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eval.py
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eval.py
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
import time
import warnings
from collections import defaultdict
import paddle
import numpy as np
import paddle.distributed as dist
from paddle.optimizer.lr import StepDecay
from dataset.reader import read_trigraph
from dataset.dataset import create_dataloaders
from models.ke_model import KGEModel
from models.loss_func import LossFunction
from utils import set_seed, set_logger, print_log
from utils import evaluate
from config import prepare_config
def main():
"""Main function for shallow knowledge embedding methods.
"""
args = prepare_config()
set_seed(args.seed)
set_logger(args)
trigraph = read_trigraph(args.data_path, args.data_name, args.use_dict)
if args.valid_percent < 1:
trigraph.sampled_subgraph(args.valid_percent, dataset='valid')
use_filter_set = args.filter_sample or args.filter_eval or args.weighted_loss
if use_filter_set:
filter_dict = {
'head': trigraph.true_heads_for_tail_rel,
'tail': trigraph.true_tails_for_head_rel
}
else:
filter_dict = None
model = KGEModel(args.model_name, trigraph, args)
_, _, test_loader = create_dataloaders(
trigraph,
args,
filter_dict=filter_dict if use_filter_set else None,
shared_ent_path=model.shared_ent_path if args.mix_cpu_gpu else None)
if args.init_from_ckpt:
state_dict = paddle.load(
os.path.join(args.init_from_ckpt, 'params.pdparams'))
model.set_dict(state_dict)
evaluate(
model,
test_loader,
'test',
filter_dict if args.filter_eval else None,
args.save_path,
data_mode=args.data_name)
if __name__ == '__main__':
main()