batch.
2022-10-19 00:27:56,883 step [ 535], lr [0.0001500], embedding loss [ 0.7336], quantization loss [ 0.0517], 0.53 sec/batch.
2022-10-19 00:27:58,864 step [ 536], lr [0.0001500], embedding loss [ 0.7237], quantization loss [ 0.0521], 0.53 sec/batch.
2022-10-19 00:28:00,912 step [ 537], lr [0.0001500], embedding loss [ 0.7442], quantization loss [ 0.0536], 0.53 sec/batch.
2022-10-19 00:28:02,929 step [ 538], lr [0.0001500], embedding loss [ 0.7395], quantization loss [ 0.0548], 0.53 sec/batch.
2022-10-19 00:28:04,973 step [ 539], lr [0.0001500], embedding loss [ 0.7362], quantization loss [ 0.0515], 0.53 sec/batch.
2022-10-19 00:28:06,988 step [ 540], lr [0.0001500], embedding loss [ 0.7273], quantization loss [ 0.0553], 0.53 sec/batch.
2022-10-19 00:28:09,031 step [ 541], lr [0.0001500], embedding loss [ 0.7518], quantization loss [ 0.0457], 0.53 sec/batch.
2022-10-19 00:28:11,024 step [ 542], lr [0.0001500], embedding loss [ 0.7391], quantization loss [ 0.0458], 0.52 sec/batch.
2022-10-19 00:28:13,057 step [ 543], lr [0.0001500], embedding loss [ 0.7359], quantization loss [ 0.0455], 0.53 sec/batch.
2022-10-19 00:28:15,044 step [ 544], lr [0.0001500], embedding loss [ 0.7408], quantization loss [ 0.0495], 0.53 sec/batch.
2022-10-19 00:28:17,076 step [ 545], lr [0.0001500], embedding loss [ 0.7337], quantization loss [ 0.0529], 0.53 sec/batch.
2022-10-19 00:28:19,111 step [ 546], lr [0.0001500], embedding loss [ 0.7323], quantization loss [ 0.0479], 0.54 sec/batch.
2022-10-19 00:28:21,141 step [ 547], lr [0.0001500], embedding loss [ 0.7413], quantization loss [ 0.0581], 0.53 sec/batch.
2022-10-19 00:28:23,131 step [ 548], lr [0.0001500], embedding loss [ 0.7215], quantization loss [ 0.0533], 0.52 sec/batch.
2022-10-19 00:28:25,165 step [ 549], lr [0.0001500], embedding loss [ 0.7238], quantization loss [ 0.0429], 0.53 sec/batch.
2022-10-19 00:28:27,148 step [ 550], lr [0.0001500], embedding loss [ 0.7421], quantization loss [ 0.0526], 0.53 sec/batch.
2022-10-19 00:28:29,185 step [ 551], lr [0.0001500], embedding loss [ 0.7344], quantization loss [ 0.0523], 0.53 sec/batch.
2022-10-19 00:28:31,172 step [ 552], lr [0.0001500], embedding loss [ 0.7339], quantization loss [ 0.0543], 0.52 sec/batch.
2022-10-19 00:28:33,211 step [ 553], lr [0.0001500], embedding loss [ 0.7424], quantization loss [ 0.0554], 0.53 sec/batch.
2022-10-19 00:28:35,203 step [ 554], lr [0.0001500], embedding loss [ 0.7455], quantization loss [ 0.0491], 0.52 sec/batch.
2022-10-19 00:28:37,154 step [ 555], lr [0.0001500], embedding loss [ 0.7369], quantization loss [ 0.0501], 0.51 sec/batch.
2022-10-19 00:28:39,128 step [ 556], lr [0.0001500], embedding loss [ 0.7492], quantization loss [ 0.0557], 0.52 sec/batch.
2022-10-19 00:28:41,195 step [ 557], lr [0.0001500], embedding loss [ 0.7367], quantization loss [ 0.0505], 0.53 sec/batch.
2022-10-19 00:28:43,186 step [ 558], lr [0.0001500], embedding loss [ 0.7491], quantization loss [ 0.0502], 0.52 sec/batch.
2022-10-19 00:28:45,173 step [ 559], lr [0.0001500], embedding loss [ 0.7433], quantization loss [ 0.0590], 0.53 sec/batch.
2022-10-19 00:28:47,144 step [ 560], lr [0.0001500], embedding loss [ 0.7330], quantization loss [ 0.0456], 0.52 sec/batch.
2022-10-19 00:28:49,107 step [ 561], lr [0.0001500], embedding loss [ 0.7319], quantization loss [ 0.0474], 0.51 sec/batch.
2022-10-19 00:28:49,108 update codes and centers iter(1/1).
2022-10-19 00:28:50,702 number of update_code wrong: 0.
2022-10-19 00:28:53,819 non zero codewords: 512.
2022-10-19 00:28:53,819 finish center update, duration: 4.71 sec.
2022-10-19 00:28:55,696 step [ 562], lr [0.0001500], embedding loss [ 0.7477], quantization loss [ 0.0595], 0.53 sec/batch.
2022-10-19 00:28:57,688 step [ 563], lr [0.0001500], embedding loss [ 0.7469], quantization loss [ 0.0554], 0.54 sec/batch.
2022-10-19 00:28:59,676 step [ 564], lr [0.0001500], embedding loss [ 0.7365], quantization loss [ 0.0516], 0.52 sec/batch.
2022-10-19 00:29:01,742 step [ 565], lr [0.0001500], embedding loss [ 0.7295], quantization loss [ 0.0501], 0.53 sec/batch.
2022-10-19 00:29:03,745 step [ 566], lr [0.0001500], embedding loss [ 0.7430], quantization loss [ 0.0496], 0.51 sec/batch.
2022-10-19 00:29:05,757 step [ 567], lr [0.0001500], embedding loss [ 0.7484], quantization loss [ 0.0498], 0.53 sec/batch.
2022-10-19 00:29:07,768 step [ 568], lr [0.0001500], embedding loss [ 0.7279], quantization loss [ 0.0476], 0.55 sec/batch.
2022-10-19 00:29:09,764 step [ 569], lr [0.0001500], embedding loss [ 0.7265], quantization loss [ 0.0525], 0.52 sec/batch.
2022-10-19 00:29:11,822 step [ 570], lr [0.0001500], embedding loss [ 0.7436], quantization loss [ 0.0673], 0.53 sec/batch.
2022-10-19 00:29:13,879 step [ 571], lr [0.0001500], embedding loss [ 0.7410], quantization loss [ 0.0513], 0.53 sec/batch.
2022-10-19 00:29:15,948 step [ 572], lr [0.0001500], embedding loss [ 0.7326], quantization loss [ 0.0507], 0.53 sec/batch.
2022-10-19 00:29:17,960 step [ 573], lr [0.0001500], embedding loss [ 0.7398], quantization loss [ 0.0508], 0.53 sec/batch.
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2022-10-19 00:29:30,100 step [ 579], lr [0.0001500], embedding loss [ 0.7396], quantization loss [ 0.0487], 0.51 sec/batch.
2022-10-19 00:29:32,097 step [ 580], lr [0.0001500], embedding loss [ 0.7382], quantization loss [ 0.0585], 0.53 sec/batch.
2022-10-19 00:29:34,151 step [ 581], lr [0.0001500], embedding loss [ 0.7313], quantization loss [ 0.0523], 0.53 sec/batch.
2022-10-19 00:29:36,214 step [ 582], lr [0.0001500], embedding loss [ 0.7418], quantization loss [ 0.0474], 0.53 sec/batch.
2022-10-19 00:29:38,212 step [ 583], lr [0.0001500], embedding loss [ 0.7408], quantization loss [ 0.0456], 0.53 sec/batch.
2022-10-19 00:29:40,263 step [ 584], lr [0.0001500], embedding loss [ 0.7389], quantization loss [ 0.0483], 0.53 sec/batch.
2022-10-19 00:29:42,303 step [ 585], lr [0.0001500], embedding loss [ 0.7332], quantization loss [ 0.0460], 0.53 sec/batch.
2022-10-19 00:29:44,338 step [ 586], lr [0.0001500], embedding loss [ 0.7349], quantization loss [ 0.0543], 0.52 sec/batch.
2022-10-19 00:29:46,437 step [ 587], lr [0.0001500], embedding loss [ 0.7361], quantization loss [ 0.0523], 0.53 sec/batch.
2022-10-19 00:29:48,452 step [ 588], lr [0.0001500], embedding loss [ 0.7283], quantization loss [ 0.0526], 0.53 sec/batch.
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2022-10-19 00:29:52,458 step [ 590], lr [0.0001500], embedding loss [ 0.7405], quantization loss [ 0.0453], 0.51 sec/batch.
2022-10-19 00:29:54,465 step [ 591], lr [0.0001500], embedding loss [ 0.7365], quantization loss [ 0.0482], 0.52 sec/batch.
2022-10-19 00:29:56,483 step [ 592], lr [0.0001500], embedding loss [ 0.7396], quantization loss [ 0.0490], 0.52 sec/batch.
2022-10-19 00:29:58,462 step [ 593], lr [0.0001500], embedding loss [ 0.7257], quantization loss [ 0.0458], 0.51 sec/batch.
2022-10-19 00:30:00,472 step [ 594], lr [0.0001500], embedding loss [ 0.7450], quantization loss [ 0.0531], 0.53 sec/batch.
2022-10-19 00:30:02,496 step [ 595], lr [0.0001500], embedding loss [ 0.7402], quantization loss [ 0.0458], 0.53 sec/batch.
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2022-10-19 00:30:06,481 step [ 597], lr [0.0001500], embedding loss [ 0.7389], quantization loss [ 0.0474], 0.53 sec/batch.
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2022-10-19 00:30:10,486 step [ 599], lr [0.0001500], embedding loss [ 0.7261], quantization loss [ 0.0496], 0.52 sec/batch.
2022-10-19 00:30:12,475 step [ 600], lr [0.0001500], embedding loss [ 0.7379], quantization loss [ 0.0511], 0.51 sec/batch.
2022-10-19 00:30:14,450 step [ 601], lr [0.0000750], embedding loss [ 0.7424], quantization loss [ 0.0547], 0.52 sec/batch.
2022-10-19 00:30:16,423 step [ 602], lr [0.0000750], embedding loss [ 0.7460], quantization loss [ 0.0471], 0.51 sec/batch.
2022-10-19 00:30:18,466 step [ 603], lr [0.0000750], embedding loss [ 0.7306], quantization loss [ 0.0486], 0.51 sec/batch.
2022-10-19 00:30:20,421 step [ 604], lr [0.0000750], embedding loss [ 0.7383], quantization loss [ 0.0402], 0.51 sec/batch.
2022-10-19 00:30:22,421 step [ 605], lr [0.0000750], embedding loss [ 0.7310], quantization loss [ 0.0444], 0.52 sec/batch.
2022-10-19 00:30:24,430 step [ 606], lr [0.0000750], embedding loss [ 0.7249], quantization loss [ 0.0471], 0.53 sec/batch.
2022-10-19 00:30:26,479 step [ 607], lr [0.0000750], embedding loss [ 0.7244], quantization loss [ 0.0428], 0.53 sec/batch.
2022-10-19 00:30:28,488 step [ 608], lr [0.0000750], embedding loss [ 0.7388], quantization loss [ 0.0454], 0.53 sec/batch.
2022-10-19 00:30:30,531 step [ 609], lr [0.0000750], embedding loss [ 0.7381], quantization loss [ 0.0455], 0.52 sec/batch.
2022-10-19 00:30:32,529 step [ 610], lr [0.0000750], embedding loss [ 0.7315], quantization loss [ 0.0486], 0.52 sec/batch.
2022-10-19 00:30:34,552 step [ 611], lr [0.0000750], embedding loss [ 0.7263], quantization loss [ 0.0440], 0.53 sec/batch.
2022-10-19 00:30:36,560 step [ 612], lr [0.0000750], embedding loss [ 0.7290], quantization loss [ 0.0427], 0.53 sec/batch.
2022-10-19 00:30:38,555 step [ 613], lr [0.0000750], embedding loss [ 0.7276], quantization loss [ 0.0451], 0.52 sec/batch.
2022-10-19 00:30:40,567 step [ 614], lr [0.0000750], embedding loss [ 0.7368], quantization loss [ 0.0439], 0.53 sec/batch.
2022-10-19 00:30:42,579 step [ 615], lr [0.0000750], embedding loss [ 0.7359], quantization loss [ 0.0456], 0.53 sec/batch.
2022-10-19 00:30:44,616 step [ 616], lr [0.0000750], embedding loss [ 0.7382], quantization loss [ 0.0474], 0.54 sec/batch.
2022-10-19 00:30:46,647 step [ 617], lr [0.0000750], embedding loss [ 0.7536], quantization loss [ 0.0531], 0.53 sec/batch.
2022-10-19 00:30:48,642 step [ 618], lr [0.0000750], embedding loss [ 0.7335], quantization loss [ 0.0483], 0.53 sec/batch.
2022-10-19 00:30:50,674 step [ 619], lr [0.0000750], embedding loss [ 0.7438], quantization loss [ 0.0465], 0.53 sec/batch.
2022-10-19 00:30:52,685 step [ 620], lr [0.0000750], embedding loss [ 0.7285], quantization loss [ 0.0439], 0.51 sec/batch.
2022-10-19 00:30:54,685 step [ 621], lr [0.0000750], embedding loss [ 0.7335], quantization loss [ 0.0470], 0.51 sec/batch.
2022-10-19 00:30:56,712 step [ 622], lr [0.0000750], embedding loss [ 0.7293], quantization loss [ 0.0471], 0.55 sec/batch.
2022-10-19 00:30:58,769 step [ 623], lr [0.0000750], embedding loss [ 0.7394], quantization loss [ 0.0383], 0.53 sec/batch.
2022-10-19 00:31:00,832 step [ 624], lr [0.0000750], embedding loss [ 0.7391], quantization loss [ 0.0470], 0.51 sec/batch.
2022-10-19 00:31:02,833 step [ 625], lr [0.0000750], embedding loss [ 0.7342], quantization loss [ 0.0480], 0.52 sec/batch.
2022-10-19 00:31:04,831 step [ 626], lr [0.0000750], embedding loss [ 0.7345], quantization loss [ 0.0457], 0.53 sec/batch.
2022-10-19 00:31:06,830 step [ 627], lr [0.0000750], embedding loss [ 0.7403], quantization loss [ 0.0450], 0.52 sec/batch.
2022-10-19 00:31:08,925 step [ 628], lr [0.0000750], embedding loss [ 0.7407], quantization loss [ 0.0535], 0.53 sec/batch.
2022-10-19 00:31:10,929 step [ 629], lr [0.0000750], embedding loss [ 0.7331], quantization loss [ 0.0451], 0.52 sec/batch.
2022-10-19 00:31:12,937 step [ 630], lr [0.0000750], embedding loss [ 0.7306], quantization loss [ 0.0480], 0.52 sec/batch.
2022-10-19 00:31:14,935 step [ 631], lr [0.0000750], embedding loss [ 0.7381], quantization loss [ 0.0442], 0.52 sec/batch.
2022-10-19 00:31:16,895 step [ 632], lr [0.0000750], embedding loss [ 0.7451], quantization loss [ 0.0472], 0.52 sec/batch.
2022-10-19 00:31:18,913 step [ 633], lr [0.0000750], embedding loss [ 0.7370], quantization loss [ 0.0421], 0.52 sec/batch.
2022-10-19 00:31:20,982 step [ 634], lr [0.0000750], embedding loss [ 0.7465], quantization loss [ 0.0484], 0.53 sec/batch.
2022-10-19 00:31:22,986 step [ 635], lr [0.0000750], embedding loss [ 0.7395], quantization loss [ 0.0420], 0.52 sec/batch.
2022-10-19 00:31:25,067 step [ 636], lr [0.0000750], embedding loss [ 0.7280], quantization loss [ 0.0481], 0.53 sec/batch.
2022-10-19 00:31:27,059 step [ 637], lr [0.0000750], embedding loss [ 0.7501], quantization loss [ 0.0555], 0.52 sec/batch.
2022-10-19 00:31:29,102 step [ 638], lr [0.0000750], embedding loss [ 0.7393], quantization loss [ 0.0468], 0.53 sec/batch.
2022-10-19 00:31:31,137 step [ 639], lr [0.0000750], embedding loss [ 0.7340], quantization loss [ 0.0425], 0.53 sec/batch.
2022-10-19 00:31:33,213 step [ 640], lr [0.0000750], embedding loss [ 0.7373], quantization loss [ 0.0453], 0.53 sec/batch.
2022-10-19 00:31:35,240 step [ 641], lr [0.0000750], embedding loss [ 0.7391], quantization loss [ 0.0438], 0.53 sec/batch.
2022-10-19 00:31:35,241 update codes and centers iter(1/1).
2022-10-19 00:31:36,864 number of update_code wrong: 0.
2022-10-19 00:31:39,946 non zero codewords: 512.
2022-10-19 00:31:39,946 finish center update, duration: 4.71 sec.
2022-10-19 00:31:41,832 step [ 642], lr [0.0000750], embedding loss [ 0.7301], quantization loss [ 0.0446], 0.53 sec/batch.
2022-10-19 00:31:43,796 step [ 643], lr [0.0000750], embedding loss [ 0.7279], quantization loss [ 0.0423], 0.52 sec/batch.
2022-10-19 00:31:45,859 step [ 644], lr [0.0000750], embedding loss [ 0.7217], quantization loss [ 0.0515], 0.53 sec/batch.
2022-10-19 00:31:47,933 step [ 645], lr [0.0000750], embedding loss [ 0.7530], quantization loss [ 0.0467], 0.53 sec/batch.
2022-10-19 00:31:50,001 step [ 646], lr [0.0000750], embedding loss [ 0.7382], quantization loss [ 0.0398], 0.52 sec/batch.
2022-10-19 00:31:52,082 step [ 647], lr [0.0000750], embedding loss [ 0.7533], quantization loss [ 0.0447], 0.53 sec/batch.
2022-10-19 00:31:54,128 step [ 648], lr [0.0000750], embedding loss [ 0.7404], quantization loss [ 0.0475], 0.52 sec/batch.
2022-10-19 00:31:56,169 step [ 649], lr [0.0000750], embedding loss [ 0.7286], quantization loss [ 0.0433], 0.53 sec/batch.
2022-10-19 00:31:58,215 step [ 650], lr [0.0000750], embedding loss [ 0.7435], quantization loss [ 0.0469], 0.52 sec/batch.
2022-10-19 00:32:00,240 step [ 651], lr [0.0000750], embedding loss [ 0.7334], quantization loss [ 0.0410], 0.53 sec/batch.
2022-10-19 00:32:02,239 step [ 652], lr [0.0000750], embedding loss [ 0.7388], quantization loss [ 0.0459], 0.52 sec/batch.
2022-10-19 00:32:04,295 step [ 653], lr [0.0000750], embedding loss [ 0.7271], quantization loss [ 0.0415], 0.53 sec/batch.
2022-10-19 00:32:06,302 step [ 654], lr [0.0000750], embedding loss [ 0.7318], quantization loss [ 0.0418], 0.52 sec/batch.
2022-10-19 00:32:08,310 step [ 655], lr [0.0000750], embedding loss [ 0.7382], quantization loss [ 0.0448], 0.53 sec/batch.
2022-10-19 00:32:10,326 step [ 656], lr [0.0000750], embedding loss [ 0.7308], quantization loss [ 0.0391], 0.53 sec/batch.
2022-10-19 00:32:12,333 step [ 657], lr [0.0000750], embedding loss [ 0.7291], quantization loss [ 0.0480], 0.53 sec/batch.
2022-10-19 00:32:14,359 step [ 658], lr [0.0000750], embedding loss [ 0.7309], quantization loss [ 0.0443], 0.53 sec/batch.
2022-10-19 00:32:16,389 step [ 659], lr [0.0000750], embedding loss [ 0.7221], quantization loss [ 0.0448], 0.51 sec/batch.
2022-10-19 00:32:18,418 step [ 660], lr [0.0000750], embedding loss [ 0.7298], quantization loss [ 0.0392], 0.52 sec/batch.
2022-10-19 00:32:20,411 step [ 661], lr [0.0000750], embedding loss [ 0.7428], quantization loss [ 0.0392], 0.52 sec/batch.
2022-10-19 00:32:22,394 step [ 662], lr [0.0000750], embedding loss [ 0.7417], quantization loss [ 0.0469], 0.52 sec/batch.
2022-10-19 00:32:24,416 step [ 663], lr [0.0000750], embedding loss [ 0.7313], quantization loss [ 0.0489], 0.53 sec/batch.
2022-10-19 00:32:26,424 step [ 664], lr [0.0000750], embedding loss [ 0.7309], quantization loss [ 0.0407], 0.53 sec/batch.
2022-10-19 00:32:28,443 step [ 665], lr [0.0000750], embedding loss [ 0.7453], quantization loss [ 0.0447], 0.53 sec/batch.
2022-10-19 00:32:30,449 step [ 666], lr [0.0000750], embedding loss [ 0.7281], quantization loss [ 0.0474], 0.52 sec/batch.
2022-10-19 00:32:32,490 step [ 667], lr [0.0000750], embedding loss [ 0.7343], quantization loss [ 0.0495], 0.54 sec/batch.
2022-10-19 00:32:34,467 step [ 668], lr [0.0000750], embedding loss [ 0.7316], quantization loss [ 0.0430], 0.52 sec/batch.
2022-10-19 00:32:36,495 step [ 669], lr [0.0000750], embedding loss [ 0.7329], quantization loss [ 0.0426], 0.53 sec/batch.
2022-10-19 00:32:38,509 step [ 670], lr [0.0000750], embedding loss [ 0.7351], quantization loss [ 0.0441], 0.52 sec/batch.
2022-10-19 00:32:40,533 step [ 671], lr [0.0000750], embedding loss [ 0.7369], quantization loss [ 0.0465], 0.52 sec/batch.
2022-10-19 00:32:42,558 step [ 672], lr [0.0000750], embedding loss [ 0.7381], quantization loss [ 0.0473], 0.53 sec/batch.
2022-10-19 00:32:44,597 step [ 673], lr [0.0000750], embedding loss [ 0.7339], quantization loss [ 0.0428], 0.53 sec/batch.
2022-10-19 00:32:46,646 step [ 674], lr [0.0000750], embedding loss [ 0.7459], quantization loss [ 0.0473], 0.54 sec/batch.
2022-10-19 00:32:48,652 step [ 675], lr [0.0000750], embedding loss [ 0.7384], quantization loss [ 0.0411], 0.53 sec/batch.
2022-10-19 00:32:50,694 step [ 676], lr [0.0000750], embedding loss [ 0.7237], quantization loss [ 0.0433], 0.54 sec/batch.
2022-10-19 00:32:52,709 step [ 677], lr [0.0000750], embedding loss [ 0.7276], quantization loss [ 0.0443], 0.53 sec/batch.
2022-10-19 00:32:54,707 step [ 678], lr [0.0000750], embedding loss [ 0.7378], quantization loss [ 0.0397], 0.52 sec/batch.
2022-10-19 00:32:56,740 step [ 679], lr [0.0000750], embedding loss [ 0.7383], quantization loss [ 0.0447], 0.53 sec/batch.
2022-10-19 00:32:58,801 step [ 680], lr [0.0000750], embedding loss [ 0.7361], quantization loss [ 0.0418], 0.53 sec/batch.
2022-10-19 00:33:00,829 step [ 681], lr [0.0000750], embedding loss [ 0.7283], quantization loss [ 0.0440], 0.53 sec/batch.
2022-10-19 00:33:02,849 step [ 682], lr [0.0000750], embedding loss [ 0.7410], quantization loss [ 0.0425], 0.53 sec/batch.
2022-10-19 00:33:04,871 step [ 683], lr [0.0000750], embedding loss [ 0.7415], quantization loss [ 0.0402], 0.53 sec/batch.
2022-10-19 00:33:06,892 step [ 684], lr [0.0000750], embedding loss [ 0.7156], quantization loss [ 0.0507], 0.52 sec/batch.
2022-10-19 00:33:08,911 step [ 685], lr [0.0000750], embedding loss [ 0.7283], quantization loss [ 0.0460], 0.53 sec/batch.
2022-10-19 00:33:10,931 step [ 686], lr [0.0000750], embedding loss [ 0.7408], quantization loss [ 0.0397], 0.52 sec/batch.
2022-10-19 00:33:12,952 step [ 687], lr [0.0000750], embedding loss [ 0.7285], quantization loss [ 0.0465], 0.52 sec/batch.
2022-10-19 00:33:14,977 step [ 688], lr [0.0000750], embedding loss [ 0.7421], quantization loss [ 0.0424], 0.53 sec/batch.
2022-10-19 00:33:17,014 step [ 689], lr [0.0000750], embedding loss [ 0.7348], quantization loss [ 0.0422], 0.53 sec/batch.
2022-10-19 00:33:19,021 step [ 690], lr [0.0000750], embedding loss [ 0.7236], quantization loss [ 0.0392], 0.53 sec/batch.
2022-10-19 00:33:21,044 step [ 691], lr [0.0000750], embedding loss [ 0.7382], quantization loss [ 0.0419], 0.52 sec/batch.
2022-10-19 00:33:23,065 step [ 692], lr [0.0000750], embedding loss [ 0.7461], quantization loss [ 0.0419], 0.51 sec/batch.
2022-10-19 00:33:25,195 step [ 693], lr [0.0000750], embedding loss [ 0.7427], quantization loss [ 0.0441], 0.56 sec/batch.
2022-10-19 00:33:27,278 step [ 694], lr [0.0000750], embedding loss [ 0.7324], quantization loss [ 0.0416], 0.53 sec/batch.
2022-10-19 00:33:29,350 step [ 695], lr [0.0000750], embedding loss [ 0.7278], quantization loss [ 0.0425], 0.53 sec/batch.
2022-10-19 00:33:31,381 step [ 696], lr [0.0000750], embedding loss [ 0.7346], quantization loss [ 0.0425], 0.53 sec/batch.
2022-10-19 00:33:33,468 step [ 697], lr [0.0000750], embedding loss [ 0.7297], quantization loss [ 0.0410], 0.53 sec/batch.
2022-10-19 00:33:35,469 step [ 698], lr [0.0000750], embedding loss [ 0.7432], quantization loss [ 0.0419], 0.52 sec/batch.
2022-10-19 00:33:37,571 step [ 699], lr [0.0000750], embedding loss [ 0.7283], quantization loss [ 0.0413], 0.52 sec/batch.
2022-10-19 00:33:39,642 step [ 700], lr [0.0000750], embedding loss [ 0.7350], quantization loss [ 0.0431], 0.53 sec/batch.
2022-10-19 00:33:41,753 step [ 701], lr [0.0000750], embedding loss [ 0.7348], quantization loss [ 0.0407], 0.54 sec/batch.
2022-10-19 00:33:43,767 step [ 702], lr [0.0000750], embedding loss [ 0.7389], quantization loss [ 0.0386], 0.53 sec/batch.
2022-10-19 00:33:45,837 step [ 703], lr [0.0000750], embedding loss [ 0.7430], quantization loss [ 0.0414], 0.53 sec/batch.
2022-10-19 00:33:47,893 step [ 704], lr [0.0000750], embedding loss [ 0.7369], quantization loss [ 0.0378], 0.53 sec/batch.
2022-10-19 00:33:49,940 step [ 705], lr [0.0000750], embedding loss [ 0.7245], quantization loss [ 0.0408], 0.52 sec/batch.
2022-10-19 00:33:51,995 step [ 706], lr [0.0000750], embedding loss [ 0.7272], quantization loss [ 0.0407], 0.53 sec/batch.
2022-10-19 00:33:54,034 step [ 707], lr [0.0000750], embedding loss [ 0.7342], quantization loss [ 0.0449], 0.53 sec/batch.
2022-10-19 00:33:56,071 step [ 708], lr [0.0000750], embedding loss [ 0.7349], quantization loss [ 0.0467], 0.52 sec/batch.
2022-10-19 00:33:58,124 step [ 709], lr [0.0000750], embedding loss [ 0.7366], quantization loss [ 0.0430], 0.52 sec/batch.
2022-10-19 00:34:00,188 step [ 710], lr [0.0000750], embedding loss [ 0.7400], quantization loss [ 0.0459], 0.53 sec/batch.
2022-10-19 00:34:02,185 step [ 711], lr [0.0000750], embedding loss [ 0.7384], quantization loss [ 0.0377], 0.52 sec/batch.
2022-10-19 00:34:04,193 step [ 712], lr [0.0000750], embedding loss [ 0.7377], quantization loss [ 0.0418], 0.52 sec/batch.
2022-10-19 00:34:06,197 step [ 713], lr [0.0000750], embedding loss [ 0.7329], quantization loss [ 0.0382], 0.53 sec/batch.
2022-10-19 00:34:08,302 step [ 714], lr [0.0000750], embedding loss [ 0.7361], quantization loss [ 0.0468], 0.53 sec/batch.
2022-10-19 00:34:10,378 step [ 715], lr [0.0000750], embedding loss [ 0.7286], quantization loss [ 0.0410], 0.53 sec/batch.
2022-10-19 00:34:12,466 step [ 716], lr [0.0000750], embedding loss [ 0.7344], quantization loss [ 0.0442], 0.53 sec/batch.
2022-10-19 00:34:14,535 step [ 717], lr [0.0000750], embedding loss [ 0.7272], quantization loss [ 0.0445], 0.53 sec/batch.
2022-10-19 00:34:16,638 step [ 718], lr [0.0000750], embedding loss [ 0.7355], quantization loss [ 0.0444], 0.54 sec/batch.
2022-10-19 00:34:18,724 step [ 719], lr [0.0000750], embedding loss [ 0.7372], quantization loss [ 0.0376], 0.53 sec/batch.
2022-10-19 00:34:20,847 step [ 720], lr [0.0000750], embedding loss [ 0.7276], quantization loss [ 0.0379], 0.53 sec/batch.
2022-10-19 00:34:22,935 step [ 721], lr [0.0000750], embedding loss [ 0.7241], quantization loss [ 0.0415], 0.53 sec/batch.
2022-10-19 00:34:22,935 update codes and centers iter(1/1).
2022-10-19 00:34:24,542 number of update_code wrong: 0.
2022-10-19 00:34:27,547 non zero codewords: 512.
2022-10-19 00:34:27,547 finish center update, duration: 4.61 sec.
2022-10-19 00:34:29,451 step [ 722], lr [0.0000750], embedding loss [ 0.7266], quantization loss [ 0.0402], 0.53 sec/batch.
2022-10-19 00:34:31,471 step [ 723], lr [0.0000750], embedding loss [ 0.7233], quantization loss [ 0.0401], 0.52 sec/batch.
2022-10-19 00:34:33,588 step [ 724], lr [0.0000750], embedding loss [ 0.7321], quantization loss [ 0.0435], 0.53 sec/batch.
2022-10-19 00:34:35,677 step [ 725], lr [0.0000750], embedding loss [ 0.7397], quantization loss [ 0.0422], 0.53 sec/batch.
2022-10-19 00:34:37,786 step [ 726], lr [0.0000750], embedding loss [ 0.7443], quantization loss [ 0.0424], 0.53 sec/batch.
2022-10-19 00:34:39,879 step [ 727], lr [0.0000750], embedding loss [ 0.7266], quantization loss [ 0.0383], 0.53 sec/batch.
2022-10-19 00:34:41,914 step [ 728], lr [0.0000750], embedding loss [ 0.7251], quantization loss [ 0.0434], 0.53 sec/batch.
2022-10-19 00:34:44,002 step [ 729], lr [0.0000750], embedding loss [ 0.7317], quantization loss [ 0.0445], 0.54 sec/batch.
2022-10-19 00:34:46,065 step [ 730], lr [0.0000750], embedding loss [ 0.7332], quantization loss [ 0.0435], 0.53 sec/batch.
2022-10-19 00:34:48,115 step [ 731], lr [0.0000750], embedding loss [ 0.7330], quantization loss [ 0.0410], 0.53 sec/batch.
2022-10-19 00:34:50,139 step [ 732], lr [0.0000750], embedding loss [ 0.7336], quantization loss [ 0.0438], 0.53 sec/batch.
2022-10-19 00:34:52,212 step [ 733], lr [0.0000750], embedding loss [ 0.7337], quantization loss [ 0.0484], 0.53 sec/batch.
2022-10-19 00:34:54,249 step [ 734], lr [0.0000750], embedding loss [ 0.7327], quantization loss [ 0.0454], 0.54 sec/batch.
2022-10-19 00:34:56,250 step [ 735], lr [0.0000750], embedding loss [ 0.7359], quantization loss [ 0.0422], 0.51 sec/batch.
2022-10-19 00:34:58,274 step [ 736], lr [0.0000750], embedding loss [ 0.7279], quantization loss [ 0.0395], 0.53 sec/batch.
2022-10-19 00:35:00,358 step [ 737], lr [0.0000750], embedding loss [ 0.7280], quantization loss [ 0.0390], 0.52 sec/batch.
2022-10-19 00:35:02,409 step [ 738], lr [0.0000750], embedding loss [ 0.7409], quantization loss [ 0.0403], 0.53 sec/batch.
2022-10-19 00:35:04,460 step [ 739], lr [0.0000750], embedding loss [ 0.7386], quantization loss [ 0.0375], 0.52 sec/batch.
2022-10-19 00:35:06,504 step [ 740], lr [0.0000750], embedding loss [ 0.7213], quantization loss [ 0.0425], 0.52 sec/batch.
2022-10-19 00:35:08,552 step [ 741], lr [0.0000750], embedding loss [ 0.7257], quantization loss [ 0.0422], 0.51 sec/batch.
2022-10-19 00:35:10,628 step [ 742], lr [0.0000750], embedding loss [ 0.7305], quantization loss [ 0.0440], 0.53 sec/batch.
2022-10-19 00:35:12,656 step [ 743], lr [0.0000750], embedding loss [ 0.7307], quantization loss [ 0.0430], 0.53 sec/batch.
2022-10-19 00:35:14,647 step [ 744], lr [0.0000750], embedding loss [ 0.7358], quantization loss [ 0.0449], 0.53 sec/batch.
2022-10-19 00:35:16,732 step [ 745], lr [0.0000750], embedding loss [ 0.7182], quantization loss [ 0.0440], 0.53 sec/batch.
2022-10-19 00:35:18,759 step [ 746], lr [0.0000750], embedding loss [ 0.7450], quantization loss [ 0.0446], 0.52 sec/batch.
2022-10-19 00:35:20,870 step [ 747], lr [0.0000750], embedding loss [ 0.7291], quantization loss [ 0.0418], 0.53 sec/batch.
2022-10-19 00:35:22,884 step [ 748], lr [0.0000750], embedding loss [ 0.7231], quantization loss [ 0.0422], 0.52 sec/batch.
2022-10-19 00:35:24,899 step [ 749], lr [0.0000750], embedding loss [ 0.7387], quantization loss [ 0.0432], 0.52 sec/batch.
2022-10-19 00:35:26,883 step [ 750], lr [0.0000750], embedding loss [ 0.7432], quantization loss [ 0.0383], 0.52 sec/batch.
2022-10-19 00:35:28,927 step [ 751], lr [0.0000750], embedding loss [ 0.7356], quantization loss [ 0.0408], 0.53 sec/batch.
2022-10-19 00:35:30,975 step [ 752], lr [0.0000750], embedding loss [ 0.7398], quantization loss [ 0.0469], 0.53 sec/batch.
2022-10-19 00:35:33,051 step [ 753], lr [0.0000750], embedding loss [ 0.7450], quantization loss [ 0.0373], 0.53 sec/batch.
2022-10-19 00:35:35,056 step [ 754], lr [0.0000750], embedding loss [ 0.7268], quantization loss [ 0.0394], 0.51 sec/batch.
2022-10-19 00:35:37,077 step [ 755], lr [0.0000750], embedding loss [ 0.7426], quantization loss [ 0.0409], 0.52 sec/batch.
2022-10-19 00:35:39,080 step [ 756], lr [0.0000750], embedding loss [ 0.7441], quantization loss [ 0.0433], 0.52 sec/batch.
2022-10-19 00:35:41,152 step [ 757], lr [0.0000750], embedding loss [ 0.7295], quantization loss [ 0.0425], 0.52 sec/batch.
2022-10-19 00:35:43,123 step [ 758], lr [0.0000750], embedding loss [ 0.7329], quantization loss [ 0.0430], 0.51 sec/batch.
2022-10-19 00:35:45,190 step [ 759], lr [0.0000750], embedding loss [ 0.7408], quantization loss [ 0.0414], 0.53 sec/batch.
2022-10-19 00:35:47,222 step [ 760], lr [0.0000750], embedding loss [ 0.7389], quantization loss [ 0.0396], 0.52 sec/batch.
2022-10-19 00:35:49,219 step [ 761], lr [0.0000750], embedding loss [ 0.7374], quantization loss [ 0.0408], 0.52 sec/batch.
2022-10-19 00:35:51,213 step [ 762], lr [0.0000750], embedding loss [ 0.7407], quantization loss [ 0.0402], 0.52 sec/batch.
2022-10-19 00:35:53,199 step [ 763], lr [0.0000750], embedding loss [ 0.7378], quantization loss [ 0.0468], 0.52 sec/batch.
2022-10-19 00:35:55,237 step [ 764], lr [0.0000750], embedding loss [ 0.7310], quantization loss [ 0.0341], 0.53 sec/batch.
2022-10-19 00:35:57,262 step [ 765], lr [0.0000750], embedding loss [ 0.7215], quantization loss [ 0.0400], 0.53 sec/batch.
2022-10-19 00:35:59,269 step [ 766], lr [0.0000750], embedding loss [ 0.7258], quantization loss [ 0.0419], 0.53 sec/batch.
2022-10-19 00:36:01,311 step [ 767], lr [0.0000750], embedding loss [ 0.7359], quantization loss [ 0.0399], 0.53 sec/batch.
2022-10-19 00:36:03,343 step [ 768], lr [0.0000750], embedding loss [ 0.7331], quantization loss [ 0.0360], 0.52 sec/batch.
2022-10-19 00:36:05,436 step [ 769], lr [0.0000750], embedding loss [ 0.7433], quantization loss [ 0.0435], 0.51 sec/batch.
2022-10-19 00:36:07,466 step [ 770], lr [0.0000750], embedding loss [ 0.7360], quantization loss [ 0.0366], 0.52 sec/batch.
2022-10-19 00:36:09,504 step [ 771], lr [0.0000750], embedding loss [ 0.7347], quantization loss [ 0.0365], 0.53 sec/batch.
2022-10-19 00:36:11,535 step [ 772], lr [0.0000750], embedding loss [ 0.7280], quantization loss [ 0.0400], 0.52 sec/batch.
2022-10-19 00:36:13,570 step [ 773], lr [0.0000750], embedding loss [ 0.7305], quantization loss [ 0.0435], 0.52 sec/batch.
2022-10-19 00:36:15,613 step [ 774], lr [0.0000750], embedding loss [ 0.7360], quantization loss [ 0.0415], 0.53 sec/batch.
2022-10-19 00:36:17,719 step [ 775], lr [0.0000750], embedding loss [ 0.7391], quantization loss [ 0.0397], 0.53 sec/batch.
2022-10-19 00:36:19,796 step [ 776], lr [0.0000750], embedding loss [ 0.7304], quantization loss [ 0.0401], 0.52 sec/batch.
2022-10-19 00:36:21,913 step [ 777], lr [0.0000750], embedding loss [ 0.7256], quantization loss [ 0.0374], 0.53 sec/batch.
2022-10-19 00:36:23,978 step [ 778], lr [0.0000750], embedding loss [ 0.7447], quantization loss [ 0.0450], 0.52 sec/batch.
2022-10-19 00:36:26,024 step [ 779], lr [0.0000750], embedding loss [ 0.7384], quantization loss [ 0.0403], 0.53 sec/batch.
2022-10-19 00:36:28,147 step [ 780], lr [0.0000750], embedding loss [ 0.7369], quantization loss [ 0.0429], 0.53 sec/batch.
2022-10-19 00:36:30,207 step [ 781], lr [0.0000750], embedding loss [ 0.7296], quantization loss [ 0.0374], 0.53 sec/batch.
2022-10-19 00:36:32,218 step [ 782], lr [0.0000750], embedding loss [ 0.7565], quantization loss [ 0.0385], 0.51 sec/batch.
2022-10-19 00:36:34,258 step [ 783], lr [0.0000750], embedding loss [ 0.7266], quantization loss [ 0.0382], 0.52 sec/batch.
2022-10-19 00:36:36,364 step [ 784], lr [0.0000750], embedding loss [ 0.7202], quantization loss [ 0.0335], 0.53 sec/batch.
2022-10-19 00:36:38,431 step [ 785], lr [0.0000750], embedding loss [ 0.7425], quantization loss [ 0.0391], 0.53 sec/batch.
2022-10-19 00:36:40,468 step [ 786], lr [0.0000750], embedding loss [ 0.7319], quantization loss [ 0.0375], 0.51 sec/batch.
2022-10-19 00:36:42,508 step [ 787], lr [0.0000750], embedding loss [ 0.7469], quantization loss [ 0.0402], 0.53 sec/batch.
2022-10-19 00:36:44,535 step [ 788], lr [0.0000750], embedding loss [ 0.7304], quantization loss [ 0.0360], 0.53 sec/batch.
2022-10-19 00:36:46,539 step [ 789], lr [0.0000750], embedding loss [ 0.7301], quantization loss [ 0.0420], 0.52 sec/batch.
2022-10-19 00:36:48,558 step [ 790], lr [0.0000750], embedding loss [ 0.7346], quantization loss [ 0.0352], 0.52 sec/batch.
2022-10-19 00:36:50,575 step [ 791], lr [0.0000750], embedding loss [ 0.7241], quantization loss [ 0.0372], 0.51 sec/batch.
2022-10-19 00:36:52,611 step [ 792], lr [0.0000750], embedding loss [ 0.7210], quantization loss [ 0.0367], 0.53 sec/batch.
2022-10-19 00:36:54,663 step [ 793], lr [0.0000750], embedding loss [ 0.7259], quantization loss [ 0.0388], 0.52 sec/batch.
2022-10-19 00:36:56,766 step [ 794], lr [0.0000750], embedding loss [ 0.7316], quantization loss [ 0.0464], 0.53 sec/batch.
2022-10-19 00:36:58,803 step [ 795], lr [0.0000750], embedding loss [ 0.7176], quantization loss [ 0.0359], 0.50 sec/batch.
2022-10-19 00:37:00,842 step [ 796], lr [0.0000750], embedding loss [ 0.7222], quantization loss [ 0.0370], 0.53 sec/batch.
2022-10-19 00:37:02,877 step [ 797], lr [0.0000750], embedding loss [ 0.7308], quantization loss [ 0.0379], 0.52 sec/batch.
2022-10-19 00:37:04,925 step [ 798], lr [0.0000750], embedding loss [ 0.7287], quantization loss [ 0.0380], 0.52 sec/batch.
2022-10-19 00:37:06,958 step [ 799], lr [0.0000750], embedding loss [ 0.7260], quantization loss [ 0.0424], 0.53 sec/batch.
2022-10-19 00:37:09,017 step [ 800], lr [0.0000750], embedding loss [ 0.7268], quantization loss [ 0.0336], 0.53 sec/batch.
2022-10-19 00:37:11,067 step [ 801], lr [0.0000750], embedding loss [ 0.7275], quantization loss [ 0.0411], 0.52 sec/batch.
2022-10-19 00:37:11,067 update codes and centers iter(1/1).
2022-10-19 00:37:12,666 number of update_code wrong: 0.
2022-10-19 00:37:15,692 non zero codewords: 512.
2022-10-19 00:37:15,692 finish center update, duration: 4.63 sec.
2022-10-19 00:37:17,709 step [ 802], lr [0.0000750], embedding loss [ 0.7423], quantization loss [ 0.0432], 0.53 sec/batch.
2022-10-19 00:37:19,825 step [ 803], lr [0.0000750], embedding loss [ 0.7396], quantization loss [ 0.0384], 0.53 sec/batch.
2022-10-19 00:37:21,900 step [ 804], lr [0.0000750], embedding loss [ 0.7240], quantization loss [ 0.0396], 0.53 sec/batch.
2022-10-19 00:37:24,052 step [ 805], lr [0.0000750], embedding loss [ 0.7306], quantization loss [ 0.0390], 0.52 sec/batch.
2022-10-19 00:37:26,148 step [ 806], lr [0.0000750], embedding loss [ 0.7374], quantization loss [ 0.0418], 0.52 sec/batch.
2022-10-19 00:37:28,268 step [ 807], lr [0.0000750], embedding loss [ 0.7289], quantization loss [ 0.0439], 0.53 sec/batch.
2022-10-19 00:37:30,303 step [ 808], lr [0.0000750], embedding loss [ 0.7365], quantization loss [ 0.0404], 0.52 sec/batch.
2022-10-19 00:37:32,350 step [ 809], lr [0.0000750], embedding loss [ 0.7278], quantization loss [ 0.0435], 0.53 sec/batch.
2022-10-19 00:37:34,411 step [ 810], lr [0.0000750], embedding loss [ 0.7364], quantization loss [ 0.0421], 0.53 sec/batch.
2022-10-19 00:37:36,482 step [ 811], lr [0.0000750], embedding loss [ 0.7377], quantization loss [ 0.0366], 0.53 sec/batch.
2022-10-19 00:37:38,567 step [ 812], lr [0.0000750], embedding loss [ 0.7305], quantization loss [ 0.0384], 0.52 sec/batch.
2022-10-19 00:37:40,576 step [ 813], lr [0.0000750], embedding loss [ 0.7205], quantization loss [ 0.0406], 0.52 sec/batch.
2022-10-19 00:37:42,593 step [ 814], lr [0.0000750], embedding loss [ 0.7368], quantization loss [ 0.0391], 0.52 sec/batch.
2022-10-19 00:37:44,692 step [ 815], lr [0.0000750], embedding loss [ 0.7277], quantization loss [ 0.0437], 0.53 sec/batch.
2022-10-19 00:37:46,759 step [ 816], lr [0.0000750], embedding loss [ 0.7270], quantization loss [ 0.0357], 0.52 sec/batch.
2022-10-19 00:37:48,858 step [ 817], lr [0.0000750], embedding loss [ 0.7291], quantization loss [ 0.0403], 0.52 sec/batch.
2022-10-19 00:37:50,903 step [ 818], lr [0.0000750], embedding loss [ 0.7336], quantization loss [ 0.0384], 0.52 sec/batch.
2022-10-19 00:37:52,953 step [ 819], lr [0.0000750], embedding loss [ 0.7249], quantization loss [ 0.0389], 0.52 sec/batch.
2022-10-19 00:37:55,075 step [ 820], lr [0.0000750], embedding loss [ 0.7445], quantization loss [ 0.0387], 0.54 sec/batch.
2022-10-19 00:37:57,147 step [ 821], lr [0.0000750], embedding loss [ 0.7352], quantization loss [ 0.0383], 0.53 sec/batch.
2022-10-19 00:37:59,196 step [ 822], lr [0.0000750], embedding loss [ 0.7497], quantization loss [ 0.0350], 0.53 sec/batch.
2022-10-19 00:38:01,295 step [ 823], lr [0.0000750], embedding loss [ 0.7230], quantization loss [ 0.0408], 0.53 sec/batch.
2022-10-19 00:38:03,412 step [ 824], lr [0.0000750], embedding loss [ 0.7313], quantization loss [ 0.0428], 0.53 sec/batch.
2022-10-19 00:38:05,434 step [ 825], lr [0.0000750], embedding loss [ 0.7153], quantization loss [ 0.0418], 0.51 sec/batch.
2022-10-19 00:38:07,438 step [ 826], lr [0.0000750], embedding loss [ 0.7263], quantization loss [ 0.0370], 0.52 sec/batch.
2022-10-19 00:38:09,482 step [ 827], lr [0.0000750], embedding loss [ 0.7210], quantization loss [ 0.0423], 0.52 sec/batch.
2022-10-19 00:38:11,542 step [ 828], lr [0.0000750], embedding loss [ 0.7396], quantization loss [ 0.0390], 0.53 sec/batch.
2022-10-19 00:38:13,641 step [ 829], lr [0.0000750], embedding loss [ 0.7309], quantization loss [ 0.0426], 0.53 sec/batch.
2022-10-19 00:38:15,665 step [ 830], lr [0.0000750], embedding loss [ 0.7263], quantization loss [ 0.0408], 0.52 sec/batch.
2022-10-19 00:38:17,699 step [ 831], lr [0.0000750], embedding loss [ 0.7282], quantization loss [ 0.0401], 0.52 sec/batch.
2022-10-19 00:38:19,751 step [ 832], lr [0.0000750], embedding loss [ 0.7210], quantization loss [ 0.0423], 0.53 sec/batch.
2022-10-19 00:38:21,814 step [ 833], lr [0.0000750], embedding loss [ 0.7240], quantization loss [ 0.0425], 0.56 sec/batch.
2022-10-19 00:38:23,940 step [ 834], lr [0.0000750], embedding loss [ 0.7420], quantization loss [ 0.0393], 0.53 sec/batch.
2022-10-19 00:38:25,978 step [ 835], lr [0.0000750], embedding loss [ 0.7413], quantization loss [ 0.0468], 0.56 sec/batch.
2022-10-19 00:38:28,025 step [ 836], lr [0.0000750], embedding loss [ 0.7383], quantization loss [ 0.0422], 0.53 sec/batch.
2022-10-19 00:38:30,216 step [ 837], lr [0.0000750], embedding loss [ 0.7405], quantization loss [ 0.0454], 0.59 sec/batch.
2022-10-19 00:38:32,446 step [ 838], lr [0.0000750], embedding loss [ 0.7206], quantization loss [ 0.0415], 0.57 sec/batch.
2022-10-19 00:38:34,598 step [ 839], lr [0.0000750], embedding loss [ 0.7362], quantization loss [ 0.0356], 0.59 sec/batch.
2022-10-19 00:38:36,698 step [ 840], lr [0.0000750], embedding loss [ 0.7342], quantization loss [ 0.0411], 0.53 sec/batch.
2022-10-19 00:38:38,821 step [ 841], lr [0.0000750], embedding loss [ 0.7420], quantization loss [ 0.0371], 0.54 sec/batch.
2022-10-19 00:38:40,921 step [ 842], lr [0.0000750], embedding loss [ 0.7277], quantization loss [ 0.0380], 0.56 sec/batch.
2022-10-19 00:38:42,946 step [ 843], lr [0.0000750], embedding loss [ 0.7258], quantization loss [ 0.0402], 0.52 sec/batch.
2022-10-19 00:38:45,118 step [ 844], lr [0.0000750], embedding loss [ 0.7353], quantization loss [ 0.0416], 0.56 sec/batch.
2022-10-19 00:38:47,176 step [ 845], lr [0.0000750], embedding loss [ 0.7391], quantization loss [ 0.0403], 0.58 sec/batch.
2022-10-19 00:38:49,414 step [ 846], lr [0.0000750], embedding loss [ 0.7384], quantization loss [ 0.0363], 0.56 sec/batch.
2022-10-19 00:38:51,515 step [ 847], lr [0.0000750], embedding loss [ 0.7188], quantization loss [ 0.0419], 0.57 sec/batch.
2022-10-19 00:38:53,583 step [ 848], lr [0.0000750], embedding loss [ 0.7233], quantization loss [ 0.0376], 0.54 sec/batch.
2022-10-19 00:38:55,764 step [ 849], lr [0.0000750], embedding loss [ 0.7346], quantization loss [ 0.0448], 0.51 sec/batch.
2022-10-19 00:38:57,868 step [ 850], lr [0.0000750], embedding loss [ 0.7299], quantization loss [ 0.0399], 0.53 sec/batch.
2022-10-19 00:38:59,918 step [ 851], lr [0.0000750], embedding loss [ 0.7182], quantization loss [ 0.0400], 0.53 sec/batch.
2022-10-19 00:39:01,987 step [ 852], lr [0.0000750], embedding loss [ 0.7239], quantization loss [ 0.0376], 0.54 sec/batch.
2022-10-19 00:39:04,167 step [ 853], lr [0.0000750], embedding loss [ 0.7330], quantization loss [ 0.0381], 0.51 sec/batch.
2022-10-19 00:39:06,218 step [ 854], lr [0.0000750], embedding loss [ 0.7315], quantization loss [ 0.0436], 0.52 sec/batch.
2022-10-19 00:39:08,341 step [ 855], lr [0.0000750], embedding loss [ 0.7197], quantization loss [ 0.0375], 0.52 sec/batch.
2022-10-19 00:39:10,421 step [ 856], lr [0.0000750], embedding loss [ 0.7337], quantization loss [ 0.0377], 0.53 sec/batch.
2022-10-19 00:39:12,503 step [ 857], lr [0.0000750], embedding loss [ 0.7268], quantization loss [ 0.0365], 0.51 sec/batch.
2022-10-19 00:39:14,512 step [ 858], lr [0.0000750], embedding loss [ 0.7374], quantization loss [ 0.0377], 0.52 sec/batch.
2022-10-19 00:39:16,568 step [ 859], lr [0.0000750], embedding loss [ 0.7383], quantization loss [ 0.0362], 0.53 sec/batch.
2022-10-19 00:39:18,698 step [ 860], lr [0.0000750], embedding loss [ 0.7354], quantization loss [ 0.0381], 0.54 sec/batch.
2022-10-19 00:39:20,882 step [ 861], lr [0.0000750], embedding loss [ 0.7374], quantization loss [ 0.0360], 0.55 sec/batch.
2022-10-19 00:39:23,005 step [ 862], lr [0.0000750], embedding loss [ 0.7313], quantization loss [ 0.0412], 0.56 sec/batch.
2022-10-19 00:39:25,184 step [ 863], lr [0.0000750], embedding loss [ 0.7379], quantization loss [ 0.0415], 0.58 sec/batch.
2022-10-19 00:39:27,234 step [ 864], lr [0.0000750], embedding loss [ 0.7324], quantization loss [ 0.0449], 0.57 sec/batch.
2022-10-19 00:39:29,452 step [ 865], lr [0.0000750], embedding loss [ 0.7221], quantization loss [ 0.0375], 0.56 sec/batch.
2022-10-19 00:39:31,640 step [ 866], lr [0.0000750], embedding loss [ 0.7223], quantization loss [ 0.0381], 0.58 sec/batch.
2022-10-19 00:39:33,825 step [ 867], lr [0.0000750], embedding loss [ 0.7393], quantization loss [ 0.0386], 0.61 sec/batch.
2022-10-19 00:39:35,853 step [ 868], lr [0.0000750], embedding loss [ 0.7251], quantization loss [ 0.0373], 0.51 sec/batch.
2022-10-19 00:39:37,905 step [ 869], lr [0.0000750], embedding loss [ 0.7220], quantization loss [ 0.0445], 0.53 sec/batch.
2022-10-19 00:39:39,925 step [ 870], lr [0.0000750], embedding loss [ 0.7316], quantization loss [ 0.0408], 0.53 sec/batch.
2022-10-19 00:39:42,036 step [ 871], lr [0.0000750], embedding loss [ 0.7321], quantization loss [ 0.0385], 0.55 sec/batch.
2022-10-19 00:39:44,160 step [ 872], lr [0.0000750], embedding loss [ 0.7364], quantization loss [ 0.0368], 0.54 sec/batch.
2022-10-19 00:39:46,381 step [ 873], lr [0.0000750], embedding loss [ 0.7445], quantization loss [ 0.0391], 0.58 sec/batch.
2022-10-19 00:39:48,555 step [ 874], lr [0.0000750], embedding loss [ 0.7317], quantization loss [ 0.0395], 0.52 sec/batch.
2022-10-19 00:39:50,644 step [ 875], lr [0.0000750], embedding loss [ 0.7278], quantization loss [ 0.0369], 0.51 sec/batch.
2022-10-19 00:39:52,684 step [ 876], lr [0.0000750], embedding loss [ 0.7320], quantization loss [ 0.0358], 0.51 sec/batch.
2022-10-19 00:39:54,677 step [ 877], lr [0.0000750], embedding loss [ 0.7402], quantization loss [ 0.0367], 0.51 sec/batch.
2022-10-19 00:39:56,690 step [ 878], lr [0.0000750], embedding loss [ 0.7177], quantization loss [ 0.0386], 0.51 sec/batch.
2022-10-19 00:39:58,719 step [ 879], lr [0.0000750], embedding loss [ 0.7283], quantization loss [ 0.0361], 0.52 sec/batch.
2022-10-19 00:40:00,738 step [ 880], lr [0.0000750], embedding loss [ 0.7299], quantization loss [ 0.0323], 0.52 sec/batch.
2022-10-19 00:40:02,759 step [ 881], lr [0.0000750], embedding loss [ 0.7283], quantization loss [ 0.0456], 0.51 sec/batch.
2022-10-19 00:40:02,760 update codes and centers iter(1/1).
2022-10-19 00:40:04,341 number of update_code wrong: 0.
2022-10-19 00:40:07,455 non zero codewords: 512.
2022-10-19 00:40:07,455 finish center update, duration: 4.70 sec.
2022-10-19 00:40:09,492 step [ 882], lr [0.0000750], embedding loss [ 0.7270], quantization loss [ 0.0387], 0.55 sec/batch.
2022-10-19 00:40:11,597 step [ 883], lr [0.0000750], embedding loss [ 0.7404], quantization loss [ 0.0400], 0.53 sec/batch.
2022-10-19 00:40:13,675 step [ 884], lr [0.0000750], embedding loss [ 0.7303], quantization loss [ 0.0459], 0.58 sec/batch.
2022-10-19 00:40:15,798 step [ 885], lr [0.0000750], embedding loss [ 0.7278], quantization loss [ 0.0390], 0.53 sec/batch.
2022-10-19 00:40:17,933 step [ 886], lr [0.0000750], embedding loss [ 0.7282], quantization loss [ 0.0370], 0.54 sec/batch.
2022-10-19 00:40:20,010 step [ 887], lr [0.0000750], embedding loss [ 0.7212], quantization loss [ 0.0398], 0.53 sec/batch.
2022-10-19 00:40:22,067 step [ 888], lr [0.0000750], embedding loss [ 0.7261], quantization loss [ 0.0365], 0.50 sec/batch.
2022-10-19 00:40:24,184 step [ 889], lr [0.0000750], embedding loss [ 0.7229], quantization loss [ 0.0457], 0.52 sec/batch.
2022-10-19 00:40:26,276 step [ 890], lr [0.0000750], embedding loss [ 0.7363], quantization loss [ 0.0394], 0.54 sec/batch.
2022-10-19 00:40:28,379 step [ 891], lr [0.0000750], embedding loss [ 0.7452], quantization loss [ 0.0404], 0.53 sec/batch.
2022-10-19 00:40:30,518 step [ 892], lr [0.0000750], embedding loss [ 0.7326], quantization loss [ 0.0458], 0.53 sec/batch.
2022-10-19 00:40:32,698 step [ 893], lr [0.0000750], embedding loss [ 0.7350], quantization loss [ 0.0406], 0.53 sec/batch.
2022-10-19 00:40:34,815 step [ 894], lr [0.0000750], embedding loss [ 0.7410], quantization loss [ 0.0425], 0.53 sec/batch.
2022-10-19 00:40:36,909 step [ 895], lr [0.0000750], embedding loss [ 0.7292], quantization loss [ 0.0335], 0.53 sec/batch.
2022-10-19 00:40:39,010 step [ 896], lr [0.0000750], embedding loss [ 0.7223], quantization loss [ 0.0365], 0.53 sec/batch.
2022-10-19 00:40:41,099 step [ 897], lr [0.0000750], embedding loss [ 0.7194], quantization loss [ 0.0401], 0.53 sec/batch.
2022-10-19 00:40:43,209 step [ 898], lr [0.0000750], embedding loss [ 0.7355], quantization loss [ 0.0386], 0.52 sec/batch.
2022-10-19 00:40:45,313 step [ 899], lr [0.0000750], embedding loss [ 0.7157], quantization loss [ 0.0380], 0.53 sec/batch.
2022-10-19 00:40:47,418 step [ 900], lr [0.0000750], embedding loss [ 0.7224], quantization loss [ 0.0360], 0.53 sec/batch.
2022-10-19 00:40:49,572 step [ 901], lr [0.0000375], embedding loss [ 0.7244], quantization loss [ 0.0387], 0.53 sec/batch.
2022-10-19 00:40:51,627 step [ 902], lr [0.0000375], embedding loss [ 0.7281], quantization loss [ 0.0390], 0.50 sec/batch.
2022-10-19 00:40:53,696 step [ 903], lr [0.0000375], embedding loss [ 0.7348], quantization loss [ 0.0435], 0.53 sec/batch.
2022-10-19 00:40:55,840 step [ 904], lr [0.0000375], embedding loss [ 0.7340], quantization loss [ 0.0392], 0.53 sec/batch.
2022-10-19 00:40:57,984 step [ 905], lr [0.0000375], embedding loss [ 0.7369], quantization loss [ 0.0426], 0.53 sec/batch.
2022-10-19 00:41:00,131 step [ 906], lr [0.0000375], embedding loss [ 0.7179], quantization loss [ 0.0393], 0.53 sec/batch.
2022-10-19 00:41:02,225 step [ 907], lr [0.0000375], embedding loss [ 0.7266], quantization loss [ 0.0372], 0.53 sec/batch.
2022-10-19 00:41:04,401 step [ 908], lr [0.0000375], embedding loss [ 0.7267], quantization loss [ 0.0356], 0.53 sec/batch.
2022-10-19 00:41:06,468 step [ 909], lr [0.0000375], embedding loss [ 0.7272], quantization loss [ 0.0431], 0.52 sec/batch.
2022-10-19 00:41:08,544 step [ 910], lr [0.0000375], embedding loss [ 0.7357], quantization loss [ 0.0373], 0.51 sec/batch.
2022-10-19 00:41:10,584 step [ 911], lr [0.0000375], embedding loss [ 0.7332], quantization loss [ 0.0395], 0.51 sec/batch.
2022-10-19 00:41:12,683 step [ 912], lr [0.0000375], embedding loss [ 0.7226], quantization loss [ 0.0380], 0.52 sec/batch.
2022-10-19 00:41:14,781 step [ 913], lr [0.0000375], embedding loss [ 0.7376], quantization loss [ 0.0363], 0.51 sec/batch.
2022-10-19 00:41:16,843 step [ 914], lr [0.0000375], embedding loss [ 0.7311], quantization loss [ 0.0355], 0.52 sec/batch.
2022-10-19 00:41:18,874 step [ 915], lr [0.0000375], embedding loss [ 0.7368], quantization loss [ 0.0401], 0.52 sec/batch.
2022-10-19 00:41:20,995 step [ 916], lr [0.0000375], embedding loss [ 0.7398], quantization loss [ 0.0388], 0.52 sec/batch.
2022-10-19 00:41:23,143 step [ 917], lr [0.0000375], embedding loss [ 0.7288], quantization loss [ 0.0384], 0.53 sec/batch.
2022-10-19 00:41:25,225 step [ 918], lr [0.0000375], embedding loss [ 0.7205], quantization loss [ 0.0427], 0.53 sec/batch.
2022-10-19 00:41:27,280 step [ 919], lr [0.0000375], embedding loss [ 0.7303], quantization loss [ 0.0378], 0.52 sec/batch.
2022-10-19 00:41:29,366 step [ 920], lr [0.0000375], embedding loss [ 0.7303], quantization loss [ 0.0360], 0.53 sec/batch.
2022-10-19 00:41:31,416 step [ 921], lr [0.0000375], embedding loss [ 0.7169], quantization loss [ 0.0389], 0.50 sec/batch.
2022-10-19 00:41:33,483 step [ 922], lr [0.0000375], embedding loss [ 0.7192], quantization loss [ 0.0349], 0.52 sec/batch.
2022-10-19 00:41:35,558 step [ 923], lr [0.0000375], embedding loss [ 0.7273], quantization loss [ 0.0359], 0.52 sec/batch.
2022-10-19 00:41:37,651 step [ 924], lr [0.0000375], embedding loss [ 0.7300], quantization loss [ 0.0327], 0.53 sec/batch.
2022-10-19 00:41:39,716 step [ 925], lr [0.0000375], embedding loss [ 0.7436], quantization loss [ 0.0334], 0.53 sec/batch.
2022-10-19 00:41:41,817 step [ 926], lr [0.0000375], embedding loss [ 0.7316], quantization loss [ 0.0386], 0.53 sec/batch.
2022-10-19 00:41:43,879 step [ 927], lr [0.0000375], embedding loss [ 0.7256], quantization loss [ 0.0360], 0.52 sec/batch.
2022-10-19 00:41:45,942 step [ 928], lr [0.0000375], embedding loss [ 0.7276], quantization loss [ 0.0390], 0.53 sec/batch.
2022-10-19 00:41:47,992 step [ 929], lr [0.0000375], embedding loss [ 0.7318], quantization loss [ 0.0398], 0.51 sec/batch.
2022-10-19 00:41:50,024 step [ 930], lr [0.0000375], embedding loss [ 0.7432], quantization loss [ 0.0407], 0.51 sec/batch.
2022-10-19 00:41:52,090 step [ 931], lr [0.0000375], embedding loss [ 0.7323], quantization loss [ 0.0359], 0.53 sec/batch.
2022-10-19 00:41:54,159 step [ 932], lr [0.0000375], embedding loss [ 0.7199], quantization loss [ 0.0402], 0.52 sec/batch.
2022-10-19 00:41:56,225 step [ 933], lr [0.0000375], embedding loss [ 0.7354], quantization loss [ 0.0447], 0.52 sec/batch.
2022-10-19 00:41:58,251 step [ 934], lr [0.0000375], embedding loss [ 0.7259], quantization loss [ 0.0397], 0.51 sec/batch.
2022-10-19 00:42:00,319 step [ 935], lr [0.0000375], embedding loss [ 0.7241], quantization loss [ 0.0376], 0.53 sec/batch.
2022-10-19 00:42:02,411 step [ 936], lr [0.0000375], embedding loss [ 0.7371], quantization loss [ 0.0423], 0.53 sec/batch.
2022-10-19 00:42:04,508 step [ 937], lr [0.0000375], embedding loss [ 0.7258], quantization loss [ 0.0399], 0.53 sec/batch.
2022-10-19 00:42:06,581 step [ 938], lr [0.0000375], embedding loss [ 0.7350], quantization loss [ 0.0394], 0.53 sec/batch.
2022-10-19 00:42:08,651 step [ 939], lr [0.0000375], embedding loss [ 0.7345], quantization loss [ 0.0329], 0.52 sec/batch.
2022-10-19 00:42:10,685 step [ 940], lr [0.0000375], embedding loss [ 0.7407], quantization loss [ 0.0384], 0.52 sec/batch.
2022-10-19 00:42:12,749 step [ 941], lr [0.0000375], embedding loss [ 0.7382], quantization loss [ 0.0339], 0.52 sec/batch.
2022-10-19 00:42:14,748 step [ 942], lr [0.0000375], embedding loss [ 0.7314], quantization loss [ 0.0411], 0.52 sec/batch.
2022-10-19 00:42:16,914 step [ 943], lr [0.0000375], embedding loss [ 0.7019], quantization loss [ 0.0345], 0.53 sec/batch.
2022-10-19 00:42:18,998 step [ 944], lr [0.0000375], embedding loss [ 0.7297], quantization loss [ 0.0344], 0.52 sec/batch.