ParlAI框架实践

训练seq2seq模型：

?

1	parlai train_model --task cornell_movie --model seq2seq --model-file tmp/model_s2s --batchsize 8 --rnn-class gru --hiddensize 200 --numlayers 2 --bidirectional True --attention dot --attention-time post --lookuptable enc_dec --num-epochs 6 --optimizer adam --learningrate 1e-3

本地交互模式：

?

1	parlai interactive --model-file zoo:dodecadialogue/empathetic_dialogues_ft/model --inference beam --beam-size 5 --beam-min-length 10 --beam-block-ngram 3 --beam-context-block-ngram 3

格式化数据集：

?

1	python parlai/scripts/convert_data_to_parlai_format.py --task cornell_movie --outfile tmp.txt

?

1	python parlai/scripts/convert_data_to_parlai_format.py -t dailydialog --outfile make_data/dailydialog.train --datatype train

构建字典

?

1	parlai build_dict -t cornell_movie --dict-file temp_dict_by_nltk.txt --dict-lower True --dict_tokenizer nltk

消息传递过程：

?

1 2 3 4

query = teacher.act() student.observe(query) reply = student.act() teacher.observe(reply)

python 打印调用栈

?

1 2	import traceback traceback.print_stack()

list of metrics

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

accuracy: Exact match text accuracy bleu-4: BLEU-4 of the generation, under a standardized (model-independent) tokenizer clen: Average length of context in number of tokens clip: Fraction of batches with clipped gradients ctpb: Context tokens per batch ctps: Context tokens per second ctrunc: Fraction of samples with some context truncation ctrunclen: Average length of context tokens truncated exps: Examples per second exs: Number of examples processed since last print f1: Unigram F1 overlap, under a standardized (model-independent) tokenizer gnorm: Gradient norm gpu_mem: Fraction of GPU memory used. May slightly underestimate true value. hits@1: Fraction of correct choices in 1 guess. (Similar to recall@K) hits@5: Fraction of correct choices in 5 guesses. (Similar to recall@K) interdistinct-1: Fraction of n-grams unique across all generations interdistinct-2: Fraction of n-grams unique across all generations intradictinct-2: Fraction of n-grams unique within each utterance intradistinct-1: Fraction of n-grams unique within each utterance jga: Joint Goal Accuracy llen: Average length of label in number of tokens loss: Loss lr: The most recent learning rate applied ltpb: Label tokens per batch ltps: Label tokens per second ltrunc: Fraction of samples with some label truncation ltrunclen: Average length of label tokens truncated rouge-1: ROUGE metrics rouge-2: ROUGE metrics rouge-L: ROUGE metrics token_acc: Token-wise accuracy (generative only) token_em: Utterance-level token accuracy. Roughly corresponds to perfection under greedy search (generative only) total_train_updates: Number of SGD steps taken across all batches tpb: Total tokens (context + label) per batch tps: Total tokens (context + label) per second ups: Updates per second (approximate)

print(train_report)

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

{     'exs': SumMetric(400),     'clen': AverageMetric(32.88),     'ctrunc': AverageMetric(0),     'ctrunclen': AverageMetric(0),     'llen': AverageMetric(13.43),     'ltrunc': AverageMetric(0),     'ltrunclen': AverageMetric(0),     'loss': AverageMetric(9.64),     'ppl': PPLMetric(1.536e+04),     'token_acc': AverageMetric(0.1015),     'token_em': AverageMetric(0),     'exps': GlobalTimerMetric(107.3),     'ltpb': GlobalAverageMetric(107.4),     'ltps': GlobalTimerMetric(1441),     'ctpb': GlobalAverageMetric(263.1),     'ctps': GlobalTimerMetric(3527),     'tpb': GlobalAverageMetric(370.5),     'tps': GlobalTimerMetric(4968),     'ups': GlobalTimerMetric(13.41),     'gnorm': GlobalAverageMetric(3.744),     'clip': GlobalAverageMetric(1),     'lr': GlobalAverageMetric(1),     'gpu_mem': GlobalAverageMetric(0.2491),     'total_train_updates': GlobalFixedMetric(50) }

torch_agent.py的batch_act调用栈

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')())   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser)   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 939, in run   return self.train_loop.train()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 903, in train   for _train_log in self.train_steps():   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 804, in train_steps   world.parley()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 867, in parley   batch_act = self.batch_act(agent_idx, batch_observations[agent_idx])   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 835, in batch_act   batch_actions = a.batch_act(batch_observation)     File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/torch_agent.py", line 2128, in batch_act   traceback.print_stack()

print(batch_reply)

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

[ {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(285), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(20), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(10.44), 'ppl': PPLMetric(3.43e+04), 'token_acc': AverageMetric(0), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(10), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(33), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(10.62), 'ppl': PPLMetric(4.108e+04), 'token_acc': AverageMetric(0.06061), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(52), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(4), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(9.659), 'ppl': PPLMetric(1.565e+04), 'token_acc': AverageMetric(0), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(60), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(3), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(8.532), 'ppl': PPLMetric(5076), 'token_acc': AverageMetric(0.3333), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(9), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(24), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(10.06), 'ppl': PPLMetric(2.339e+04), 'token_acc': AverageMetric(0.125), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(14), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(20), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(8.522), 'ppl': PPLMetric(5024), 'token_acc': AverageMetric(0.4), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(5), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(21), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(10.05), 'ppl': PPLMetric(2.314e+04), 'token_acc': AverageMetric(0.1905), 'token_em': AverageMetric(0)}},   {'id': 'Seq2Seq', 'episode_done': False, 'metrics': {'clen': AverageMetric(12), 'ctrunc': AverageMetric(0), 'ctrunclen': AverageMetric(0), 'llen': AverageMetric(3), 'ltrunc': AverageMetric(0), 'ltrunclen': AverageMetric(0), 'loss': AverageMetric(10.15), 'ppl': PPLMetric(2.56e+04), 'token_acc': AverageMetric(0), 'token_em': AverageMetric(0)}} ]

batch交互过程：

metrics.report调用栈

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71

File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')())    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser)    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 941, in run   return self.train_loop.train()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 905, in train   for _train_log in self.train_steps():    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 842, in train_steps   yield self.log()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 751, in log   train_report = self.world.report()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 963, in report   return self.world.report()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 392, in report   m = a.report()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/teachers.py", line 225, in report   return self.metrics.report()    File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/metrics.py", line 914, in report   traceback.print_stack()   File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')())   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser)   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 941, in run   return self.train_loop.train()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 905, in train   for _train_log in self.train_steps():   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 842, in train_steps   yield self.log()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 751, in log   train_report = self.world.report()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 963, in report   return self.world.report()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 392, in report   m = a.report()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/torch_agent.py", line 1172, in report   report = self.global_metrics.report()     File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/metrics.py", line 914, in report   traceback.print_stack()

clear metric的调用栈：

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75

File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')())   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser)   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 941, in run   return self.train_loop.train()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 905, in train   for _train_log in self.train_steps():   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 842, in train_steps   yield self.log()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 753, in log   self.world.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 977, in reset_metrics   self.world.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 272, in reset_metrics   a.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/teachers.py", line 239, in reset_metrics   self.metrics.clear()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/metrics.py", line 934, in clear   traceback.print_stack()     File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')())   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser)   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 941, in run   return self.train_loop.train()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 905, in train   for _train_log in self.train_steps():   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 842, in train_steps   yield self.log()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/scripts/train_model.py", line 753, in log   self.world.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 977, in reset_metrics   self.world.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/worlds.py", line 272, in reset_metrics   a.reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/torch_generator_agent.py", line 638, in reset_metrics   super().reset_metrics()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/torch_agent.py", line 2103, in reset_metrics   self.global_metrics.clear()   File "/mnt/hdd2/yanghh/ParlAI-master/parlai/core/metrics.py", line 934, in clear   traceback.print_stack()

eval_step()调用栈：　

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')()) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 935, in run   return self.train_loop.train() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 899, in train   for _train_log in self.train_steps(): File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 850, in train_steps   stop_training = self.validate() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 500, in validate   self.valid_worlds, opt, 'valid', opt['validation_max_exs'] File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 627, in _run_eval   task_report = self._run_single_eval(opt, v_world, max_exs_per_worker) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 593, in _run_single_eval   valid_world.parley() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/worlds.py", line 865, in parley   batch_act = self.batch_act(agent_idx, batch_observations[agent_idx]) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/worlds.py", line 833, in batch_act   batch_actions = a.batch_act(batch_observation) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/torch_agent.py", line 2208, in batch_act   traceback.print_stack()

_set_text_vec调用栈：

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

File "/home/lee/anaconda3/envs/pariai/bin/parlai", line 33, in <module>   sys.exit(load_entry_point('parlai', 'console_scripts', 'parlai')()) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/__main__.py", line 14, in main   superscript_main() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/script.py", line 324, in superscript_main   return SCRIPT_REGISTRY[cmd].klass._run_from_parser_and_opt(opt, parser) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/script.py", line 107, in _run_from_parser_and_opt   return script.run() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 935, in run   return self.train_loop.train() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 899, in train   for _train_log in self.train_steps(): File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/scripts/train_model.py", line 802, in train_steps   world.parley() File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/worlds.py", line 873, in parley   obs = self.batch_observe(other_index, batch_act, agent_idx) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/worlds.py", line 817, in batch_observe   observation = agents[index].observe(observation) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/torch_agent.py", line 1855, in observe   label_truncate=self.label_truncate, File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/torch_generator_agent.py", line 656, in vectorize   return super().vectorize(*args, **kwargs) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/torch_agent.py", line 1590, in vectorize   self._set_text_vec(obs, history, text_truncate) File "/mnt/hdd2/yanghh/experiments/ParlAI-master/parlai/core/torch_agent.py", line 1439, in _set_text_vec   traceback.print_stack()

Transformer某一层的参数：

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

"encoder.layers.6.attention.q_lin.weight", "encoder.layers.6.attention.q_lin.bias", "encoder.layers.6.attention.k_lin.weight", "encoder.layers.6.attention.k_lin.bias", "encoder.layers.6.attention.v_lin.weight", "encoder.layers.6.attention.v_lin.bias", "encoder.layers.6.attention.out_lin.weight", "encoder.layers.6.attention.out_lin.bias", "encoder.layers.6.norm1.weight", "encoder.layers.6.norm1.bias", "encoder.layers.6.ffn.lin1.weight", "encoder.layers.6.ffn.lin1.bias", "encoder.layers.6.ffn.lin2.weight", "encoder.layers.6.ffn.lin2.bias", "encoder.layers.6.norm2.weight", "encoder.layers.6.norm2.bias",   "decoder.layers.6.self_attention.q_lin.weight", "decoder.layers.6.self_attention.q_lin.bias", "decoder.layers.6.self_attention.k_lin.weight", "decoder.layers.6.self_attention.k_lin.bias", "decoder.layers.6.self_attention.v_lin.weight", "decoder.layers.6.self_attention.v_lin.bias", "decoder.layers.6.self_attention.out_lin.weight", "decoder.layers.6.self_attention.out_lin.bias", "decoder.layers.6.norm1.weight", "decoder.layers.6.norm1.bias", "decoder.layers.6.encoder_attention.q_lin.weight", "decoder.layers.6.encoder_attention.q_lin.bias", "decoder.layers.6.encoder_attention.k_lin.weight", "decoder.layers.6.encoder_attention.k_lin.bias", "decoder.layers.6.encoder_attention.v_lin.weight", "decoder.layers.6.encoder_attention.v_lin.bias", "decoder.layers.6.encoder_attention.out_lin.weight", "decoder.layers.6.encoder_attention.out_lin.bias", "decoder.layers.6.norm2.weight", "decoder.layers.6.norm2.bias", "decoder.layers.6.ffn.lin1.weight", "decoder.layers.6.ffn.lin1.bias", "decoder.layers.6.ffn.lin2.weight", "decoder.layers.6.ffn.lin2.bias", "decoder.layers.6.norm3.weight", "decoder.layers.6.norm3.bias",

　　

　　

 

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306

[ training... ]         fffffffffff ['\n who saved you ?'] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. =================================== gggggggggggg ["i __unk__ . i had i my my i i ' i had i i my . ' . ."] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . +++++++++++++++++++++++++++++++++++ fffffffffff ['\n who saved you ?'] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. =================================== gggggggggggg ["i __unk__ . i had i my my i i ' i had i i my . ' . ."] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . +++++++++++++++++++++++++++++++++++ fffffffffff ['\n who saved you ?'] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. =================================== gggggggggggg ["i __unk__ . i had i my my i i ' i had i i my . ' . ."] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . +++++++++++++++++++++++++++++++++++ fffffffffff ['\n who saved you ?'] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. =================================== gggggggggggg ["i __unk__ . i had i my my i i ' i had i i my . ' . ."] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . +++++++++++++++++++++++++++++++++++ fffffffffff ['\n who saved you ?'] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. =================================== gggggggggggg ["i __unk__ . i had i my my i i ' i had i i my . ' . ."] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . +++++++++++++++++++++++++++++++++++         fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! =================================== gggggggggggg ["that , , that ' s a , i . i"] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m +++++++++++++++++++++++++++++++++++ fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! =================================== gggggggggggg ["that , , that ' s a , i . i"] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m +++++++++++++++++++++++++++++++++++ fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! =================================== gggggggggggg ["that , , that ' s a , i . i"] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m +++++++++++++++++++++++++++++++++++ fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! =================================== gggggggggggg ["that , , that ' s a , i . i"] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m +++++++++++++++++++++++++++++++++++ fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! =================================== gggggggggggg ["that , , that ' s a , i . i"] +++++++++++++++++++++++++++++++++++ __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ i __unk__ . i had i my my i i ' i had i i my . ' . . __newln__ that ' s nice . i ' m i ' m i had a nice . __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m __newln__ that , , that ' s a , i . i __newln__ i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m i ' m +++++++++++++++++++++++++++++++++++         fffffffffff ["\n who saved you ? \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n my sister thought i was playing around but when she realized i was really in trouble she grabbed me . \n someone paid off my student loans for me ? i ' m shocked ! \n holy cow ! that ' s amazing ! __unk__ ! \n holy cow ! that ' s amazing ! __unk__ ! \n holy cow ! that ' s amazing ! __unk__ ! \n holy cow ! that ' s amazing ! __unk__ ! \n holy cow ! that ' s amazing ! __unk__ ! \n yes , it ' s going to help me out so much !"] =================================== __newln__ who saved you? __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ My sister thought I was playing around but when she realized I was really in trouble she grabbed me. __newln__ Someone paid off my student loans for me? I'm shocked! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Holy cow! That's amazing! Congrats! __newln__ Yes, it's going to help me out so much! __newln__ That's really amazing. How generous. =================================== ^CTraceback (most recent call last):   File "train.py", line 248, in <module>     ReinforceLoop(setup_rl_args().parse_args()).train()   File "train.py", line 224, in train     world.parley()   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/rl/worlds.py", line 88, in parley     actions = self.rollout(initial_action)   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/rl/worlds.py", line 197, in rollout     return roll(initial, self.opt['dialog_rounds'])   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/rl/worlds.py", line 186, in roll     roll(active_action, num_rollouts - 1))   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/rl/worlds.py", line 144, in roll     act = self.static_agent.act()   File "/home/ztl301/yanghh/ParlAI-master/parlai/core/torch_agent.py", line 2290, in act     response = self.batch_act([self.observation])[0]   File "/home/ztl301/yanghh/ParlAI-master/parlai/core/torch_agent.py", line 2386, in batch_act     output = self.eval_step(batch)   File "/home/ztl301/yanghh/ParlAI-master/parlai/core/torch_generator_agent.py", line 902, in eval_step     beam_preds_scores, beams = self._generate(batch, self.beam_size, maxlen)   File "/home/ztl301/yanghh/ParlAI-master/parlai/core/torch_generator_agent.py", line 1242, in _generate     score, incr_state = model.decoder(decoder_input, encoder_states, incr_state)   File "/home/ztl301/anaconda3/envs/bot/lib/python3.7/site-packages/torch-1.10.2-py3.7-linux-x86_64.egg/torch/nn/modules/module.py", line 1102, in _call_impl     return forward_call(*input, **kwargs)   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/transformer/modules/decoder.py", line 390, in forward     tensor, encoder_output, encoder_mask, incr_state   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/transformer/modules/decoder.py", line 346, in forward_layers     incr_state=incr_state.get(idx),   File "/home/ztl301/anaconda3/envs/bot/lib/python3.7/site-packages/torch-1.10.2-py3.7-linux-x86_64.egg/torch/nn/modules/module.py", line 1102, in _call_impl     return forward_call(*input, **kwargs)   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/transformer/modules/decoder.py", line 125, in forward     static_kv=True,   File "/home/ztl301/anaconda3/envs/bot/lib/python3.7/site-packages/torch-1.10.2-py3.7-linux-x86_64.egg/torch/nn/modules/module.py", line 1102, in _call_impl     return forward_call(*input, **kwargs)   File "/home/ztl301/yanghh/ParlAI-master/parlai/agents/transformer/modules/attention.py", line 243, in forward     attentioned = attn_weights.bmm(v) KeyboardInterrupt

　　

　　

 

　　

　　

 

 

 

 

 

未完待续。。。。。。