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106 lines
5.4 KiB
106 lines
5.4 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""
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BGCF evaluation script.
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"""
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import os
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import datetime
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import mindspore.context as context
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from mindspore.train.serialization import load_checkpoint
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from src.bgcf import BGCF
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from src.utils import BGCFLogger
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from src.config import parser_args
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from src.metrics import BGCFEvaluate
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from src.callback import ForwardBGCF, TestBGCF
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from src.dataset import TestGraphDataset, load_graph
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def evaluation():
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"""evaluation"""
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num_user = train_graph.graph_info()["node_num"][0]
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num_item = train_graph.graph_info()["node_num"][1]
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eval_class = BGCFEvaluate(parser, train_graph, test_graph, parser.Ks)
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for _epoch in range(parser.eval_interval, parser.num_epoch+1, parser.eval_interval):
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bgcfnet_test = BGCF([parser.input_dim, num_user, num_item],
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parser.embedded_dimension,
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parser.activation,
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[0.0, 0.0, 0.0],
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num_user,
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num_item,
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parser.input_dim)
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load_checkpoint(parser.ckptpath + "/bgcf_epoch{}.ckpt".format(_epoch), net=bgcfnet_test)
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forward_net = ForwardBGCF(bgcfnet_test)
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user_reps, item_reps = TestBGCF(forward_net, num_user, num_item, parser.input_dim, test_graph_dataset)
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test_recall_bgcf, test_ndcg_bgcf, \
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test_sedp, test_nov = eval_class.eval_with_rep(user_reps, item_reps, parser)
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if parser.log_name:
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log.write(
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'epoch:%03d, recall_@10:%.5f, recall_@20:%.5f, ndcg_@10:%.5f, ndcg_@20:%.5f, '
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'sedp_@10:%.5f, sedp_@20:%.5f, nov_@10:%.5f, nov_@20:%.5f\n' % (_epoch,
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test_recall_bgcf[1],
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test_recall_bgcf[2],
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test_ndcg_bgcf[1],
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test_ndcg_bgcf[2],
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test_sedp[0],
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test_sedp[1],
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test_nov[1],
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test_nov[2]))
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else:
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print('epoch:%03d, recall_@10:%.5f, recall_@20:%.5f, ndcg_@10:%.5f, ndcg_@20:%.5f, '
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'sedp_@10:%.5f, sedp_@20:%.5f, nov_@10:%.5f, nov_@20:%.5f\n' % (_epoch,
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test_recall_bgcf[1],
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test_recall_bgcf[2],
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test_ndcg_bgcf[1],
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test_ndcg_bgcf[2],
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test_sedp[0],
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test_sedp[1],
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test_nov[1],
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test_nov[2]))
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if __name__ == "__main__":
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context.set_context(mode=context.GRAPH_MODE,
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device_target="Ascend",
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save_graphs=False)
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parser = parser_args()
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os.environ['DEVICE_ID'] = parser.device
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train_graph, test_graph, sampled_graph_list = load_graph(parser.datapath)
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test_graph_dataset = TestGraphDataset(train_graph, sampled_graph_list, num_samples=parser.raw_neighs,
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num_bgcn_neigh=parser.gnew_neighs,
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num_neg=parser.num_neg)
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if parser.log_name:
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now = datetime.datetime.now().strftime("%b_%d_%H_%M_%S")
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name = "bgcf" + '-' + parser.log_name + '-' + parser.dataset
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log_save_path = './log-files/' + name + '/' + now
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log = BGCFLogger(logname=name, now=now, foldername='log-files', copy=False)
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log.open(log_save_path + '/log.train.txt', mode='a')
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for arg in vars(parser):
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log.write(arg + '=' + str(getattr(parser, arg)) + '\n')
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else:
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for arg in vars(parser):
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print(arg + '=' + str(getattr(parser, arg)))
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evaluation()
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