ParlAI框架实践

训练seq2seq模型:

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:

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:

python parlai/scripts/convert_data_to_parlai_format.py --task cornell_movie --outfile tmp.txt
python parlai/scripts/convert_data_to_parlai_format.py -t dailydialog --outfile make_data/dailydialog.train --datatype train

构建字典

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:

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

python 打印调用栈

import traceback
traceback.print_stack()

list of metrics

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)

{
    '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

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)

[
{'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

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:

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: 

  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:

  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:

"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",

  

  

 

[ 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。。。。。。

posted @ 2021-05-19 19:29  _yanghh  阅读(181)  评论(0编辑  收藏  举报