计算SPICE score报错Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before startin

[mymuli]

你好！
我在AAT里面运行AOA模型的代码，运用下面的代码：
python3.6 train.py --id aoa
--batch_size 10
--beam_size 1
--max_epochs 25
--caption_model aoa
--refine 1
--refine_aoa 1
--use_ff 0
--decoder_type AoA
--use_multi_head 2
--num_heads 8
--multi_head_scale 1
--mean_feats 1
--ctx_drop 1
--dropout_aoa 0.3
--label_smoothing 0.2
--input_json data/cocotalk.json
--input_label_h5 data/cocotalk_label.h5
--input_fc_dir data/cocobu_fc
--input_att_dir data/cocobu_att
--input_box_dir data/cocobu_box
--seq_per_img 5
--learning_rate 2e-4
--num_layers 2
--input_encoding_size 1024
--rnn_size 1024
--learning_rate_decay_start 0
--scheduled_sampling_start 0
--checkpoint_path log_aoa/log_aoa
--save_checkpoint_every 6000
--language_eval 1
--val_images_use -1
--scheduled_sampling_increase_every 5
--scheduled_sampling_max_prob 0.5
--learning_rate_decay_every 3

在epoch=0的过程中，computing SPICE 时，代码报错如下：

`computing SPICE score...
Parsing reference captions
Initiating Stanford parsing pipeline
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator tokenize
[main] INFO edu.stanford.nlp.pipeline.TokenizerAnnotator - TokenizerAnnotator: No tokenizer type provided. Defaulting to PTBTokenizer.
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator ssplit
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator parse
[main] INFO edu.stanford.nlp.parser.common.ParserGrammar - Loading parser from serialized file edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz ...
done [0.3 sec].
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator lemma
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator ner
Loading classifier from edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz ... done [1.0 sec].
Loading classifier from edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf.ser.gz ... done [0.4 sec].
Loading classifier from edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz ... done [0.5 sec].
Threads( StanfordCoreNLP ) #

Threads( StanfordCoreNLP ) #
A fatal error has been detected by the Java Runtime Environment:

SIGSEGV (0xb) at pc=0x00007f0aa67f4e10, pid=12537, tid=0x00007f0a7d4b4700

JRE version: OpenJDK Runtime Environment (8.0_265-b01) (build 1.8.0_265-8u265-b01-0ubuntu2~16.04-b01)
Java VM: OpenJDK 64-Bit Server VM (25.265-b01 mixed mode linux-amd64 compressed oops)
Problematic frame:
V [libjvm.so+0x408e10]

Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again

An error report file with more information is saved as:
/home/muli/myExpe--caption/AAT/coco-caption/pycocoevalcap/spice/hs_err_pid12537.log

[error occurred during error reporting , id 0xb]

If you would like to submit a bug report, please visit:
http://bugreport.java.com/bugreport/crash.jsp

Traceback (most recent call last):
File "train.py", line 300, in
train(opt)
File "train.py", line 244, in train
val_loss, predictions, lang_stats = eval_utils.eval_split(dp_model, lw_model.crit, loader, eval_kwargs)
File "/home/muli/myExpe--caption/AAT/eval_utils.py", line 173, in eval_split
lang_stats = language_eval(dataset, predictions, eval_kwargs['id'], split)
File "/home/muli/myExpe--caption/AAT/eval_utils.py", line 55, in language_eval
cocoEval.evaluate()
File "coco-caption/pycocoevalcap/eval.py", line 61, in evaluate
score, scores = scorer.compute_score(gts, res)
File "coco-caption/pycocoevalcap/spice/spice.py", line 79, in compute_score
cwd=os.path.dirname(os.path.abspath(file)))
File "/usr/lib/python3.6/subprocess.py", line 311, in check_call
raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['java', '-jar', '-Xmx8G', 'spice-1.0.jar', '/home/muli/myExpe--caption/AAT/coco-caption/pycocoevalcap/spice/tmp/tmpyfgzkyc4', '-cache', '/home/muli/myExpe--caption/AAT/coco-caption/pycocoevalcap/spice/cache/1601606281.2002816', '-out', '/home/muli/myExpe--caption/AAT/coco-caption/pycocoevalcap/spice/tmp/tmp_de8maf_', '-subset', '-silent']' died with <Signals.SIGABRT: 6>.
Terminating BlobFetcher`

请问一下，这个怎么解决呢？
我在运行AAT 模型时，没有报错