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Further optimization for NCF model (#17148)
* further optimization for ncf model * fix benchmark script * enhance model optimizer to support general configurations of mlp and neurf models * fix minor typo
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| #!/bin/bash | ||
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| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
|
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| usage() | ||
| { | ||
| echo "usage: bash ./benchmark.sh [[[-p prefix ] [-e epoch] [-d dataset] [-b batch_size] [-i instance] [-c cores/instance]] | [-h]]" | ||
| } | ||
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| while [ $# -gt 0 ]; do | ||
| case "$1" in | ||
| --prefix | -p) | ||
| shift | ||
| PREFIX=$1 | ||
| ;; | ||
| --epoch | -e) | ||
| shift | ||
| EPOCH=$1 | ||
| ;; | ||
| --dataset | -d) | ||
| shift | ||
| DATASET=$1 | ||
| ;; | ||
| --batch-size | -b) | ||
| shift | ||
| BS=$1 | ||
| ;; | ||
| --instance | -i) | ||
| shift | ||
| INS=$1 | ||
| ;; | ||
| --core | -c) | ||
| shift | ||
| CORES=$1 | ||
| ;; | ||
| --help | -h) | ||
| usage | ||
| exit 1 | ||
| ;; | ||
| *) | ||
| usage | ||
| exit 1 | ||
| esac | ||
| shift | ||
| done | ||
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| NUM_SOCKET=`lscpu | grep 'Socket(s)' | awk '{print $NF}'` | ||
| NUM_NUMA_NODE=`lscpu | grep 'NUMA node(s)' | awk '{print $NF}'` | ||
| CORES_PER_SOCKET=`lscpu | grep 'Core(s) per socket' | awk '{print $NF}'` | ||
| NUM_CORES=$((CORES_PER_SOCKET * NUM_SOCKET)) | ||
| CORES_PER_NUMA=$((NUM_CORES / NUM_NUMA_NODE)) | ||
| echo "target machine has $NUM_CORES physical core(s) on $NUM_NUMA_NODE numa nodes of $NUM_SOCKET socket(s)." | ||
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| if [ -z $PREFIX ]; then | ||
| echo "Error: Need a model prefix." | ||
| exit | ||
| fi | ||
| if [ -z $EPOCH ]; then | ||
| echo "Default: set epoch of model parameters to 7." | ||
| EPOCH=7 | ||
| fi | ||
| if [ -z $DATASET ]; then | ||
| echo "Default: set dataset to ml-20m." | ||
| DATASET='ml-20m' | ||
| fi | ||
| if [ -z $INS ]; then | ||
| echo "Default: launch one instance per physical core." | ||
| INS=$NUM_CORES | ||
| fi | ||
| if [ -z $CORES ]; then | ||
| echo "Default: divide full physical cores." | ||
| CORES=$((NUM_CORES / $INS)) | ||
| fi | ||
| if [ -z $BS ]; then | ||
| echo "Default: set batch size to 700." | ||
| BS=700 | ||
| fi | ||
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| echo " cores/instance: $CORES" | ||
| echo " total instances: $INS" | ||
| echo " batch size: $BS" | ||
| echo "" | ||
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| rm NCF_*.log | ||
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| for((i=0;i<$INS;i++)); | ||
| do | ||
| ((a=$i*$CORES)) | ||
| ((b=$a+$CORES-1)) | ||
| memid=$((b/CORES_PER_NUMA)) | ||
| LOG=NCF_$i.log | ||
| echo " $i instance use $a-$b cores with $LOG" | ||
| KMP_AFFINITY=granularity=fine,noduplicates,compact,1,0 \ | ||
| OMP_NUM_THREADS=$CORES \ | ||
| numactl --physcpubind=$a-$b --membind=$memid python ncf.py --batch-size=$BS --dataset=$DATASET --epoch=$EPOCH --benchmark --prefix=$PREFIX 2>&1 | tee $LOG & | ||
| done | ||
| wait | ||
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| grep speed NCF_*.log | awk '{ sum += $(NF-1) }; END { print "Total Performance is " sum " samples/sec"}' |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,81 @@ | ||
| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
| # | ||
| import os | ||
| import time | ||
| import argparse | ||
| import logging | ||
| import math | ||
| import random | ||
| import numpy as np | ||
| import mxnet as mx | ||
| from core.model import get_model | ||
| from core.dataset import NCFTrainData | ||
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| logging.basicConfig(level=logging.DEBUG) | ||
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| parser = argparse.ArgumentParser(description="Run model optimizer.", | ||
| formatter_class=argparse.ArgumentDefaultsHelpFormatter) | ||
| parser.add_argument('--path', nargs='?', default='./data/', | ||
| help='Input data path.') | ||
| parser.add_argument('--dataset', nargs='?', default='ml-20m', | ||
| help='The dataset name.') | ||
| parser.add_argument('--model-prefix', type=str, default='./model/ml-20m/neumf') | ||
| parser.add_argument('--epoch', type=int, default=7, help='parameters epoch') | ||
| parser.add_argument('--model-type', type=str, default='neumf', choices=['neumf', 'gmf', 'mlp'], | ||
| help="mdoel type") | ||
| parser.add_argument('--layers', default='[256, 256, 128, 64]', | ||
| help="list of number hiddens of fc layers in mlp model.") | ||
| parser.add_argument('--factor-size-gmf', type=int, default=64, | ||
| help="outdim of gmf embedding layers.") | ||
| parser.add_argument('--num-hidden', type=int, default=1, | ||
| help="num-hidden of neumf fc layer") | ||
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| head = '%(asctime)-15s %(message)s' | ||
| logging.basicConfig(level=logging.INFO, format=head) | ||
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| # arg parser | ||
| args = parser.parse_args() | ||
| logging.info(args) | ||
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| model_prefix = args.model_prefix | ||
| model_type = args.model_type | ||
| model_layers = eval(args.layers) | ||
| factor_size_gmf = args.factor_size_gmf | ||
| factor_size_mlp = int(model_layers[0]/2) | ||
| num_hidden = args.num_hidden | ||
| train_dataset = NCFTrainData((args.path + args.dataset + '/train-ratings.csv'), nb_neg=4) | ||
| net = get_model(model_type, factor_size_mlp, factor_size_gmf, | ||
| model_layers, num_hidden, train_dataset.nb_users, train_dataset.nb_items, opt=True) | ||
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| raw_params, _ = mx.model.load_params(model_prefix, args.epoch) | ||
| fc_0_weight_split = mx.nd.split(raw_params['fc_0_weight'], axis=1, num_outputs=2) | ||
| fc_0_left = fc_0_weight_split[0] | ||
| fc_0_right = fc_0_weight_split[1] | ||
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| user_weight_fusion = mx.nd.FullyConnected(data = raw_params['mlp_user_weight'], weight=fc_0_left, bias=raw_params['fc_0_bias'], no_bias=False, num_hidden=model_layers[0]) | ||
| item_weight_fusion = mx.nd.FullyConnected(data = raw_params['mlp_item_weight'], weight=fc_0_right, no_bias=True, num_hidden=model_layers[0]) | ||
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| opt_params = raw_params | ||
| del opt_params['mlp_user_weight'] | ||
| del opt_params['mlp_item_weight'] | ||
| del opt_params['fc_0_bias'] | ||
| opt_params['fused_mlp_user_weight'] = user_weight_fusion | ||
| opt_params['fused_mlp_item_weight'] = item_weight_fusion | ||
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| mx.model.save_checkpoint(model_prefix + '-opt', args.epoch, net, opt_params, {}) | ||
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