RASA框架解析

1、Rasa重要类和方法导入

import os

from rasa.importers.importer import TrainingDataImporter #训练数据加载

from rasa.utils.io import pickle_dump,json_pickle        
from rasa.utils.common import TempDirectoryPath          #数据零时目录路径
from rasa.utils.endpoints import read_endpoint_config    #action_endpoint，endpoint文件读取

from rasa.nlu import components, utils                   #nlu组件模块
from rasa.nlu import config as nlu_config                #nlu config模块
from rasa.nlu.model import Interpreter, Trainer          #nlu模型解析器，训练器接口
from rasa.nlu.train import train as NLU_train            #nlu训练接口
from rasa.nlu.config import RasaNLUModelConfig           #nlu模型config接口
from rasa.nlu.training_data import Message
from rasa.nlu.tokenizers.jieba_tokenizer import JiebaTokenizer

from rasa.core import config as core_config              #core config模块
from rasa.core.domain import Domain                      #core domain接口
from rasa.core.agent import Agent,load_agent             #core Agent接口
from rasa.core.interpreter import RasaNLUInterpreter     #core nlu解析器接口
from rasa.core.channels.channel import UserMessage       #core 用户消息接口
from rasa.core.channels import CollectingOutputChannel   #core 输出消息收集接口

from rasa.core.featurizers import BinarySingleStateFeaturizer
from rasa.core.featurizers import MaxHistoryTrackerFeaturizer

from rasa.train import (
    train, train_async, 
    _train_nlu_with_validated_data    #rasa 模型训练上层接口
)

from parsing_utils import json_dump

2、Rasa项目的原始数据导入

一个Rasa项目，主要数据文件包括：nlu.md, stories.md, domain.yml, config.yml, endpoints.yml, credentials.yml等等。下面导入其中几个关键数据文件：nlu.md, stories.md, domain.yml, config.yml。

2.1、metadata_parsing

domain_file = 'domain.yml'
configs_file = 'config_15.yml'
training_files = 'data'

output_path = 'models/model_15'
model_path = 'models/models_15'

file_importer = TrainingDataImporter.load_from_config(configs_file,domain_file,
                                             training_files)
file_importer.__dict__['_importers'][0].__dict__

{'config': {'language': 'zh',
  'pipeline': [{'name': 'JiebaTokenizer'},
   {'name': 'KashgariEntityExtractor',
    'bert_model_path': 'chinese_L-12_H-768_A-12'},
   {'name': 'RegexExtractor', 'regex_ner_entity': ['EqpType']},
   {'name': 'KashgariIntentClassifier',
    'bert_model_path': 'chinese_L-12_H-768_A-12'}],
  'policies': [{'name': 'TwoStageFallbackPolicy',
    'core_threshold': 0.1,
    'nlu_threshold': 0.1,
    'fallback_core_action_name': 'action_default_fallback',
    'fallback_nlu_action_name': 'action_handoff_to_human',
    'deny_suggestion_intent_name': 'out_of_scope'},
   {'name': 'MemoizationPolicy', 'max_history': 3},
   {'name': 'FormPolicy'},
   {'name': 'MappingPolicy'},
   {'name': 'KerasPolicy',
    'featurizer': [{'name': 'MaxHistoryTrackerFeaturizer',
      'max_history': 5,
      'state_featurizer': [{'name': 'BinarySingleStateFeaturizer'}]}]}]},
 '_domain_path': 'domain.yml',
 '_story_files': ['data\\stories.md'],
 '_nlu_files': ['data\\nlu.md']}

返回类 rasa.nlu.training_data.training_data.TrainingData

domain = await file_importer.get_domain() 
#domain.__dict__
domain

<rasa.core.domain.Domain at 0x1a3bf72cf08>

stories.md文件，被解析成story_steps：它主要由StoryStep列表组成，一条StoryStep对应一个story，events代表每个story中bot和用户产生的对话动作 stories_data.as_story_string

stories_data = await file_importer.get_stories() #返回类 rasa.nlu.training_data.training_data.TrainingData
stories_data.__dict__

{'story_steps': [StoryStep(block_name='equipFaultDiag_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF73A248>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6B41C8>, <rasa.core.events.Form object at 0x000001A3BF6ABFC8>, <rasa.core.events.Form object at 0x000001A3BF26CB88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF2646C8>]),
  StoryStep(block_name='sysFaultDiag_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF7259C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF73A4C8>, <rasa.core.events.Form object at 0x000001A3BDB57D48>, <rasa.core.events.Form object at 0x000001A3BF725848>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7208C8>]),
  StoryStep(block_name='equipFaultDiag Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF725808>, <rasa.core.events.ActionExecuted object at 0x000001A3BF705C88>, <rasa.core.events.Form object at 0x000001A3BF705148>, <rasa.core.events.SlotSet object at 0x000001A3BF705248>, <rasa.core.events.SlotSet object at 0x000001A3BF8C1BC8>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB808>, <rasa.core.events.SlotSet object at 0x000001A3BF7ABF48>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB708>, <rasa.core.events.SlotSet object at 0x000001A3BF7ABA48>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB788>, <rasa.core.events.SlotSet object at 0x000001A3BF857808>, <rasa.core.events.SlotSet object at 0x000001A3BF7154C8>, <rasa.core.events.Form object at 0x000001A3BF7A8108>, <rasa.core.events.SlotSet object at 0x000001A3BF7A2408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A2F08>]),
  StoryStep(block_name='equipFaultDiag Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF7A2F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A25C8>, <rasa.core.events.Form object at 0x000001A3BF7A27C8>, <rasa.core.events.UserUttered object at 0x000001A3BF87D348>, <rasa.core.events.SlotSet object at 0x000001A3BF7A2D48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A2308>, <rasa.core.events.UserUttered object at 0x000001A3BF70A308>, <rasa.core.events.SlotSet object at 0x000001A3BF70F8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BC336048>, <rasa.core.events.SlotSet object at 0x000001A3BF7A7508>, <rasa.core.events.UserUttered object at 0x000001A3BF6F1648>, <rasa.core.events.SlotSet object at 0x000001A3BF7A7448>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6F1908>, <rasa.core.events.SlotSet object at 0x000001A3BF852B48>, <rasa.core.events.UserUttered object at 0x000001A3BF852608>, <rasa.core.events.SlotSet object at 0x000001A3BF852D08>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8526C8>, <rasa.core.events.Form object at 0x000001A3BF7A1F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8A29C8>]),
  StoryStep(block_name='equipFaultDiag Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8B9988>, <rasa.core.events.SlotSet object at 0x000001A3BF877508>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9608>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9748>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9888>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8B9948>, <rasa.core.events.Form object at 0x000001A3BF8B9CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B99C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9E08>, <rasa.core.events.Form object at 0x000001A3BF8B9E88>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9F88>]),
  StoryStep(block_name='equipFaultDiag Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8AB1C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB2C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB348>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8AB3C8>, <rasa.core.events.Form object at 0x000001A3BF8AB508>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB448>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB588>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB5C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8AB6C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8AB648>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB848>, <rasa.core.events.Form object at 0x000001A3BF8AB7C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB908>]),
  StoryStep(block_name='equipFaultDiag Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8ABA48>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB948>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABB48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8ABBC8>, <rasa.core.events.Form object at 0x000001A3BF8ABC88>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABD08>, <rasa.core.events.UserUttered object at 0x000001A3BF8ABEC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABD88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8ABF08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3048>, <rasa.core.events.UserUttered object at 0x000001A3BF8D3088>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABFC8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D31C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3308>, <rasa.core.events.Form object at 0x000001A3BF8D3288>, <rasa.core.events.SlotSet object at 0x000001A3BF8D33C8>]),
  StoryStep(block_name='equipMaintenance path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8AB8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3408>, <rasa.core.events.Form object at 0x000001A3BF8D3588>, <rasa.core.events.Form object at 0x000001A3BF8D34C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3648>]),
  StoryStep(block_name='sysMaintenance_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D3548>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3748>, <rasa.core.events.Form object at 0x000001A3BF8D3948>, <rasa.core.events.Form object at 0x000001A3BF8D37C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3A08>]),
  StoryStep(block_name='equipMaintenance Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D38C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3A48>, <rasa.core.events.Form object at 0x000001A3BF8D3CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3DC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3E48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3F08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6088>, <rasa.core.events.Form object at 0x000001A3BF8D6108>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6248>]),
  StoryStep(block_name='equipMaintenance Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8B9F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6308>, <rasa.core.events.Form object at 0x000001A3BF8D6588>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6688>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D66C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6848>, <rasa.core.events.SlotSet object at 0x000001A3BF8D68C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6888>, <rasa.core.events.SlotSet object at 0x000001A3BF8D67C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6B08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6988>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6D08>, <rasa.core.events.Form object at 0x000001A3BF8D6C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6DC8>]),
  StoryStep(block_name='equipMaintenance Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D6F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6E08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8088>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D82C8>, <rasa.core.events.Form object at 0x000001A3BF8D8408>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8348>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8488>, <rasa.core.events.Form object at 0x000001A3BF8D84C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8588>]),
  StoryStep(block_name='equipMaintenance Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D86C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D85C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D87C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D8A08>, <rasa.core.events.Form object at 0x000001A3BF8D8B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8A88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8BC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8C08>, <rasa.core.events.Form object at 0x000001A3BF8D8C88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8B08>]),
  StoryStep(block_name='equipMaintenance Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D8E48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF108>, <rasa.core.events.Form object at 0x000001A3BF8DF208>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF188>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF288>, <rasa.core.events.UserUttered object at 0x000001A3BF8DF448>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF308>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF488>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF608>, <rasa.core.events.Form object at 0x000001A3BF8DF588>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF6C8>]),
  StoryStep(block_name='equipOperation path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8DF7C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF708>, <rasa.core.events.Form object at 0x000001A3BF8DFA88>, <rasa.core.events.Form object at 0x000001A3BF8DF908>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DFB48>]),
  StoryStep(block_name='sysOperation_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8DFB88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF688>, <rasa.core.events.Form object at 0x000001A3BF8DFEC8>, <rasa.core.events.Form object at 0x000001A3BF8DFD48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DFF88>]),
  StoryStep(block_name='equipOperation Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E1048>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E10C8>, <rasa.core.events.Form object at 0x000001A3BF8E1348>, <rasa.core.events.SlotSet object at 0x000001A3BF8E11C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E13C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1448>, <rasa.core.events.SlotSet object at 0x000001A3BF8E14C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1588>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1648>, <rasa.core.events.SlotSet object at 0x000001A3BF8E16C8>, <rasa.core.events.Form object at 0x000001A3BF8E1788>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1848>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1888>]),
  StoryStep(block_name='equipOperation Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E1948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E19C8>, <rasa.core.events.Form object at 0x000001A3BF8E1C48>, <rasa.core.events.UserUttered object at 0x000001A3BF8E1D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1AC8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1D88>, <rasa.core.events.UserUttered object at 0x000001A3BF8E1F08>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1F88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5088>, <rasa.core.events.UserUttered object at 0x000001A3BF8E5208>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1E88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E5248>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5408>, <rasa.core.events.Form object at 0x000001A3BF8E5348>, <rasa.core.events.SlotSet object at 0x000001A3BF8E54C8>]),
  StoryStep(block_name='equipOperation Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E5688>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5508>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5788>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5908>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E59C8>, <rasa.core.events.Form object at 0x000001A3BF8E5B08>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5A48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5B88>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5BC8>, <rasa.core.events.Form object at 0x000001A3BF8E5C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5AC8>]),
  StoryStep(block_name='equipOperation Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E5EC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7188>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7248>, <rasa.core.events.Form object at 0x000001A3BF8E7388>, <rasa.core.events.SlotSet object at 0x000001A3BF8E72C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7408>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7448>, <rasa.core.events.Form object at 0x000001A3BF8E74C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7348>]),
  StoryStep(block_name='equipOperation Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E76C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E75C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E77C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7948>, <rasa.core.events.Form object at 0x000001A3BF8E7A48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E79C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7AC8>, <rasa.core.events.UserUttered object at 0x000001A3BF8E7C88>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7B48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7E48>, <rasa.core.events.Form object at 0x000001A3BF8E7DC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7F08>]),
  StoryStep(block_name='equipInstall path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB088>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7F48>, <rasa.core.events.Form object at 0x000001A3BF8EB308>, <rasa.core.events.Form object at 0x000001A3BF8EB188>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB3C8>]),
  StoryStep(block_name='sysInstall_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB508>, <rasa.core.events.Form object at 0x000001A3BF8EB7C8>, <rasa.core.events.Form object at 0x000001A3BF8EB608>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB888>]),
  StoryStep(block_name='equipInstall Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB388>, <rasa.core.events.Form object at 0x000001A3BF8EBC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBA88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBC88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBD08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBD88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBE48>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBF08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBF88>, <rasa.core.events.Form object at 0x000001A3BF8EE048>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE148>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE188>]),
  StoryStep(block_name='equipInstall Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EE208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB848>, <rasa.core.events.Form object at 0x000001A3BF8EE548>, <rasa.core.events.UserUttered object at 0x000001A3BF8EE648>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE3C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE688>, <rasa.core.events.UserUttered object at 0x000001A3BF8EE808>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE888>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE848>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE788>, <rasa.core.events.UserUttered object at 0x000001A3BF8EEAC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EEB08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EECC8>, <rasa.core.events.Form object at 0x000001A3BF8EEC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EED88>]),
  StoryStep(block_name='equipInstall Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EEF48>, <rasa.core.events.SlotSet object at 0x000001A3BF8EEDC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1088>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F12C8>, <rasa.core.events.Form object at 0x000001A3BF8F1408>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1348>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1488>, <rasa.core.events.SlotSet object at 0x000001A3BF8F14C8>, <rasa.core.events.Form object at 0x000001A3BF8F1548>, <rasa.core.events.SlotSet object at 0x000001A3BF8F13C8>]),
  StoryStep(block_name='equipInstall Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F17C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1648>, <rasa.core.events.SlotSet object at 0x000001A3BF8F18C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1A48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F1B08>, <rasa.core.events.Form object at 0x000001A3BF8F1C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1B88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1D08>, <rasa.core.events.Form object at 0x000001A3BF8F1D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1C08>]),
  StoryStep(block_name='equipInstall Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F1F88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1E88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F50C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F5248>, <rasa.core.events.Form object at 0x000001A3BF8F5348>, <rasa.core.events.SlotSet object at 0x000001A3BF8F52C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F53C8>, <rasa.core.events.UserUttered object at 0x000001A3BF70A108>, <rasa.core.events.SlotSet object at 0x000001A3BF70AB08>, <rasa.core.events.ActionExecuted object at 0x000001A3BF70A608>, <rasa.core.events.SlotSet object at 0x000001A3BF733748>, <rasa.core.events.Form object at 0x000001A3BF8BC808>, <rasa.core.events.SlotSet object at 0x000001A3BF87D5C8>]),
  StoryStep(block_name='deviceParameter path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F1E48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF87D508>, <rasa.core.events.Form object at 0x000001A3BF876E88>, <rasa.core.events.Form object at 0x000001A3BF876E48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6F1BC8>])],
 'step_lookup': {'30_59cb32cb69a14425b5ec7ceb21dfab88': StoryStep(block_name='equipFaultDiag_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF73A248>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6B41C8>, <rasa.core.events.Form object at 0x000001A3BF6ABFC8>, <rasa.core.events.Form object at 0x000001A3BF26CB88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF2646C8>]),
  '31_5436161f1ba141d79006debc4e61a004': StoryStep(block_name='sysFaultDiag_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF7259C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF73A4C8>, <rasa.core.events.Form object at 0x000001A3BDB57D48>, <rasa.core.events.Form object at 0x000001A3BF725848>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7208C8>]),
  '32_6ab17da8458f44db8c4f0d809fb92cc6': StoryStep(block_name='equipFaultDiag Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF725808>, <rasa.core.events.ActionExecuted object at 0x000001A3BF705C88>, <rasa.core.events.Form object at 0x000001A3BF705148>, <rasa.core.events.SlotSet object at 0x000001A3BF705248>, <rasa.core.events.SlotSet object at 0x000001A3BF8C1BC8>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB808>, <rasa.core.events.SlotSet object at 0x000001A3BF7ABF48>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB708>, <rasa.core.events.SlotSet object at 0x000001A3BF7ABA48>, <rasa.core.events.SlotSet object at 0x000001A3BF7AB788>, <rasa.core.events.SlotSet object at 0x000001A3BF857808>, <rasa.core.events.SlotSet object at 0x000001A3BF7154C8>, <rasa.core.events.Form object at 0x000001A3BF7A8108>, <rasa.core.events.SlotSet object at 0x000001A3BF7A2408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A2F08>]),
  '33_ddbbf2fcb04745428807e5f0591ff77c': StoryStep(block_name='equipFaultDiag Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF7A2F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A25C8>, <rasa.core.events.Form object at 0x000001A3BF7A27C8>, <rasa.core.events.UserUttered object at 0x000001A3BF87D348>, <rasa.core.events.SlotSet object at 0x000001A3BF7A2D48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF7A2308>, <rasa.core.events.UserUttered object at 0x000001A3BF70A308>, <rasa.core.events.SlotSet object at 0x000001A3BF70F8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BC336048>, <rasa.core.events.SlotSet object at 0x000001A3BF7A7508>, <rasa.core.events.UserUttered object at 0x000001A3BF6F1648>, <rasa.core.events.SlotSet object at 0x000001A3BF7A7448>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6F1908>, <rasa.core.events.SlotSet object at 0x000001A3BF852B48>, <rasa.core.events.UserUttered object at 0x000001A3BF852608>, <rasa.core.events.SlotSet object at 0x000001A3BF852D08>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8526C8>, <rasa.core.events.Form object at 0x000001A3BF7A1F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8A29C8>]),
  '34_e543523258f14563926bc7934c17b936': StoryStep(block_name='equipFaultDiag Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8B9988>, <rasa.core.events.SlotSet object at 0x000001A3BF877508>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9608>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9748>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9888>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8B9948>, <rasa.core.events.Form object at 0x000001A3BF8B9CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B99C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9E08>, <rasa.core.events.Form object at 0x000001A3BF8B9E88>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9F88>]),
  '35_4b422fd5799b48d5b0d857e862111ec3': StoryStep(block_name='equipFaultDiag Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8AB1C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8B9FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB2C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB348>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8AB3C8>, <rasa.core.events.Form object at 0x000001A3BF8AB508>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB448>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB588>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB5C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8AB6C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8AB648>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB848>, <rasa.core.events.Form object at 0x000001A3BF8AB7C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB908>]),
  '36_92b0ebd96d034401bc6cf5e6631ee0aa': StoryStep(block_name='equipFaultDiag Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8ABA48>, <rasa.core.events.SlotSet object at 0x000001A3BF8AB948>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABB48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8ABBC8>, <rasa.core.events.Form object at 0x000001A3BF8ABC88>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABD08>, <rasa.core.events.UserUttered object at 0x000001A3BF8ABEC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABD88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8ABF08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3048>, <rasa.core.events.UserUttered object at 0x000001A3BF8D3088>, <rasa.core.events.SlotSet object at 0x000001A3BF8ABFC8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D31C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3308>, <rasa.core.events.Form object at 0x000001A3BF8D3288>, <rasa.core.events.SlotSet object at 0x000001A3BF8D33C8>]),
  '37_32e443a972d34a6c93342ffa794248e0': StoryStep(block_name='equipMaintenance path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8AB8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3408>, <rasa.core.events.Form object at 0x000001A3BF8D3588>, <rasa.core.events.Form object at 0x000001A3BF8D34C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3648>]),
  '38_ff72b1e474eb4a85b76bf1a9cfa886e9': StoryStep(block_name='sysMaintenance_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D3548>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3748>, <rasa.core.events.Form object at 0x000001A3BF8D3948>, <rasa.core.events.Form object at 0x000001A3BF8D37C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3A08>]),
  '39_4ce9f23606444e6e8be2cbceb62f4eec': StoryStep(block_name='equipMaintenance Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D38C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D3A48>, <rasa.core.events.Form object at 0x000001A3BF8D3CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3DC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3E48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3F08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D3FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6088>, <rasa.core.events.Form object at 0x000001A3BF8D6108>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6248>]),
  '40_a171f49097f9400993a175980c61fc91': StoryStep(block_name='equipMaintenance Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8B9F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6308>, <rasa.core.events.Form object at 0x000001A3BF8D6588>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6688>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D66C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6848>, <rasa.core.events.SlotSet object at 0x000001A3BF8D68C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6888>, <rasa.core.events.SlotSet object at 0x000001A3BF8D67C8>, <rasa.core.events.UserUttered object at 0x000001A3BF8D6B08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6988>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D6B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6D08>, <rasa.core.events.Form object at 0x000001A3BF8D6C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6DC8>]),
  '41_0881e034b025458983ecbc7a875abd25': StoryStep(block_name='equipMaintenance Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D6F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D6E08>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8088>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D82C8>, <rasa.core.events.Form object at 0x000001A3BF8D8408>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8348>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8488>, <rasa.core.events.Form object at 0x000001A3BF8D84C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8588>]),
  '42_2ac0edb631204c4fb0f5cc22da3f14ae': StoryStep(block_name='equipMaintenance Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D86C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D85C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D87C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8D8A08>, <rasa.core.events.Form object at 0x000001A3BF8D8B48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8A88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8BC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8C08>, <rasa.core.events.Form object at 0x000001A3BF8D8C88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8B08>]),
  '43_acc7066f4e584ec487380350a14608bc': StoryStep(block_name='equipMaintenance Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8D8E48>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8D8F48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF108>, <rasa.core.events.Form object at 0x000001A3BF8DF208>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF188>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF288>, <rasa.core.events.UserUttered object at 0x000001A3BF8DF448>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF308>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF488>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF608>, <rasa.core.events.Form object at 0x000001A3BF8DF588>, <rasa.core.events.SlotSet object at 0x000001A3BF8DF6C8>]),
  '44_554dd70f09f94f6aaa1bcd4122385a7a': StoryStep(block_name='equipOperation path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8DF7C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF708>, <rasa.core.events.Form object at 0x000001A3BF8DFA88>, <rasa.core.events.Form object at 0x000001A3BF8DF908>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DFB48>]),
  '45_72ec892318b848f4b7eaf96768b5ab60': StoryStep(block_name='sysOperation_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8DFB88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DF688>, <rasa.core.events.Form object at 0x000001A3BF8DFEC8>, <rasa.core.events.Form object at 0x000001A3BF8DFD48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8DFF88>]),
  '46_a96f4cf20fd041be82c0fbec6f1422bc': StoryStep(block_name='equipOperation Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E1048>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E10C8>, <rasa.core.events.Form object at 0x000001A3BF8E1348>, <rasa.core.events.SlotSet object at 0x000001A3BF8E11C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E13C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1448>, <rasa.core.events.SlotSet object at 0x000001A3BF8E14C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1588>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1648>, <rasa.core.events.SlotSet object at 0x000001A3BF8E16C8>, <rasa.core.events.Form object at 0x000001A3BF8E1788>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1848>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1888>]),
  '47_9ced12c5cb7d4d0aaff4753e795e0b5c': StoryStep(block_name='equipOperation Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E1948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E19C8>, <rasa.core.events.Form object at 0x000001A3BF8E1C48>, <rasa.core.events.UserUttered object at 0x000001A3BF8E1D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1AC8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1D88>, <rasa.core.events.UserUttered object at 0x000001A3BF8E1F08>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1F88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E1F48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5088>, <rasa.core.events.UserUttered object at 0x000001A3BF8E5208>, <rasa.core.events.SlotSet object at 0x000001A3BF8E1E88>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E5248>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5408>, <rasa.core.events.Form object at 0x000001A3BF8E5348>, <rasa.core.events.SlotSet object at 0x000001A3BF8E54C8>]),
  '48_6f113e0986604e38a6c45f013236a895': StoryStep(block_name='equipOperation Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E5688>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5508>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5788>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5908>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E59C8>, <rasa.core.events.Form object at 0x000001A3BF8E5B08>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5A48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5B88>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5BC8>, <rasa.core.events.Form object at 0x000001A3BF8E5C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5AC8>]),
  '49_9da19de845dd42c896098e07018d122a': StoryStep(block_name='equipOperation Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E5EC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5D48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E5FC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7188>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7248>, <rasa.core.events.Form object at 0x000001A3BF8E7388>, <rasa.core.events.SlotSet object at 0x000001A3BF8E72C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7408>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7448>, <rasa.core.events.Form object at 0x000001A3BF8E74C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7348>]),
  '50_3bee6a16c39c4eabaa1278f9bd96cfc2': StoryStep(block_name='equipOperation Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8E76C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E75C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E77C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7948>, <rasa.core.events.Form object at 0x000001A3BF8E7A48>, <rasa.core.events.SlotSet object at 0x000001A3BF8E79C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7AC8>, <rasa.core.events.UserUttered object at 0x000001A3BF8E7C88>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7B48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7E48>, <rasa.core.events.Form object at 0x000001A3BF8E7DC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8E7F08>]),
  '51_20ad94aadf594d179b405c4903357db7': StoryStep(block_name='equipInstall path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB088>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8E7F48>, <rasa.core.events.Form object at 0x000001A3BF8EB308>, <rasa.core.events.Form object at 0x000001A3BF8EB188>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB3C8>]),
  '52_3825abe773fc4daca3da45e135d04e4d': StoryStep(block_name='sysInstall_form_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB408>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB508>, <rasa.core.events.Form object at 0x000001A3BF8EB7C8>, <rasa.core.events.Form object at 0x000001A3BF8EB608>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB888>]),
  '53_37acd2b8d2a34cdba5e139047e57b358': StoryStep(block_name='equipInstall Generated Form Story 1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EB8C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB388>, <rasa.core.events.Form object at 0x000001A3BF8EBC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBA88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBC88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBD08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBD88>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBE48>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBF08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EBF88>, <rasa.core.events.Form object at 0x000001A3BF8EE048>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE148>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE188>]),
  '54_05045c417be746e89c91eac0af345766': StoryStep(block_name='equipInstall Generated Form Story 2', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EE208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EB848>, <rasa.core.events.Form object at 0x000001A3BF8EE548>, <rasa.core.events.UserUttered object at 0x000001A3BF8EE648>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE3C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE688>, <rasa.core.events.UserUttered object at 0x000001A3BF8EE808>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE888>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EE848>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE788>, <rasa.core.events.UserUttered object at 0x000001A3BF8EEAC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8EE948>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8EEB08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EECC8>, <rasa.core.events.Form object at 0x000001A3BF8EEC08>, <rasa.core.events.SlotSet object at 0x000001A3BF8EED88>]),
  '55_f6bc73cec1d44f4db2670a88fd2da682': StoryStep(block_name='equipInstall Generated Form Story 3', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8EEF48>, <rasa.core.events.SlotSet object at 0x000001A3BF8EEDC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1088>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1208>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F12C8>, <rasa.core.events.Form object at 0x000001A3BF8F1408>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1348>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1488>, <rasa.core.events.SlotSet object at 0x000001A3BF8F14C8>, <rasa.core.events.Form object at 0x000001A3BF8F1548>, <rasa.core.events.SlotSet object at 0x000001A3BF8F13C8>]),
  '56_ecc468847db04cf58456cb7d6e916fa3': StoryStep(block_name='equipInstall Generated Form Story 4', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F17C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1648>, <rasa.core.events.SlotSet object at 0x000001A3BF8F18C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1A48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F1B08>, <rasa.core.events.Form object at 0x000001A3BF8F1C48>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1B88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1CC8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1D08>, <rasa.core.events.Form object at 0x000001A3BF8F1D88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1C08>]),
  '57_25447c1fd41449ad956c3feef44dd07b': StoryStep(block_name='equipInstall Generated Form Story 5', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F1F88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F1E88>, <rasa.core.events.SlotSet object at 0x000001A3BF8F50C8>, <rasa.core.events.ActionExecuted object at 0x000001A3BF8F5248>, <rasa.core.events.Form object at 0x000001A3BF8F5348>, <rasa.core.events.SlotSet object at 0x000001A3BF8F52C8>, <rasa.core.events.SlotSet object at 0x000001A3BF8F53C8>, <rasa.core.events.UserUttered object at 0x000001A3BF70A108>, <rasa.core.events.SlotSet object at 0x000001A3BF70AB08>, <rasa.core.events.ActionExecuted object at 0x000001A3BF70A608>, <rasa.core.events.SlotSet object at 0x000001A3BF733748>, <rasa.core.events.Form object at 0x000001A3BF8BC808>, <rasa.core.events.SlotSet object at 0x000001A3BF87D5C8>]),
  '58_94269af447734bf8a680276b6186e2cc': StoryStep(block_name='deviceParameter path_1', start_checkpoints=[Checkpoint(name='STORY_START', conditions={})], end_checkpoints=[], events=[<rasa.core.events.UserUttered object at 0x000001A3BF8F1E48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF87D508>, <rasa.core.events.Form object at 0x000001A3BF876E88>, <rasa.core.events.Form object at 0x000001A3BF876E48>, <rasa.core.events.ActionExecuted object at 0x000001A3BF6F1BC8>])},
 'ordered_ids': deque(['30_59cb32cb69a14425b5ec7ceb21dfab88',
        '31_5436161f1ba141d79006debc4e61a004',
        '32_6ab17da8458f44db8c4f0d809fb92cc6',
        '33_ddbbf2fcb04745428807e5f0591ff77c',
        '34_e543523258f14563926bc7934c17b936',
        '35_4b422fd5799b48d5b0d857e862111ec3',
        '36_92b0ebd96d034401bc6cf5e6631ee0aa',
        '37_32e443a972d34a6c93342ffa794248e0',
        '38_ff72b1e474eb4a85b76bf1a9cfa886e9',
        '39_4ce9f23606444e6e8be2cbceb62f4eec',
        '40_a171f49097f9400993a175980c61fc91',
        '41_0881e034b025458983ecbc7a875abd25',
        '42_2ac0edb631204c4fb0f5cc22da3f14ae',
        '43_acc7066f4e584ec487380350a14608bc',
        '44_554dd70f09f94f6aaa1bcd4122385a7a',
        '45_72ec892318b848f4b7eaf96768b5ab60',
        '46_a96f4cf20fd041be82c0fbec6f1422bc',
        '47_9ced12c5cb7d4d0aaff4753e795e0b5c',
        '48_6f113e0986604e38a6c45f013236a895',
        '49_9da19de845dd42c896098e07018d122a',
        '50_3bee6a16c39c4eabaa1278f9bd96cfc2',
        '51_20ad94aadf594d179b405c4903357db7',
        '52_3825abe773fc4daca3da45e135d04e4d',
        '53_37acd2b8d2a34cdba5e139047e57b358',
        '54_05045c417be746e89c91eac0af345766',
        '55_f6bc73cec1d44f4db2670a88fd2da682',
        '56_ecc468847db04cf58456cb7d6e916fa3',
        '57_25447c1fd41449ad956c3feef44dd07b',
        '58_94269af447734bf8a680276b6186e2cc']),
 'cyclic_edge_ids': [],
 'story_end_checkpoints': {}}

nlu.md被解析成rasa.nlu.training_data.message.Message格式数据

nlu_data = await file_importer.get_nlu_data() #返回类 rasa.nlu.training_data.training_data.TrainingData
nlu_data.__dict__

{'training_examples': [<rasa.nlu.training_data.message.Message at 0x1a3bf877a08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8773c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8776c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877c88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877448>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877f48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877148>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877248>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877fc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877288>,
  <rasa.nlu.training_data.message.Message at 0x1a3a4106d48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bc340d08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf877608>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf686a88>,
  <rasa.nlu.training_data.message.Message at 0x1a3a4106d88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf686908>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf6918c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf691c48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf691dc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf691708>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf6866c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf691cc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf691748>,
  <rasa.nlu.training_data.message.Message at 0x1a3bc940d08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bc940cc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3a406cc48>,
  <rasa.nlu.training_data.message.Message at 0x1a3a401c3c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3a401c688>,
  <rasa.nlu.training_data.message.Message at 0x1a3a406cd08>,
  <rasa.nlu.training_data.message.Message at 0x1a3a401c548>,
  <rasa.nlu.training_data.message.Message at 0x1a3a401c308>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf6f1748>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf720548>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf6f1e88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf6f19c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf70a488>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf71c708>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf72cb08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf87d908>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf87de48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf87d448>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf87d8c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf701108>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852f48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852bc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852188>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852748>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852a88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852488>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852dc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852fc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852708>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf852e88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8523c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf733a48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf69da88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf73a808>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf7abd08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8c1d88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8c1388>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8c1408>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8c1348>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715388>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715548>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715088>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715b88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715148>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf715188>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8765c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf876748>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8eebc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92f288>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92f5c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92f2c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92fa48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92f788>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92fdc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92fb88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf92ff88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935408>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935608>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935448>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935a08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf9357c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935e08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935bc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf935fc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf8b0688>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d248>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d548>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d388>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d848>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d688>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93db48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93d988>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93de48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93dc88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93df88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a2c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a508>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a708>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a548>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93aa08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a848>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93aa48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93ac48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bf93a308>,
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  <rasa.nlu.training_data.message.Message at 0x1a3bfbf85c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbf8108>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbf8708>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbf8d08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbfcc88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbfc688>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbfc088>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbfc4c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfbfcac8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc05ec8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc058c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc052c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc05408>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc05a08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0bf88>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0b988>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0b388>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0b1c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0b7c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc0bdc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc10c08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc10608>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc10108>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc10748>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc10d48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc16cc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc166c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc160c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc16508>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc16b08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc1cf08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc1c908>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc1c308>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc1c448>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc1ca48>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc21fc8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc219c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc213c8>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc21208>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc21808>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc21e08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc27c08>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc27608>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc27148>,
  <rasa.nlu.training_data.message.Message at 0x1a3bfc27748>,
  ...],
 'entity_synonyms': {},
 'regex_features': [],
 'lookup_tables': [],
 'nlg_stories': {}}

rasa.nlu.training_data.message.Message格式数据

nlu_data.__dict__['training_examples'][910].__dict__

{'text': 'LED1闪烁',
 'time': None,
 'data': {'intent': 'inform',
  'entities': [{'start': 0,
    'end': 6,
    'value': 'LED1闪烁',
    'entity': 'FaultPhenomenon'}]},
 'output_properties': set()}

config数据

config = await file_importer.get_config() #返回数据 dict
NLU_config = nlu_config.load(configs_file) #见文件metadata_parsing.txt
Core_config = core_config.load(configs_file) #见文件metadata_parsing.txt
NLU_config.as_dict(),Core_config

D:\ProgramFiles\Anaconda3\lib\site-packages\rasa\core\policies\ensemble.py:318: FutureWarning: 'KerasPolicy' is deprecated and will be removed in version 2.0. Use 'TEDPolicy' instead.
  policy_object = constr_func(**policy)





({'language': 'zh',
  'pipeline': [{'name': 'JiebaTokenizer'},
   {'name': 'KashgariEntityExtractor',
    'bert_model_path': 'chinese_L-12_H-768_A-12'},
   {'name': 'RegexExtractor', 'regex_ner_entity': ['EqpType']},
   {'name': 'KashgariIntentClassifier',
    'bert_model_path': 'chinese_L-12_H-768_A-12'}],
  'data': None,
  'policies': [{'name': 'TwoStageFallbackPolicy',
    'core_threshold': 0.1,
    'nlu_threshold': 0.1,
    'fallback_core_action_name': 'action_default_fallback',
    'fallback_nlu_action_name': 'action_handoff_to_human',
    'deny_suggestion_intent_name': 'out_of_scope'},
   {'name': 'MemoizationPolicy', 'max_history': 3},
   {'name': 'FormPolicy'},
   {'name': 'MappingPolicy'},
   {'name': 'KerasPolicy',
    'featurizer': [{'name': 'MaxHistoryTrackerFeaturizer',
      'max_history': 5,
      'state_featurizer': [{'name': 'BinarySingleStateFeaturizer'}]}]}]},
 [<rasa.core.policies.two_stage_fallback.TwoStageFallbackPolicy at 0x1a3bf87dd08>,
  <rasa.core.policies.memoization.MemoizationPolicy at 0x1a3bf852988>,
  <rasa.core.policies.form_policy.FormPolicy at 0x1a3bfd10048>,
  <rasa.core.policies.mapping_policy.MappingPolicy at 0x1a3ddf1bd88>,
  <rasa.core.policies.keras_policy.KerasPolicy at 0x1a3ddf1be88>])

domain_states 为对话系统domain中包含的对话状态编码，用于生成对话状态向量（作为Policy的输入）

domain_dict = domain.as_dict()
domain_states = domain.input_state_map

domain_dict, domain_states

({'config': {'store_entities_as_slots': True},
  'session_config': {'session_expiration_time': 0,
   'carry_over_slots_to_new_session': True},
  'intents': [{'faultDiag': {'triggers': 'utter_faultDiag',
     'use_entities': True}},
   {'sysFaultDiag': {'use_entities': True}},
   {'equipFaultDiag': {'use_entities': True}},
   {'maintenance': {'triggers': 'utter_maintenance', 'use_entities': True}},
   {'sysMaintenance': {'use_entities': True}},
   {'equipMaintenance': {'use_entities': True}},
   {'operation': {'triggers': 'utter_operation', 'use_entities': True}},
   {'sysOperation': {'use_entities': True}},
   {'equipOperation': {'use_entities': True}},
   {'install': {'triggers': 'utter_install', 'use_entities': True}},
   {'equipInstall': {'use_entities': True}},
   {'sysInstall': {'use_entities': True}},
   {'deviceParameter': {'use_entities': True}},
   {'inform': {'use_entities': True}},
   {'greet': {'triggers': 'utter_greet', 'use_entities': True}},
   {'goodbye': {'triggers': 'utter_goodbye', 'use_entities': True}},
   {'affirm': {'use_entities': True}},
   {'deny': {'use_entities': True}},
   {'thankyou': {'use_entities': True}},
   {'chitchat': {'triggers': 'action_tuling_api', 'use_entities': True}},
   {'stop': {'triggers': 'utter_stop', 'use_entities': True}},
   {'continue': {'triggers': 'action_continue', 'use_entities': True}},
   {'out': {'triggers': 'action_out', 'use_entities': True}},
   {'askBotFunction': {'triggers': 'action_bot_function',
     'use_entities': True}},
   {'askIsBot': {'triggers': 'action_is_bot', 'use_entities': True}},
   {'askPoiet': {'triggers': 'utter_askPoiet', 'use_entities': True}},
   {'insult': {'triggers': 'action_respond_insult', 'use_entities': True}},
   {'opinion+positive': {'triggers': 'utter_positive_feedback_reaction',
     'use_entities': True}},
   {'opinion+negative': {'triggers': 'utter_imporvement_request',
     'use_entities': True}},
   {'out_of_scope': {'triggers': 'utter_ask_rephrase', 'use_entities': True}},
   {'unknow': {'use_entities': True}}],
  'entities': ['Brand',
   'EqpName',
   'EqpType',
   'FaultPhenomenon',
   'FtCode',
   'InstallApproach',
   'Installation',
   'Maintaining',
   'MajorName',
   'OpApproach',
   'OpManagement',
   'OpRegulation',
   'OutMark',
   'Param',
   'RunSystem',
   'Setting',
   'SysName',
   'TestRun',
   'parameter'],
  'slots': {'Brand': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'EqpName': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'EqpType': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'FaultPhenomenon': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'FtCode': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'InstallApproach': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'Maintaining': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'OpApproach': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'OutMark': {'type': 'rasa.core.slots.BooleanSlot',
    'initial_value': None,
    'auto_fill': True},
   'Param': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'SysName': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True},
   'feedback': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': False},
   'requested_slot': {'type': 'rasa.core.slots.UnfeaturizedSlot',
    'initial_value': None,
    'auto_fill': True}},
  'responses': {....此处省略......},
  'actions': ['action_bot_function',
   'action_continue',
   'action_handoff_to_human',
   'action_is_bot',
   'action_out',
   'action_respond_insult',
   'action_tuling_api',
   'utter_askPoiet',
   'utter_ask_Brand',
   'utter_ask_EqpName',
   'utter_ask_EqpType',
   'utter_ask_FaultPhenomenon',
   'utter_ask_FtCode',
   'utter_ask_SysName',
   'utter_ask_continue',
   'utter_ask_rephrase',
   'utter_chitchat',
   'utter_default',
   'utter_faultDiag',
   'utter_function',
   'utter_goodbye',
   'utter_greet',
   'utter_iamabot',
   'utter_imporvement_request',
   'utter_inquireBrand',
   'utter_inquireEquipment',
   'utter_inquireEquipmentFualt',
   'utter_inquireFeedback',
   'utter_inquireSystem',
   'utter_inquireSystemFualt',
   'utter_inquireType:',
   'utter_install',
   'utter_maintenance',
   'utter_no_brand',
   'utter_no_equipment',
   'utter_no_equipmentFualt',
   'utter_no_system',
   'utter_no_systemFualt',
   'utter_no_type',
   'utter_noworries',
   'utter_operation',
   'utter_positive_fallback',
   'utter_positive_feedback_reaction',
   'utter_respond_insult',
   'utter_slots_deviceParameter',
   'utter_slots_equipFaultDiag',
   'utter_slots_equipInstall',
   'utter_slots_equipMaintenance',
   'utter_slots_equipOperation',
   'utter_slots_sysFaultDiag',
   'utter_slots_sysInstall',
   'utter_slots_sysMaintenance',
   'utter_slots_sysOperation',
   'utter_stop',
   'utter_submit',
   'utter_wait'],
  'forms': ['deviceParameter_form',
   'equipFaultDiag_form',
   'equipInstall_form',
   'equipMaintenance_form',
   'equipOperation_form',
   'sysFaultDiag_form',
   'sysInstall_form',
   'sysMaintenance_form',
   'sysOperation_form']},
 {'intent_affirm': 0,
  'intent_askBotFunction': 1,
  'intent_askIsBot': 2,
  'intent_askPoiet': 3,
  'intent_chitchat': 4,
  'intent_continue': 5,
  'intent_deny': 6,
  'intent_deviceParameter': 7,
  'intent_equipFaultDiag': 8,
  'intent_equipInstall': 9,
  'intent_equipMaintenance': 10,
  'intent_equipOperation': 11,
  'intent_faultDiag': 12,
  'intent_goodbye': 13,
  'intent_greet': 14,
  'intent_inform': 15,
  'intent_install': 16,
  'intent_insult': 17,
  'intent_maintenance': 18,
  'intent_operation': 19,
  'intent_opinion+negative': 20,
  'intent_opinion+positive': 21,
  'intent_out': 22,
  'intent_out_of_scope': 23,
  'intent_stop': 24,
  'intent_sysFaultDiag': 25,
  'intent_sysInstall': 26,
  'intent_sysMaintenance': 27,
  'intent_sysOperation': 28,
  'intent_thankyou': 29,
  'intent_unknow': 30,
  'entity_Brand': 31,
  'entity_EqpName': 32,
  'entity_EqpType': 33,
  'entity_FaultPhenomenon': 34,
  'entity_FtCode': 35,
  'entity_InstallApproach': 36,
  'entity_Installation': 37,
  'entity_Maintaining': 38,
  'entity_MajorName': 39,
  'entity_OpApproach': 40,
  'entity_OpManagement': 41,
  'entity_OpRegulation': 42,
  'entity_OutMark': 43,
  'entity_Param': 44,
  'entity_RunSystem': 45,
  'entity_Setting': 46,
  'entity_SysName': 47,
  'entity_TestRun': 48,
  'entity_parameter': 49,
  'slot_OutMark_0': 50,
  'slot_OutMark_1': 51,
  'prev_action_listen': 52,
  'prev_action_restart': 53,
  'prev_action_session_start': 54,
  'prev_action_default_fallback': 55,
  'prev_action_deactivate_form': 56,
  'prev_action_revert_fallback_events': 57,
  'prev_action_default_ask_affirmation': 58,
  'prev_action_default_ask_rephrase': 59,
  'prev_action_back': 60,
  'prev_action_bot_function': 61,
  'prev_action_continue': 62,
  'prev_action_handoff_to_human': 63,
  'prev_action_is_bot': 64,
  'prev_action_out': 65,
  'prev_action_respond_insult': 66,
  'prev_action_tuling_api': 67,
  'prev_utter_askPoiet': 68,
  'prev_utter_ask_Brand': 69,
  'prev_utter_ask_EqpName': 70,
  'prev_utter_ask_EqpType': 71,
  'prev_utter_ask_FaultPhenomenon': 72,
  'prev_utter_ask_FtCode': 73,
  'prev_utter_ask_SysName': 74,
  'prev_utter_ask_continue': 75,
  'prev_utter_ask_rephrase': 76,
  'prev_utter_chitchat': 77,
  'prev_utter_default': 78,
  'prev_utter_faultDiag': 79,
  'prev_utter_function': 80,
  'prev_utter_goodbye': 81,
  'prev_utter_greet': 82,
  'prev_utter_iamabot': 83,
  'prev_utter_imporvement_request': 84,
  'prev_utter_inquireBrand': 85,
  'prev_utter_inquireEquipment': 86,
  'prev_utter_inquireEquipmentFualt': 87,
  'prev_utter_inquireFeedback': 88,
  'prev_utter_inquireSystem': 89,
  'prev_utter_inquireSystemFualt': 90,
  'prev_utter_inquireType:': 91,
  'prev_utter_install': 92,
  'prev_utter_maintenance': 93,
  'prev_utter_no_brand': 94,
  'prev_utter_no_equipment': 95,
  'prev_utter_no_equipmentFualt': 96,
  'prev_utter_no_system': 97,
  'prev_utter_no_systemFualt': 98,
  'prev_utter_no_type': 99,
  'prev_utter_noworries': 100,
  'prev_utter_operation': 101,
  'prev_utter_positive_fallback': 102,
  'prev_utter_positive_feedback_reaction': 103,
  'prev_utter_respond_insult': 104,
  'prev_utter_slots_deviceParameter': 105,
  'prev_utter_slots_equipFaultDiag': 106,
  'prev_utter_slots_equipInstall': 107,
  'prev_utter_slots_equipMaintenance': 108,
  'prev_utter_slots_equipOperation': 109,
  'prev_utter_slots_sysFaultDiag': 110,
  'prev_utter_slots_sysInstall': 111,
  'prev_utter_slots_sysMaintenance': 112,
  'prev_utter_slots_sysOperation': 113,
  'prev_utter_stop': 114,
  'prev_utter_submit': 115,
  'prev_utter_wait': 116,
  'prev_deviceParameter_form': 117,
  'prev_equipFaultDiag_form': 118,
  'prev_equipInstall_form': 119,
  'prev_equipMaintenance_form': 120,
  'prev_equipOperation_form': 121,
  'prev_sysFaultDiag_form': 122,
  'prev_sysInstall_form': 123,
  'prev_sysMaintenance_form': 124,
  'prev_sysOperation_form': 125,
  'active_form_deviceParameter_form': 126,
  'active_form_equipFaultDiag_form': 127,
  'active_form_equipInstall_form': 128,
  'active_form_equipMaintenance_form': 129,
  'active_form_equipOperation_form': 130,
  'active_form_sysFaultDiag_form': 131,
  'active_form_sysInstall_form': 132,
  'active_form_sysMaintenance_form': 133,
  'active_form_sysOperation_form': 134})

3、模型训练方法解析

3.1 联合训练 nlu + core

训练方式一

train(domain_file, configs_file, training_files, output_path)

训练方式二

await train_async(domain_file, configs_file, training_files, output_path)

3.2 独立训练nlu或core

单独训练 nlu

await _train_nlu_with_validated_data(file_importer,
                                    output=output_path)

单独训练 core

#详见9.3节

4、重要的类Agent解析

Agent类为最重要的Rasa功能提供了方便的接口。这包括训练、处理消息、加载对话模型、获取下一个动作和处理通道。

4.1 Agent 加载对话模型

agent = Agent()
model_path = r'models/models_15/20200420-120239.tar.gz'
agent = agent.load(model_path) 
#loaded_agent = await load_agent() #agent.load的底层函数

agent.__dict__

obj: None
obj: C:\Users\86185\AppData\Local\Temp\tmpzu1kcsw_\nlu


WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Model will be built until sequence length is determined
WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Model will be built until sequence length is determined
D:\ProgramFiles\Anaconda3\lib\site-packages\rasa\core\policies\keras_policy.py:265: FutureWarning: 'KerasPolicy' is deprecated and will be removed in version 2.0. Use 'TEDPolicy' instead.
  current_epoch=meta["epochs"],


obj: <rasa.core.interpreter.RasaNLUInterpreter object at 0x0000025FA7775148>





{'domain': <rasa.core.domain.Domain at 0x26009d8dd08>,
 'policy_ensemble': <rasa.core.policies.ensemble.SimplePolicyEnsemble at 0x25fddc58d88>,
 'interpreter': <rasa.core.interpreter.RasaNLUInterpreter at 0x25fa7775148>,
 'nlg': <rasa.core.nlg.template.TemplatedNaturalLanguageGenerator at 0x26004c06f88>,
 'tracker_store': <rasa.core.tracker_store.FailSafeTrackerStore at 0x26009d9cd88>,
 'lock_store': <rasa.core.lock_store.InMemoryLockStore at 0x26009d9c488>,
 'action_endpoint': None,
 'fingerprint': '9ce015e0043d488fb7f33dff014acd14',
 'model_directory': 'C:\\Users\\86185\\AppData\\Local\\Temp\\tmpzu1kcsw_',
 'model_server': None,
 'remote_storage': None,
 'path_to_model_archive': None}

4.2 Agent 调取nlu模型解析用户消息

解析出用户消息中的意图和实体

ms_text = '我的空调有问题'
await agent.parse_message_using_nlu_interpreter(ms_text) 

Building prefix dict from the default dictionary ...
DEBUG:jieba:Building prefix dict from the default dictionary ...
Loading model from cache C:\Users\86185\AppData\Local\Temp\jieba.cache
DEBUG:jieba:Loading model from cache C:\Users\86185\AppData\Local\Temp\jieba.cache
Loading model cost 0.621 seconds.
DEBUG:jieba:Loading model cost 0.621 seconds.
Prefix dict has been built succesfully.
DEBUG:jieba:Prefix dict has been built succesfully.





{'intent': {'name': 'faultDiag', 'confidence': 0.8657001852989197},
 'entities': [{'start': 2,
   'end': 4,
   'value': '空调',
   'entity': 'MajorName',
   'extractor': 'RegexExtractor'}],
 'intent_ranking': [{'name': 'faultDiag', 'confidence': 0.8657001852989197},
  {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
  {'name': 'inform', 'confidence': 0.028037212789058685},
  {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
  {'name': 'unknow', 'confidence': 0.006765459664165974},
  {'name': 'greet', 'confidence': 0.006672943476587534},
  {'name': 'maintenance', 'confidence': 0.004478101618587971},
  {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
  {'name': 'thankyou', 'confidence': 0.003203833010047674},
  {'name': 'insult', 'confidence': 0.0031317586544901133}],
 'text': '我的空调有问题'}

4.3 、Agent 接收用户消息调取对话管理模块并产生系统输出

agent接收并处理用户消息，然后trackerstore得到当前对话状态，输入policy ensamble，得到agent action输出

ms_text = '我的空调有问题'
#ms_text = '唱一首歌吧'
uM = UserMessage(ms_text) #用户消息文本封装
print(uM.__dict__)
#agent加载外部Action服务端口
agent.action_endpoint = read_endpoint_config('configs/endpoints.yml',endpoint_type='action_endpoint')
#系统action输出
await agent.handle_message(uM)

{'text': '我的空调有问题', 'message_id': 'c0ef6e9a2fa0483fa974e7bdcf14a65e', 'output_channel': <rasa.core.channels.channel.CollectingOutputChannel object at 0x0000025FE70070C8>, 'sender_id': 'default', 'input_channel': None, 'parse_data': None, 'metadata': None}





[{'recipient_id': 'default',
  'text': '您要查询系统故障，还是设备故障？',
  'buttons': [{'payload': '/sysFaultDiag', 'title': '系统故障:(例如，中央空调供水温度降不下来)'},
   {'payload': '/equipFaultDiag', 'title': '设备故障:(例如，水泵喘振)'}]}]

agent基于用户sender_id的当前对话状态，输出action的预测分值、最大分值对应策略、tracker_current_state

predict_next = await agent.predict_next(sender_id='default',output_channel=CollectingOutputChannel) #只输出动作，没有生成回复
predict_next

{'scores': [{'action': 'action_listen', 'score': 0.0},
  {'action': 'action_restart', 'score': 0.0},
  {'action': 'action_session_start', 'score': 0.0},
  {'action': 'action_default_fallback', 'score': 0.0},
  {'action': 'action_deactivate_form', 'score': 0.0},
  {'action': 'action_revert_fallback_events', 'score': 0.0},
  {'action': 'action_default_ask_affirmation', 'score': 0.0},
  {'action': 'action_default_ask_rephrase', 'score': 0.0},
  {'action': 'action_back', 'score': 0.0},
  {'action': 'action_bot_function', 'score': 0.0},
  {'action': 'action_continue', 'score': 0.0},
  {'action': 'action_handoff_to_human', 'score': 0.0},
  {'action': 'action_is_bot', 'score': 0.0},
  {'action': 'action_out', 'score': 0.0},
  {'action': 'action_respond_insult', 'score': 0.0},
  {'action': 'action_tuling_api', 'score': 0.0},
  {'action': 'utter_askPoiet', 'score': 0.0},
  {'action': 'utter_ask_Brand', 'score': 0.0},
  {'action': 'utter_ask_EqpName', 'score': 0.0},
  {'action': 'utter_ask_EqpType', 'score': 0.0},
  {'action': 'utter_ask_FaultPhenomenon', 'score': 0.0},
  {'action': 'utter_ask_FtCode', 'score': 0.0},
  {'action': 'utter_ask_SysName', 'score': 0.0},
  {'action': 'utter_ask_continue', 'score': 0.0},
  {'action': 'utter_ask_rephrase', 'score': 0.0},
  {'action': 'utter_chitchat', 'score': 0.0},
  {'action': 'utter_default', 'score': 0.0},
  {'action': 'utter_faultDiag', 'score': 1},
  {'action': 'utter_function', 'score': 0.0},
  {'action': 'utter_goodbye', 'score': 0.0},
  {'action': 'utter_greet', 'score': 0.0},
  {'action': 'utter_iamabot', 'score': 0.0},
  {'action': 'utter_imporvement_request', 'score': 0.0},
  {'action': 'utter_inquireBrand', 'score': 0.0},
  {'action': 'utter_inquireEquipment', 'score': 0.0},
  {'action': 'utter_inquireEquipmentFualt', 'score': 0.0},
  {'action': 'utter_inquireFeedback', 'score': 0.0},
  {'action': 'utter_inquireSystem', 'score': 0.0},
  {'action': 'utter_inquireSystemFualt', 'score': 0.0},
  {'action': 'utter_inquireType:', 'score': 0.0},
  {'action': 'utter_install', 'score': 0.0},
  {'action': 'utter_maintenance', 'score': 0.0},
  {'action': 'utter_no_brand', 'score': 0.0},
  {'action': 'utter_no_equipment', 'score': 0.0},
  {'action': 'utter_no_equipmentFualt', 'score': 0.0},
  {'action': 'utter_no_system', 'score': 0.0},
  {'action': 'utter_no_systemFualt', 'score': 0.0},
  {'action': 'utter_no_type', 'score': 0.0},
  {'action': 'utter_noworries', 'score': 0.0},
  {'action': 'utter_operation', 'score': 0.0},
  {'action': 'utter_positive_fallback', 'score': 0.0},
  {'action': 'utter_positive_feedback_reaction', 'score': 0.0},
  {'action': 'utter_respond_insult', 'score': 0.0},
  {'action': 'utter_slots_deviceParameter', 'score': 0.0},
  {'action': 'utter_slots_equipFaultDiag', 'score': 0.0},
  {'action': 'utter_slots_equipInstall', 'score': 0.0},
  {'action': 'utter_slots_equipMaintenance', 'score': 0.0},
  {'action': 'utter_slots_equipOperation', 'score': 0.0},
  {'action': 'utter_slots_sysFaultDiag', 'score': 0.0},
  {'action': 'utter_slots_sysInstall', 'score': 0.0},
  {'action': 'utter_slots_sysMaintenance', 'score': 0.0},
  {'action': 'utter_slots_sysOperation', 'score': 0.0},
  {'action': 'utter_stop', 'score': 0.0},
  {'action': 'utter_submit', 'score': 0.0},
  {'action': 'utter_wait', 'score': 0.0},
  {'action': 'deviceParameter_form', 'score': 0.0},
  {'action': 'equipFaultDiag_form', 'score': 0.0},
  {'action': 'equipInstall_form', 'score': 0.0},
  {'action': 'equipMaintenance_form', 'score': 0.0},
  {'action': 'equipOperation_form', 'score': 0.0},
  {'action': 'sysFaultDiag_form', 'score': 0.0},
  {'action': 'sysInstall_form', 'score': 0.0},
  {'action': 'sysMaintenance_form', 'score': 0.0},
  {'action': 'sysOperation_form', 'score': 0.0}],
 'policy': 'policy_3_MappingPolicy',
 'confidence': 1.0,
 'tracker': {'sender_id': 'default',
  'slots': {'Brand': None,
   'EqpName': None,
   'EqpType': None,
   'FaultPhenomenon': None,
   'FtCode': None,
   'InstallApproach': None,
   'Maintaining': None,
   'OpApproach': None,
   'OutMark': None,
   'Param': None,
   'SysName': None,
   'feedback': None,
   'requested_slot': None},
  'latest_message': {'intent': {'name': 'faultDiag',
    'confidence': 0.8657001852989197},
   'entities': [{'start': 2,
     'end': 4,
     'value': '空调',
     'entity': 'MajorName',
     'extractor': 'RegexExtractor'}],
   'intent_ranking': [{'name': 'faultDiag', 'confidence': 0.8657001852989197},
    {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
    {'name': 'inform', 'confidence': 0.028037212789058685},
    {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
    {'name': 'unknow', 'confidence': 0.006765459664165974},
    {'name': 'greet', 'confidence': 0.006672943476587534},
    {'name': 'maintenance', 'confidence': 0.004478101618587971},
    {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
    {'name': 'thankyou', 'confidence': 0.003203833010047674},
    {'name': 'insult', 'confidence': 0.0031317586544901133}],
   'text': '我的空调有问题'},
  'latest_event_time': 1589357962.3806748,
  'followup_action': None,
  'paused': False,
  'events': [{'event': 'action',
    'timestamp': 1589357942.8721497,
    'name': 'action_session_start',
    'policy': None,
    'confidence': None},
   {'event': 'session_started', 'timestamp': 1589357942.8721497},
   {'event': 'action',
    'timestamp': 1589357942.8721497,
    'name': 'action_listen',
    'policy': None,
    'confidence': None},
   {'event': 'user',
    'timestamp': 1589357943.052667,
    'text': '我的空调有问题',
    'parse_data': {'intent': {'name': 'faultDiag',
      'confidence': 0.8657001852989197},
     'entities': [{'start': 2,
       'end': 4,
       'value': '空调',
       'entity': 'MajorName',
       'extractor': 'RegexExtractor'}],
     'intent_ranking': [{'name': 'faultDiag',
       'confidence': 0.8657001852989197},
      {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
      {'name': 'inform', 'confidence': 0.028037212789058685},
      {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
      {'name': 'unknow', 'confidence': 0.006765459664165974},
      {'name': 'greet', 'confidence': 0.006672943476587534},
      {'name': 'maintenance', 'confidence': 0.004478101618587971},
      {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
      {'name': 'thankyou', 'confidence': 0.003203833010047674},
      {'name': 'insult', 'confidence': 0.0031317586544901133}],
     'text': '我的空调有问题'},
    'input_channel': None,
    'message_id': 'c4b6e92481ba447db80303e2ba8aa2ca',
    'metadata': {}},
   {'event': 'action',
    'timestamp': 1589357943.273126,
    'name': 'utter_faultDiag',
    'policy': 'policy_3_MappingPolicy',
    'confidence': 1},
   {'event': 'bot',
    'timestamp': 1589357943.273126,
    'text': '您要查询系统故障，还是设备故障？',
    'data': {'elements': None,
     'quick_replies': None,
     'buttons': [{'payload': '/sysFaultDiag',
       'title': '系统故障:(例如，中央空调供水温度降不下来)'},
      {'payload': '/equipFaultDiag', 'title': '设备故障:(例如，水泵喘振)'}],
     'attachment': None,
     'image': None,
     'custom': None},
    'metadata': {}},
   {'event': 'action',
    'timestamp': 1589357943.3049924,
    'name': 'action_listen',
    'policy': 'policy_3_MappingPolicy',
    'confidence': 1},
   {'event': 'user',
    'timestamp': 1589357962.350755,
    'text': '我的空调有问题',
    'parse_data': {'intent': {'name': 'faultDiag',
      'confidence': 0.8657001852989197},
     'entities': [{'start': 2,
       'end': 4,
       'value': '空调',
       'entity': 'MajorName',
       'extractor': 'RegexExtractor'}],
     'intent_ranking': [{'name': 'faultDiag',
       'confidence': 0.8657001852989197},
      {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
      {'name': 'inform', 'confidence': 0.028037212789058685},
      {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
      {'name': 'unknow', 'confidence': 0.006765459664165974},
      {'name': 'greet', 'confidence': 0.006672943476587534},
      {'name': 'maintenance', 'confidence': 0.004478101618587971},
      {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
      {'name': 'thankyou', 'confidence': 0.003203833010047674},
      {'name': 'insult', 'confidence': 0.0031317586544901133}],
     'text': '我的空调有问题'},
    'input_channel': None,
    'message_id': 'c0ef6e9a2fa0483fa974e7bdcf14a65e',
    'metadata': {}},
   {'event': 'action',
    'timestamp': 1589357962.3657157,
    'name': 'utter_faultDiag',
    'policy': 'policy_3_MappingPolicy',
    'confidence': 1},
   {'event': 'bot',
    'timestamp': 1589357962.3657157,
    'text': '您要查询系统故障，还是设备故障？',
    'data': {'elements': None,
     'quick_replies': None,
     'buttons': [{'payload': '/sysFaultDiag',
       'title': '系统故障:(例如，中央空调供水温度降不下来)'},
      {'payload': '/equipFaultDiag', 'title': '设备故障:(例如，水泵喘振)'}],
     'attachment': None,
     'image': None,
     'custom': None},
    'metadata': {}},
   {'event': 'action',
    'timestamp': 1589357962.3806748,
    'name': 'action_listen',
    'policy': 'policy_3_MappingPolicy',
    'confidence': 1}],
  'latest_input_channel': None,
  'active_form': {},
  'latest_action_name': 'action_listen'}}

5、 Policy（策略）相关接口分析

1、Rasa对话策略包括：

（1）规则策略：FormPolicy、FallbackPolicy、TwoStageFallbackPolicy、MemoizationPolicy、MappingPolicy、AugmentedMemoizationPolicy

（2）监督学习策略：KerasPolicy、TEDPolicy

2、继承关系

（1）Policy 是FallbackPolicy、MemoizationPolicy、MappingPolicy、KerasPolicy、TEDPolicy的父类；

（2）FallbackPolicy是TwoStageFallbackPolicy的父类；

（3）MemoizationPolicy是AugmentedMemoizationPolicy、FormPolicy的父类；

3、policy ensemble

3.1、PolicyEnsemble：

（1）聚合各个独立的Policy：FormPolicy、FallbackPolicy、TwoStageFallbackPolicy、MemoizationPolicy、MappingPolicy、AugmentedMemoizationPolicy、KerasPolicy、TEDPolicy等；

（2）提供策略模型与domain文件兼容性验证接口、策略模型参数打包存储和加载接口、加载状态特征器接口、策略训练接口等；

（3）待实现接口probabilities_using_best_policy

3.2、SimplePolicyEnsemble继承PolicyEnsemble

（1）主要功能：在PolicyEnsemble的基础上，综合各policy独立预测的next action的概率值，以及策略的优先级，得到probabilities, 和最优的policy_name

（2）实现了probabilities_using_best_policy：基于当前tracker预测bot的next action，根据预测概率和策略优先度来选择best policy

#from rasa.core.policies.ensemble import PolicyEnsemble, SimplePolicyEnsemble
#from rasa.core.policies.memoization import MemoizationPolicy
#from rasa.core.policies.policy import Policy
#@staticmethod
#def _create_ensemble(
#    policies: Union[List[Policy], PolicyEnsemble, None]
#) -> Optional[PolicyEnsemble]:
policy_ensemble = agent.policy_ensemble
print(policy_ensemble) #SimplePolicyEnsemble 
policy_ensemble.__dict__

<rasa.core.policies.ensemble.SimplePolicyEnsemble object at 0x0000025FDDC58D88>





{'policies': [<rasa.core.policies.two_stage_fallback.TwoStageFallbackPolicy at 0x25fddc58d48>,
  <rasa.core.policies.memoization.MemoizationPolicy at 0x26008415c88>,
  <rasa.core.policies.form_policy.FormPolicy at 0x25fddc58e48>,
  <rasa.core.policies.mapping_policy.MappingPolicy at 0x26008415a08>,
  <rasa.core.policies.keras_policy.KerasPolicy at 0x26008415ec8>],
 'date_trained': None,
 'action_fingerprints': {'action_listen': {'slots': ['EqpType',
    'Brand',
    'FtCode',
    'EqpName']},
  'deviceParameter_form': {'slots': []},
  'equipMaintenance_form': {'slots': ['EqpType',
    'requested_slot',
    'Brand',
    'EqpName']},
  'sysFaultDiag_form': {'slots': []},
  'equipFaultDiag_form': {'slots': ['requested_slot',
    'Brand',
    'FtCode',
    'EqpType',
    'EqpName']},
  'equipInstall_form': {'slots': ['EqpType',
    'requested_slot',
    'Brand',
    'EqpName']},
  'sysOperation_form': {'slots': []},
  'sysMaintenance_form': {'slots': []},
  'equipOperation_form': {'slots': ['EqpType',
    'requested_slot',
    'Brand',
    'EqpName']},
  'sysInstall_form': {'slots': []},
  'utter_slots_sysInstall': {'slots': []},
  'utter_slots_equipMaintenance': {'slots': []},
  'utter_slots_equipInstall': {'slots': []},
  'utter_slots_equipFaultDiag': {'slots': []},
  'utter_slots_equipOperation': {'slots': []},
  'utter_slots_deviceParameter': {'slots': []},
  'utter_slots_sysFaultDiag': {'slots': []},
  'utter_slots_sysMaintenance': {'slots': []},
  'utter_slots_sysOperation': {'slots': []}}}

6、tracker（对话跟踪器）相关接口分析

主要由类DialogueStateTracker来实现对话系统状态跟踪

DialogueStateTracker的主要方法：

1、DialogueStateTracker生成接口：从转储创建一个跟踪器 or 采用事件列表创建跟踪器

2、current_state：当前对话系统状态

3、past_states：根据历史记录生成此跟踪器的过去状态（用于进一步产生状态向量）。

4、update：根据“事件”修改跟踪器的当前状态（tracker.current_state）。

5、export_stories_to_file将跟踪器输出为story格式，可以作为训练数据的扩充方法

tracker.current_state，对话的当前状态

6.1、 当前对话状态tracker.current_state

tracker = predict_next['tracker'] #返回dict
tracker 
#tracker.current_state的格式如下：

{'sender_id': 'default',
 'slots': {'Brand': None,
  'EqpName': None,
  'EqpType': None,
  'FaultPhenomenon': None,
  'FtCode': None,
  'InstallApproach': None,
  'Maintaining': None,
  'OpApproach': None,
  'OutMark': None,
  'Param': None,
  'SysName': None,
  'feedback': None,
  'requested_slot': None},
 'latest_message': {'intent': {'name': 'faultDiag',
   'confidence': 0.8657001852989197},
  'entities': [{'start': 2,
    'end': 4,
    'value': '空调',
    'entity': 'MajorName',
    'extractor': 'RegexExtractor'}],
  'intent_ranking': [{'name': 'faultDiag', 'confidence': 0.8657001852989197},
   {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
   {'name': 'inform', 'confidence': 0.028037212789058685},
   {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
   {'name': 'unknow', 'confidence': 0.006765459664165974},
   {'name': 'greet', 'confidence': 0.006672943476587534},
   {'name': 'maintenance', 'confidence': 0.004478101618587971},
   {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
   {'name': 'thankyou', 'confidence': 0.003203833010047674},
   {'name': 'insult', 'confidence': 0.0031317586544901133}],
  'text': '我的空调有问题'},
 'latest_event_time': 1589357962.3806748,
 'followup_action': None,
 'paused': False,
 'events': [{'event': 'action',
   'timestamp': 1589357942.8721497,
   'name': 'action_session_start',
   'policy': None,
   'confidence': None},
  {'event': 'session_started', 'timestamp': 1589357942.8721497},
  {'event': 'action',
   'timestamp': 1589357942.8721497,
   'name': 'action_listen',
   'policy': None,
   'confidence': None},
  {'event': 'user',
   'timestamp': 1589357943.052667,
   'text': '我的空调有问题',
   'parse_data': {'intent': {'name': 'faultDiag',
     'confidence': 0.8657001852989197},
    'entities': [{'start': 2,
      'end': 4,
      'value': '空调',
      'entity': 'MajorName',
      'extractor': 'RegexExtractor'}],
    'intent_ranking': [{'name': 'faultDiag', 'confidence': 0.8657001852989197},
     {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
     {'name': 'inform', 'confidence': 0.028037212789058685},
     {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
     {'name': 'unknow', 'confidence': 0.006765459664165974},
     {'name': 'greet', 'confidence': 0.006672943476587534},
     {'name': 'maintenance', 'confidence': 0.004478101618587971},
     {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
     {'name': 'thankyou', 'confidence': 0.003203833010047674},
     {'name': 'insult', 'confidence': 0.0031317586544901133}],
    'text': '我的空调有问题'},
   'input_channel': None,
   'message_id': 'c4b6e92481ba447db80303e2ba8aa2ca',
   'metadata': {}},
  {'event': 'action',
   'timestamp': 1589357943.273126,
   'name': 'utter_faultDiag',
   'policy': 'policy_3_MappingPolicy',
   'confidence': 1},
  {'event': 'bot',
   'timestamp': 1589357943.273126,
   'text': '您要查询系统故障，还是设备故障？',
   'data': {'elements': None,
    'quick_replies': None,
    'buttons': [{'payload': '/sysFaultDiag',
      'title': '系统故障:(例如，中央空调供水温度降不下来)'},
     {'payload': '/equipFaultDiag', 'title': '设备故障:(例如，水泵喘振)'}],
    'attachment': None,
    'image': None,
    'custom': None},
   'metadata': {}},
  {'event': 'action',
   'timestamp': 1589357943.3049924,
   'name': 'action_listen',
   'policy': 'policy_3_MappingPolicy',
   'confidence': 1},
  {'event': 'user',
   'timestamp': 1589357962.350755,
   'text': '我的空调有问题',
   'parse_data': {'intent': {'name': 'faultDiag',
     'confidence': 0.8657001852989197},
    'entities': [{'start': 2,
      'end': 4,
      'value': '空调',
      'entity': 'MajorName',
      'extractor': 'RegexExtractor'}],
    'intent_ranking': [{'name': 'faultDiag', 'confidence': 0.8657001852989197},
     {'name': 'equipFaultDiag', 'confidence': 0.04571297764778137},
     {'name': 'inform', 'confidence': 0.028037212789058685},
     {'name': 'opinion+negtive', 'confidence': 0.010507158003747463},
     {'name': 'unknow', 'confidence': 0.006765459664165974},
     {'name': 'greet', 'confidence': 0.006672943476587534},
     {'name': 'maintenance', 'confidence': 0.004478101618587971},
     {'name': 'sysFaultDiag', 'confidence': 0.0033905007876455784},
     {'name': 'thankyou', 'confidence': 0.003203833010047674},
     {'name': 'insult', 'confidence': 0.0031317586544901133}],
    'text': '我的空调有问题'},
   'input_channel': None,
   'message_id': 'c0ef6e9a2fa0483fa974e7bdcf14a65e',
   'metadata': {}},
  {'event': 'action',
   'timestamp': 1589357962.3657157,
   'name': 'utter_faultDiag',
   'policy': 'policy_3_MappingPolicy',
   'confidence': 1},
  {'event': 'bot',
   'timestamp': 1589357962.3657157,
   'text': '您要查询系统故障，还是设备故障？',
   'data': {'elements': None,
    'quick_replies': None,
    'buttons': [{'payload': '/sysFaultDiag',
      'title': '系统故障:(例如，中央空调供水温度降不下来)'},
     {'payload': '/equipFaultDiag', 'title': '设备故障:(例如，水泵喘振)'}],
    'attachment': None,
    'image': None,
    'custom': None},
   'metadata': {}},
  {'event': 'action',
   'timestamp': 1589357962.3806748,
   'name': 'action_listen',
   'policy': 'policy_3_MappingPolicy',
   'confidence': 1}],
 'latest_input_channel': None,
 'active_form': {},
 'latest_action_name': 'action_listen'}

tracker.current_state中包含的数据：

由以上可知，tracker.current_state中包含:

sender_id

slots（插槽状态）

latest_message（包含意图、实体识别结果、intent_ranking、text）

latest_event_time、followup_action、paused

events（事件，从对话开始以来发生的所有事件，包含用户和bot产生的）

latest_input_channel、active_form、latest_action_name

6.2、DialogueStateTracker解析

DialogueStateTracker接口。

agent登记当前用户信息，并返回DialogueStateTracker

DialogueStateTracker采用deque队列记录对话中发生的所有事件events

提供了保存和更新tracker.current_state各项数据的接口

new_tracker = await agent.log_message(uM) #返回DialogueStateTracker
print(new_tracker)
new_tracker.__dict__

<rasa.core.trackers.DialogueStateTracker object at 0x0000025FE9055588>





{'_max_event_history': None,
 'events': deque([<rasa.core.events.ActionExecuted at 0x25fe90b8648>,
        <rasa.core.events.SessionStarted at 0x25fe90b8288>,
        <rasa.core.events.ActionExecuted at 0x25fe90b8d88>,
        <rasa.core.events.UserUttered at 0x25fe90b8dc8>,
        <rasa.core.events.ActionExecuted at 0x25fe90b8f88>,
        BotUttered('您要查询系统故障，还是设备故障？', {"elements": null, "quick_replies": null, "buttons": [{"payload": "/sysFaultDiag", "title": "\u7cfb\u7edf\u6545\u969c:(\u4f8b\u5982\uff0c\u4e2d\u592e\u7a7a\u8c03\u4f9b\u6c34\u6e29\u5ea6\u964d\u4e0d\u4e0b\u6765)"}, {"payload": "/equipFaultDiag", "title": "\u8bbe\u5907\u6545\u969c:(\u4f8b\u5982\uff0c\u6c34\u6cf5\u5598\u632f)"}], "attachment": null, "image": null, "custom": null}, {}, 1589357943.273126),
        <rasa.core.events.ActionExecuted at 0x25fe90b8808>,
        <rasa.core.events.UserUttered at 0x25fe90b8708>,
        <rasa.core.events.ActionExecuted at 0x25fe90b8d08>,
        BotUttered('您要查询系统故障，还是设备故障？', {"elements": null, "quick_replies": null, "buttons": [{"payload": "/sysFaultDiag", "title": "\u7cfb\u7edf\u6545\u969c:(\u4f8b\u5982\uff0c\u4e2d\u592e\u7a7a\u8c03\u4f9b\u6c34\u6e29\u5ea6\u964d\u4e0d\u4e0b\u6765)"}, {"payload": "/equipFaultDiag", "title": "\u8bbe\u5907\u6545\u969c:(\u4f8b\u5982\uff0c\u6c34\u6cf5\u5598\u632f)"}], "attachment": null, "image": null, "custom": null}, {}, 1589357962.3657157),
        <rasa.core.events.ActionExecuted at 0x25fe90b8c88>,
        <rasa.core.events.UserUttered at 0x25fe9060b48>]),
 'sender_id': 'default',
 'slots': {'Brand': <UnfeaturizedSlot(Brand: None)>,
  'EqpName': <UnfeaturizedSlot(EqpName: None)>,
  'EqpType': <UnfeaturizedSlot(EqpType: None)>,
  'FaultPhenomenon': <UnfeaturizedSlot(FaultPhenomenon: None)>,
  'FtCode': <UnfeaturizedSlot(FtCode: None)>,
  'InstallApproach': <UnfeaturizedSlot(InstallApproach: None)>,
  'Maintaining': <UnfeaturizedSlot(Maintaining: None)>,
  'OpApproach': <UnfeaturizedSlot(OpApproach: None)>,
  'OutMark': <BooleanSlot(OutMark: None)>,
  'Param': <UnfeaturizedSlot(Param: None)>,
  'SysName': <UnfeaturizedSlot(SysName: None)>,
  'feedback': <UnfeaturizedSlot(feedback: None)>,
  'requested_slot': <UnfeaturizedSlot(requested_slot: None)>},
 '_paused': False,
 'followup_action': None,
 'latest_action_name': 'action_listen',
 'latest_message': <rasa.core.events.UserUttered at 0x25fe9060b48>,
 'latest_bot_utterance': BotUttered('您要查询系统故障，还是设备故障？', {"elements": null, "quick_replies": null, "buttons": [{"payload": "/sysFaultDiag", "title": "\u7cfb\u7edf\u6545\u969c:(\u4f8b\u5982\uff0c\u4e2d\u592e\u7a7a\u8c03\u4f9b\u6c34\u6e29\u5ea6\u964d\u4e0d\u4e0b\u6765)"}, {"payload": "/equipFaultDiag", "title": "\u8bbe\u5907\u6545\u969c:(\u4f8b\u5982\uff0c\u6c34\u6cf5\u5598\u632f)"}], "attachment": null, "image": null, "custom": null}, {}, 1589357962.3657157),
 'active_form': {}}

6.3、对话状态向量生成过程

由tarcker产生对话状态向量，作为监督学习策略（如TEDPolicy、KerasPolicy）的输入

#它用于TrackerFeaturizer的_create_states方法中，是产生状态向量的中间过程，
#得到一个deque包含n个frozenset，每个代表一轮对话（包含上一个系统动作，识别出的实体，top_10意图）
#frozenset中包括top_10 intent(用置信度表征),
states = new_tracker.past_states(domain)
states

deque([frozenset(),
       frozenset({('entity_MajorName', 1.0),
                  ('intent_equipFaultDiag', 0.04571297764778137),
                  ('intent_faultDiag', 0.8657001852989197),
                  ('intent_greet', 0.006672943476587534),
                  ('intent_inform', 0.028037212789058685),
                  ('intent_insult', 0.0031317586544901133),
                  ('intent_maintenance', 0.004478101618587971),
                  ('intent_opinion+negtive', 0.010507158003747463),
                  ('intent_sysFaultDiag', 0.0033905007876455784),
                  ('intent_thankyou', 0.003203833010047674),
                  ('intent_unknow', 0.006765459664165974),
                  ('prev_action_listen', 1.0)}),
       frozenset({('entity_MajorName', 1.0),
                  ('intent_equipFaultDiag', 0.04571297764778137),
                  ('intent_faultDiag', 0.8657001852989197),
                  ('intent_greet', 0.006672943476587534),
                  ('intent_inform', 0.028037212789058685),
                  ('intent_insult', 0.0031317586544901133),
                  ('intent_maintenance', 0.004478101618587971),
                  ('intent_opinion+negtive', 0.010507158003747463),
                  ('intent_sysFaultDiag', 0.0033905007876455784),
                  ('intent_thankyou', 0.003203833010047674),
                  ('intent_unknow', 0.006765459664165974),
                  ('prev_utter_faultDiag', 1.0)}),
       frozenset({('entity_MajorName', 1.0),
                  ('intent_equipFaultDiag', 0.04571297764778137),
                  ('intent_faultDiag', 0.8657001852989197),
                  ('intent_greet', 0.006672943476587534),
                  ('intent_inform', 0.028037212789058685),
                  ('intent_insult', 0.0031317586544901133),
                  ('intent_maintenance', 0.004478101618587971),
                  ('intent_opinion+negtive', 0.010507158003747463),
                  ('intent_sysFaultDiag', 0.0033905007876455784),
                  ('intent_thankyou', 0.003203833010047674),
                  ('intent_unknow', 0.006765459664165974),
                  ('prev_action_listen', 1.0)}),
       frozenset({('entity_MajorName', 1.0),
                  ('intent_equipFaultDiag', 0.04571297764778137),
                  ('intent_faultDiag', 0.8657001852989197),
                  ('intent_greet', 0.006672943476587534),
                  ('intent_inform', 0.028037212789058685),
                  ('intent_insult', 0.0031317586544901133),
                  ('intent_maintenance', 0.004478101618587971),
                  ('intent_opinion+negtive', 0.010507158003747463),
                  ('intent_sysFaultDiag', 0.0033905007876455784),
                  ('intent_thankyou', 0.003203833010047674),
                  ('intent_unknow', 0.006765459664165974),
                  ('prev_utter_faultDiag', 1.0)}),
       frozenset({('entity_MajorName', 1.0),
                  ('intent_equipFaultDiag', 0.04571297764778137),
                  ('intent_faultDiag', 0.8657001852989197),
                  ('intent_greet', 0.006672943476587534),
                  ('intent_inform', 0.028037212789058685),
                  ('intent_insult', 0.0031317586544901133),
                  ('intent_maintenance', 0.004478101618587971),
                  ('intent_opinion+negtive', 0.010507158003747463),
                  ('intent_sysFaultDiag', 0.0033905007876455784),
                  ('intent_thankyou', 0.003203833010047674),
                  ('intent_unknow', 0.006765459664165974),
                  ('prev_action_listen', 1.0)})])

new_tracker.past_states方法的底层实现方法，来源于Domain类

generated_states = domain.states_for_tracker_history(new_tracker)
generated_states
#domain.states_for_tracker_history等价于：
generated_states_1 = [domain.get_active_states(tr) for tr in new_tracker.generate_all_prior_trackers()]
generated_states,generated_states_1

([{},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_utter_faultDiag': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_utter_faultDiag': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0}],
 [{},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_utter_faultDiag': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_utter_faultDiag': 1.0},
  {'entity_MajorName': 1.0,
   'intent_faultDiag': 0.8657001852989197,
   'intent_equipFaultDiag': 0.04571297764778137,
   'intent_inform': 0.028037212789058685,
   'intent_opinion+negtive': 0.010507158003747463,
   'intent_unknow': 0.006765459664165974,
   'intent_greet': 0.006672943476587534,
   'intent_maintenance': 0.004478101618587971,
   'intent_sysFaultDiag': 0.0033905007876455784,
   'intent_thankyou': 0.003203833010047674,
   'intent_insult': 0.0031317586544901133,
   'prev_action_listen': 1.0}])

#tracker_store 
#存储DialogueStateTracker的方式
print(agent.tracker_store)
print(agent.tracker_store.__dict__)
inMemoryTrckerStore = agent.tracker_store.__dict__['_tracker_store']
inMemoryTrckerStore.retrieve('defualt')
inMemoryTrckerStore.__dict__,#inMemoryTrckerStore.keys() #dict_keys(['default']),

<rasa.core.tracker_store.FailSafeTrackerStore object at 0x0000026009D9CD88>
{'_fallback_tracker_store': None, '_tracker_store': <rasa.core.tracker_store.InMemoryTrackerStore object at 0x0000026009D9C808>, '_on_tracker_store_error': None, 'event_broker': None, 'max_event_history': None}





({'store': {'default': '{"events": [{"event": "action", "timestamp": 1589357942.8721497, "name": "action_session_start", "policy": null, "confidence": null}, {"event": "session_started", "timestamp": 1589357942.8721497}, {"event": "action", "timestamp": 1589357942.8721497, "name": "action_listen", "policy": null, "confidence": null}, {"event": "user", "timestamp": 1589357943.052667, "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898", "parse_data": {"intent": {"name": "faultDiag", "confidence": 0.8657001852989197}, "entities": [{"start": 2, "end": 4, "value": "\\u7a7a\\u8c03", "entity": "MajorName", "extractor": "RegexExtractor"}], "intent_ranking": [{"name": "faultDiag", "confidence": 0.8657001852989197}, {"name": "equipFaultDiag", "confidence": 0.04571297764778137}, {"name": "inform", "confidence": 0.028037212789058685}, {"name": "opinion+negtive", "confidence": 0.010507158003747463}, {"name": "unknow", "confidence": 0.006765459664165974}, {"name": "greet", "confidence": 0.006672943476587534}, {"name": "maintenance", "confidence": 0.004478101618587971}, {"name": "sysFaultDiag", "confidence": 0.0033905007876455784}, {"name": "thankyou", "confidence": 0.003203833010047674}, {"name": "insult", "confidence": 0.0031317586544901133}], "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898"}, "input_channel": null, "message_id": "c4b6e92481ba447db80303e2ba8aa2ca", "metadata": {}}, {"event": "action", "timestamp": 1589357943.273126, "name": "utter_faultDiag", "policy": "policy_3_MappingPolicy", "confidence": 1}, {"event": "bot", "timestamp": 1589357943.273126, "text": "\\u60a8\\u8981\\u67e5\\u8be2\\u7cfb\\u7edf\\u6545\\u969c\\uff0c\\u8fd8\\u662f\\u8bbe\\u5907\\u6545\\u969c\\uff1f", "data": {"elements": null, "quick_replies": null, "buttons": [{"payload": "/sysFaultDiag", "title": "\\u7cfb\\u7edf\\u6545\\u969c:(\\u4f8b\\u5982\\uff0c\\u4e2d\\u592e\\u7a7a\\u8c03\\u4f9b\\u6c34\\u6e29\\u5ea6\\u964d\\u4e0d\\u4e0b\\u6765)"}, {"payload": "/equipFaultDiag", "title": "\\u8bbe\\u5907\\u6545\\u969c:(\\u4f8b\\u5982\\uff0c\\u6c34\\u6cf5\\u5598\\u632f)"}], "attachment": null, "image": null, "custom": null}, "metadata": {}}, {"event": "action", "timestamp": 1589357943.3049924, "name": "action_listen", "policy": "policy_3_MappingPolicy", "confidence": 1}, {"event": "user", "timestamp": 1589357962.350755, "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898", "parse_data": {"intent": {"name": "faultDiag", "confidence": 0.8657001852989197}, "entities": [{"start": 2, "end": 4, "value": "\\u7a7a\\u8c03", "entity": "MajorName", "extractor": "RegexExtractor"}], "intent_ranking": [{"name": "faultDiag", "confidence": 0.8657001852989197}, {"name": "equipFaultDiag", "confidence": 0.04571297764778137}, {"name": "inform", "confidence": 0.028037212789058685}, {"name": "opinion+negtive", "confidence": 0.010507158003747463}, {"name": "unknow", "confidence": 0.006765459664165974}, {"name": "greet", "confidence": 0.006672943476587534}, {"name": "maintenance", "confidence": 0.004478101618587971}, {"name": "sysFaultDiag", "confidence": 0.0033905007876455784}, {"name": "thankyou", "confidence": 0.003203833010047674}, {"name": "insult", "confidence": 0.0031317586544901133}], "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898"}, "input_channel": null, "message_id": "c0ef6e9a2fa0483fa974e7bdcf14a65e", "metadata": {}}, {"event": "action", "timestamp": 1589357962.3657157, "name": "utter_faultDiag", "policy": "policy_3_MappingPolicy", "confidence": 1}, {"event": "bot", "timestamp": 1589357962.3657157, "text": "\\u60a8\\u8981\\u67e5\\u8be2\\u7cfb\\u7edf\\u6545\\u969c\\uff0c\\u8fd8\\u662f\\u8bbe\\u5907\\u6545\\u969c\\uff1f", "data": {"elements": null, "quick_replies": null, "buttons": [{"payload": "/sysFaultDiag", "title": "\\u7cfb\\u7edf\\u6545\\u969c:(\\u4f8b\\u5982\\uff0c\\u4e2d\\u592e\\u7a7a\\u8c03\\u4f9b\\u6c34\\u6e29\\u5ea6\\u964d\\u4e0d\\u4e0b\\u6765)"}, {"payload": "/equipFaultDiag", "title": "\\u8bbe\\u5907\\u6545\\u969c:(\\u4f8b\\u5982\\uff0c\\u6c34\\u6cf5\\u5598\\u632f)"}], "attachment": null, "image": null, "custom": null}, "metadata": {}}, {"event": "action", "timestamp": 1589357962.3806748, "name": "action_listen", "policy": "policy_3_MappingPolicy", "confidence": 1}, {"event": "user", "timestamp": 1589358162.9750464, "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898", "parse_data": {"intent": {"name": "faultDiag", "confidence": 0.8657001852989197}, "entities": [{"start": 2, "end": 4, "value": "\\u7a7a\\u8c03", "entity": "MajorName", "extractor": "RegexExtractor"}], "intent_ranking": [{"name": "faultDiag", "confidence": 0.8657001852989197}, {"name": "equipFaultDiag", "confidence": 0.04571297764778137}, {"name": "inform", "confidence": 0.028037212789058685}, {"name": "opinion+negtive", "confidence": 0.010507158003747463}, {"name": "unknow", "confidence": 0.006765459664165974}, {"name": "greet", "confidence": 0.006672943476587534}, {"name": "maintenance", "confidence": 0.004478101618587971}, {"name": "sysFaultDiag", "confidence": 0.0033905007876455784}, {"name": "thankyou", "confidence": 0.003203833010047674}, {"name": "insult", "confidence": 0.0031317586544901133}], "text": "\\u6211\\u7684\\u7a7a\\u8c03\\u6709\\u95ee\\u9898"}, "input_channel": null, "message_id": "c0ef6e9a2fa0483fa974e7bdcf14a65e", "metadata": {}}], "name": "default"}'},
  'domain': <rasa.core.domain.Domain at 0x26009d8dd08>,
  'event_broker': None,
  'max_event_history': None},)

将DialogueStateTracker带入MaxHistoryTrackerFeaturizer等特征器，生成状态向量

binarySingleStateFeaturizer = BinarySingleStateFeaturizer()
maxHistoryTrackerFeaturizer = MaxHistoryTrackerFeaturizer(
        state_featurizer=binarySingleStateFeaturizer,max_history='5')
print(maxHistoryTrackerFeaturizer._create_states(new_tracker, domain))
maxHistoryTrackerFeaturizer._create_states(new_tracker, domain,is_binary_training=True)

[{}, {'prev_action_listen': 1.0, 'entity_MajorName': 1.0, 'intent_faultDiag': 1.0}, {'entity_MajorName': 1.0, 'prev_utter_faultDiag': 1.0, 'intent_faultDiag': 1.0}, {'prev_action_listen': 1.0, 'entity_MajorName': 1.0, 'intent_faultDiag': 1.0}, {'entity_MajorName': 1.0, 'prev_utter_faultDiag': 1.0, 'intent_faultDiag': 1.0}, {'prev_action_listen': 1.0, 'entity_MajorName': 1.0, 'intent_faultDiag': 1.0}]





[{},
 {'intent_equipFaultDiag': 0.04571297764778137,
  'intent_opinion+negtive': 0.010507158003747463,
  'intent_inform': 0.028037212789058685,
  'intent_insult': 0.0031317586544901133,
  'intent_sysFaultDiag': 0.0033905007876455784,
  'intent_thankyou': 0.003203833010047674,
  'prev_action_listen': 1.0,
  'entity_MajorName': 1.0,
  'intent_unknow': 0.006765459664165974,
  'intent_faultDiag': 0.8657001852989197,
  'intent_greet': 0.006672943476587534,
  'intent_maintenance': 0.004478101618587971},
 {'intent_equipFaultDiag': 0.04571297764778137,
  'intent_opinion+negtive': 0.010507158003747463,
  'intent_inform': 0.028037212789058685,
  'intent_insult': 0.0031317586544901133,
  'intent_sysFaultDiag': 0.0033905007876455784,
  'intent_thankyou': 0.003203833010047674,
  'entity_MajorName': 1.0,
  'intent_unknow': 0.006765459664165974,
  'prev_utter_faultDiag': 1.0,
  'intent_faultDiag': 0.8657001852989197,
  'intent_greet': 0.006672943476587534,
  'intent_maintenance': 0.004478101618587971},
 {'intent_equipFaultDiag': 0.04571297764778137,
  'intent_opinion+negtive': 0.010507158003747463,
  'intent_inform': 0.028037212789058685,
  'intent_insult': 0.0031317586544901133,
  'intent_sysFaultDiag': 0.0033905007876455784,
  'intent_thankyou': 0.003203833010047674,
  'prev_action_listen': 1.0,
  'entity_MajorName': 1.0,
  'intent_unknow': 0.006765459664165974,
  'intent_faultDiag': 0.8657001852989197,
  'intent_greet': 0.006672943476587534,
  'intent_maintenance': 0.004478101618587971},
 {'intent_equipFaultDiag': 0.04571297764778137,
  'intent_opinion+negtive': 0.010507158003747463,
  'intent_inform': 0.028037212789058685,
  'intent_insult': 0.0031317586544901133,
  'intent_sysFaultDiag': 0.0033905007876455784,
  'intent_thankyou': 0.003203833010047674,
  'entity_MajorName': 1.0,
  'intent_unknow': 0.006765459664165974,
  'prev_utter_faultDiag': 1.0,
  'intent_faultDiag': 0.8657001852989197,
  'intent_greet': 0.006672943476587534,
  'intent_maintenance': 0.004478101618587971},
 {'intent_equipFaultDiag': 0.04571297764778137,
  'intent_opinion+negtive': 0.010507158003747463,
  'intent_inform': 0.028037212789058685,
  'intent_insult': 0.0031317586544901133,
  'intent_sysFaultDiag': 0.0033905007876455784,
  'intent_thankyou': 0.003203833010047674,
  'prev_action_listen': 1.0,
  'entity_MajorName': 1.0,
  'intent_unknow': 0.006765459664165974,
  'intent_faultDiag': 0.8657001852989197,
  'intent_greet': 0.006672943476587534,
  'intent_maintenance': 0.004478101618587971}]

7、LockStore分析

print(uM, uM.sender_id)
lock_store = agent.lock_store
print(lock_store, lock_store.__dict__)

print(lock_store.get_lock(uM.sender_id))

<rasa.core.channels.channel.UserMessage object at 0x0000025FE70072C8> default
<rasa.core.lock_store.InMemoryLockStore object at 0x0000026009D9C488> {'conversation_locks': {}}
None

ticketLock = lock_store.create_lock(uM.sender_id)
print(ticketLock, ticketLock.__dict__)
lock_store.save_lock(ticketLock) #必须保存才能get_lock
print(lock_store.get_lock(uM.sender_id))
ticketLock.issue_ticket(10.0)
lock_store.is_someone_waiting(uM.sender_id)

<rasa.core.lock.TicketLock object at 0x0000025FE7004F48> {'conversation_id': 'default', 'tickets': deque([])}
<rasa.core.lock.TicketLock object at 0x0000025FE7004F48>





True

8、nlu解析（数据、训练）

8.1、nlu模型组成各个部件（components）拆解

ms_text = '我的空调系统出现故障'
uM = UserMessage(ms_text)
uM.__dict__

message = Message(ms_text)
print(message.__dict__)

components.ComponentBuilder()
print(NLU_config.component_names)

trainer = Trainer(NLU_config)
print(trainer.__dict__)
print(trainer.pipeline)

#tokenizer
jieba_tokenizer = trainer.pipeline[0]
print(jieba_tokenizer.__dict__)
tokens = jieba_tokenizer.tokenize(message, 'text')
print([token.__dict__ for token in tokens])
#jieba_tokenizer.process(message, {}) #有问题？？？
#jieba_tokenizer.train()

#extractor
kashgariExtractor = trainer.pipeline[1]
print(kashgariExtractor.__dict__)
training_data = await file_importer.get_nlu_data()
print(training_data.__dict__)
training_data.nlg_stories
training_data.lookup_tables
training_data.nlg_stories
training_data.training_examples[1000].__dict__
kashgariExtractor.train(training_data, '') #可以训练
kashgariExtractor.extract_entities(message)

{'text': '我的空调系统出现故障', 'time': None, 'data': {}, 'output_properties': set()}
['JiebaTokenizer', 'KashgariEntityExtractor', 'RegexExtractor', 'KashgariIntentClassifier']


WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Model will be built until sequence length is determined
WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:Model will be built until sequence length is determined


{'config': <rasa.nlu.config.RasaNLUModelConfig object at 0x000002071B525B48>, 'skip_validation': False, 'training_data': None, 'pipeline': [<rasa.nlu.tokenizers.jieba_tokenizer.JiebaTokenizer object at 0x000002073CD69608>, <rasa.nlu.extractors.kashgari_entity_extractor.KashgariEntityExtractor object at 0x000002073CDCA408>, <rasa.nlu.extractors.regex_extractor.RegexExtractor object at 0x000002079870FB48>, <rasa.nlu.classifiers.kashgari_intent_classifier.KashgariIntentClassifier object at 0x000002079870FA48>]}
[<rasa.nlu.tokenizers.jieba_tokenizer.JiebaTokenizer object at 0x000002073CD69608>, <rasa.nlu.extractors.kashgari_entity_extractor.KashgariEntityExtractor object at 0x000002073CDCA408>, <rasa.nlu.extractors.regex_extractor.RegexExtractor object at 0x000002079870FB48>, <rasa.nlu.classifiers.kashgari_intent_classifier.KashgariIntentClassifier object at 0x000002079870FA48>]
{'component_config': {'dictionary_path': None, 'intent_tokenization_flag': False, 'intent_split_symbol': '_', 'name': 'JiebaTokenizer'}, 'partial_processing_pipeline': None, 'partial_processing_context': None, 'intent_tokenization_flag': False, 'intent_split_symbol': '_', 'dictionary_path': None}
[{'text': '我', 'start': 0, 'end': 1, 'data': {}, 'lemma': '我'}, {'text': '的', 'start': 1, 'end': 2, 'data': {}, 'lemma': '的'}, {'text': '空调', 'start': 2, 'end': 4, 'data': {}, 'lemma': '空调'}, {'text': '系统', 'start': 4, 'end': 6, 'data': {}, 'lemma': '系统'}, {'text': '出现', 'start': 6, 'end': 8, 'data': {}, 'lemma': '出现'}, {'text': '故障', 'start': 8, 'end': 10, 'data': {}, 'lemma': '故障'}]
{'component_config': {'bert_model_path': 'chinese_L-12_H-768_A-12', 'sequence_length': 'auto', 'layer_nums': 4, 'trainable': False, 'labeling_model': 'BiLSTM_Model', 'epochs': 10, 'batch_size': 32, 'validation_split': 0.2, 'patience': 5, 'factor': 0.5, 'verbose': 1, 'use_cudnn_cell': False, 'name': 'KashgariEntityExtractor'}, 'partial_processing_pipeline': None, 'partial_processing_context': None, 'labeling_model': 'BiLSTM_Model', 'bert_embedding': <<class 'kashgari.embeddings.bert_embedding.BERTEmbedding'> seq_len: auto>, 'model': None}
{'training_examples': [<rasa.nlu.training_data.message.Message object at 0x0000020798BAF948>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFA48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAF808>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAF908>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFA88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFB88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFAC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFB48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFBC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFC48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFB08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFC88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFC08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFCC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFD08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFD48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFD88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFDC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFE08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFE48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFE88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFEC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFF08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFF48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFF88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BAFFC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0048>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0088>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB00C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0108>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0148>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0188>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB01C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0208>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0248>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0308>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB03C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0488>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB05C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB06C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB07C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0888>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0988>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0A48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0B48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0C08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0CC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0D88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0E88>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB0DC8>, <rasa.nlu.training_data.message.Message object at 0x000002073CDDDA08>, <rasa.nlu.training_data.message.Message object at 0x000002073CDDDA48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7248>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7488>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB76C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7908>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7D08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7B48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7D48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BB7088>, <rasa.nlu.training_data.message.Message object at 0x0000020798A84388>, <rasa.nlu.training_data.message.Message object at 0x0000020798A84708>, <rasa.nlu.training_data.message.Message object at 0x0000020798A843C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A84C48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A84908>, <rasa.nlu.training_data.message.Message object at 0x0000020798A84C88>, <rasa.nlu.training_data.message.Message object at 0x0000020798A910C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91588>, <rasa.nlu.training_data.message.Message object at 0x0000020798A912C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91988>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91748>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91D88>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91B48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A91F48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98348>, <rasa.nlu.training_data.message.Message object at 0x0000020798A985C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98388>, <rasa.nlu.training_data.message.Message object at 0x0000020798A989C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98708>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98DC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98B88>, <rasa.nlu.training_data.message.Message object at 0x0000020798A98E08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBF148>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBF088>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBF788>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBFA48>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBF7C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBFF08>, <rasa.nlu.training_data.message.Message object at 0x0000020798BBFE08>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3088>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA30C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3588>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA33C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3888>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA36C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3B88>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA39C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3E88>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3CC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AA3FC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9D348>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9D548>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9D388>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9D848>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9DA48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9DC48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9DE48>, <rasa.nlu.training_data.message.Message object at 0x0000020798A9DD88>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAF148>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAF548>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAF748>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAF948>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAFB48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAFD48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAFF48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AAFF88>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABC048>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABC248>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABC448>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABC648>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABC848>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABCA48>, <rasa.nlu.training_data.message.Message object at 0x0000020798ABCC48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC90C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC9408>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC9808>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC9B88>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC9E08>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC9D08>, <rasa.nlu.training_data.message.Message object at 0x0000020798ACE3C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798ACE748>, <rasa.nlu.training_data.message.Message object at 0x0000020798ACEAC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798ACED48>, <rasa.nlu.training_data.message.Message object at 0x0000020798ACEC48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AD3308>, <rasa.nlu.training_data.message.Message object at 0x0000020798AD3748>, <rasa.nlu.training_data.message.Message object at 0x0000020798AD3A48>, <rasa.nlu.training_data.message.Message object at 0x0000020798AD3CC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AD3FC8>, <rasa.nlu.training_data.message.Message object at 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0x0000020798AC3088>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC3288>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC3488>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC3CC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AC3BC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF00C8>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0108>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0308>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0508>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0708>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0908>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0B08>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF0D08>, <rasa.nlu.training_data.message.Message object at 0x0000020798AF7248>, <rasa.nlu.training_data.message.Message object at 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0x0000020798A8C708>, <rasa.nlu.training_data.message.Message object at 0x000002073895E7C8>, <rasa.nlu.training_data.message.Message object at 0x00000207361A1DC8>, <rasa.nlu.training_data.message.Message object at 0x00000207361A1188>, <rasa.nlu.training_data.message.Message object at 0x00000207361A1248>, <rasa.nlu.training_data.message.Message object at 0x00000207361A1C88>, <rasa.nlu.training_data.message.Message object at 0x000002077E5CA148>, <rasa.nlu.training_data.message.Message object at 0x0000020798B90F08>, <rasa.nlu.training_data.message.Message object at 0x0000020798B90DC8>, <rasa.nlu.training_data.message.Message object at 0x0000020798B90C88>], 'entity_synonyms': {}, 'regex_features': [], 'lookup_tables': [], 'nlg_stories': {}}


WARNING:root:Sequence length will auto set at 95% of sequence length
WARNING:root:seq_len: 19


Model: "model_4"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
Input-Token (InputLayer)        [(None, 19)]         0                                            
__________________________________________________________________________________________________
Input-Segment (InputLayer)      [(None, 19)]         0                                            
__________________________________________________________________________________________________
Embedding-Token (TokenEmbedding [(None, 19, 768), (2 16226304    Input-Token[0][0]                
__________________________________________________________________________________________________
Embedding-Segment (Embedding)   (None, 19, 768)      1536        Input-Segment[0][0]              
__________________________________________________________________________________________________
Embedding-Token-Segment (Add)   (None, 19, 768)      0           Embedding-Token[0][0]            
                                                                 Embedding-Segment[0][0]          
__________________________________________________________________________________________________
Embedding-Position (PositionEmb (None, 19, 768)      14592       Embedding-Token-Segment[0][0]    
__________________________________________________________________________________________________
Embedding-Dropout (Dropout)     (None, 19, 768)      0           Embedding-Position[0][0]         
__________________________________________________________________________________________________
Embedding-Norm (LayerNormalizat (None, 19, 768)      1536        Embedding-Dropout[0][0]          
__________________________________________________________________________________________________
Encoder-1-MultiHeadSelfAttentio (None, 19, 768)      2362368     Embedding-Norm[0][0]             
__________________________________________________________________________________________________
Encoder-1-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-1-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-1-MultiHeadSelfAttentio (None, 19, 768)      0           Embedding-Norm[0][0]             
                                                                 Encoder-1-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-1-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-1-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-1-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-1-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-1-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-1-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-1-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-1-MultiHeadSelfAttention-
                                                                 Encoder-1-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-1-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-1-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-2-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-1-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-2-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-2-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-2-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-1-FeedForward-Norm[0][0] 
                                                                 Encoder-2-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-2-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-2-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-2-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-2-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-2-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-2-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-2-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-2-MultiHeadSelfAttention-
                                                                 Encoder-2-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-2-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-2-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-3-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-2-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-3-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-3-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-3-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-2-FeedForward-Norm[0][0] 
                                                                 Encoder-3-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-3-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-3-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-3-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-3-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-3-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-3-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-3-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-3-MultiHeadSelfAttention-
                                                                 Encoder-3-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-3-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-3-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-4-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-3-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-4-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-4-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-4-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-3-FeedForward-Norm[0][0] 
                                                                 Encoder-4-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-4-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-4-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-4-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-4-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-4-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-4-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-4-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-4-MultiHeadSelfAttention-
                                                                 Encoder-4-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-4-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-4-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-5-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-4-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-5-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-5-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-5-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-4-FeedForward-Norm[0][0] 
                                                                 Encoder-5-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-5-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-5-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-5-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-5-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-5-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-5-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-5-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-5-MultiHeadSelfAttention-
                                                                 Encoder-5-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-5-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-5-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-6-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-5-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-6-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-6-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-6-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-5-FeedForward-Norm[0][0] 
                                                                 Encoder-6-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-6-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-6-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-6-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-6-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-6-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-6-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-6-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-6-MultiHeadSelfAttention-
                                                                 Encoder-6-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-6-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-6-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-7-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-6-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-7-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-7-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-7-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-6-FeedForward-Norm[0][0] 
                                                                 Encoder-7-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-7-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-7-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-7-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-7-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-7-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-7-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-7-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-7-MultiHeadSelfAttention-
                                                                 Encoder-7-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-7-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-7-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-8-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-7-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-8-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-8-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-8-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-7-FeedForward-Norm[0][0] 
                                                                 Encoder-8-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-8-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-8-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-8-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-8-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-8-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-8-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-8-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-8-MultiHeadSelfAttention-
                                                                 Encoder-8-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-8-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-8-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-9-MultiHeadSelfAttentio (None, 19, 768)      2362368     Encoder-8-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-9-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-9-MultiHeadSelfAttention[
__________________________________________________________________________________________________
Encoder-9-MultiHeadSelfAttentio (None, 19, 768)      0           Encoder-8-FeedForward-Norm[0][0] 
                                                                 Encoder-9-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-9-MultiHeadSelfAttentio (None, 19, 768)      1536        Encoder-9-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-9-FeedForward (FeedForw (None, 19, 768)      4722432     Encoder-9-MultiHeadSelfAttention-
__________________________________________________________________________________________________
Encoder-9-FeedForward-Dropout ( (None, 19, 768)      0           Encoder-9-FeedForward[0][0]      
__________________________________________________________________________________________________
Encoder-9-FeedForward-Add (Add) (None, 19, 768)      0           Encoder-9-MultiHeadSelfAttention-
                                                                 Encoder-9-FeedForward-Dropout[0][
__________________________________________________________________________________________________
Encoder-9-FeedForward-Norm (Lay (None, 19, 768)      1536        Encoder-9-FeedForward-Add[0][0]  
__________________________________________________________________________________________________
Encoder-10-MultiHeadSelfAttenti (None, 19, 768)      2362368     Encoder-9-FeedForward-Norm[0][0] 
__________________________________________________________________________________________________
Encoder-10-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-10-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-10-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-9-FeedForward-Norm[0][0] 
                                                                 Encoder-10-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-10-MultiHeadSelfAttenti (None, 19, 768)      1536        Encoder-10-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-10-FeedForward (FeedFor (None, 19, 768)      4722432     Encoder-10-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-10-FeedForward-Dropout  (None, 19, 768)      0           Encoder-10-FeedForward[0][0]     
__________________________________________________________________________________________________
Encoder-10-FeedForward-Add (Add (None, 19, 768)      0           Encoder-10-MultiHeadSelfAttention
                                                                 Encoder-10-FeedForward-Dropout[0]
__________________________________________________________________________________________________
Encoder-10-FeedForward-Norm (La (None, 19, 768)      1536        Encoder-10-FeedForward-Add[0][0] 
__________________________________________________________________________________________________
Encoder-11-MultiHeadSelfAttenti (None, 19, 768)      2362368     Encoder-10-FeedForward-Norm[0][0]
__________________________________________________________________________________________________
Encoder-11-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-11-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-11-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-10-FeedForward-Norm[0][0]
                                                                 Encoder-11-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-11-MultiHeadSelfAttenti (None, 19, 768)      1536        Encoder-11-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-11-FeedForward (FeedFor (None, 19, 768)      4722432     Encoder-11-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-11-FeedForward-Dropout  (None, 19, 768)      0           Encoder-11-FeedForward[0][0]     
__________________________________________________________________________________________________
Encoder-11-FeedForward-Add (Add (None, 19, 768)      0           Encoder-11-MultiHeadSelfAttention
                                                                 Encoder-11-FeedForward-Dropout[0]
__________________________________________________________________________________________________
Encoder-11-FeedForward-Norm (La (None, 19, 768)      1536        Encoder-11-FeedForward-Add[0][0] 
__________________________________________________________________________________________________
Encoder-12-MultiHeadSelfAttenti (None, 19, 768)      2362368     Encoder-11-FeedForward-Norm[0][0]
__________________________________________________________________________________________________
Encoder-12-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-12-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-12-MultiHeadSelfAttenti (None, 19, 768)      0           Encoder-11-FeedForward-Norm[0][0]
                                                                 Encoder-12-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-12-MultiHeadSelfAttenti (None, 19, 768)      1536        Encoder-12-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-12-FeedForward (FeedFor (None, 19, 768)      4722432     Encoder-12-MultiHeadSelfAttention
__________________________________________________________________________________________________
Encoder-12-FeedForward-Dropout  (None, 19, 768)      0           Encoder-12-FeedForward[0][0]     
__________________________________________________________________________________________________
Encoder-12-FeedForward-Add (Add (None, 19, 768)      0           Encoder-12-MultiHeadSelfAttention
                                                                 Encoder-12-FeedForward-Dropout[0]
__________________________________________________________________________________________________
Encoder-12-FeedForward-Norm (La (None, 19, 768)      1536        Encoder-12-FeedForward-Add[0][0] 
__________________________________________________________________________________________________
Encoder-Output (Concatenate)    (None, 19, 3072)     0           Encoder-9-FeedForward-Norm[0][0] 
                                                                 Encoder-10-FeedForward-Norm[0][0]
                                                                 Encoder-11-FeedForward-Norm[0][0]
                                                                 Encoder-12-FeedForward-Norm[0][0]
__________________________________________________________________________________________________
non_masking_layer (NonMaskingLa (None, 19, 3072)     0           Encoder-Output[0][0]             
__________________________________________________________________________________________________
layer_blstm (Bidirectional)     (None, 19, 256)      3277824     non_masking_layer[0][0]          
__________________________________________________________________________________________________
layer_dropout (Dropout)         (None, 19, 256)      0           layer_blstm[0][0]                
__________________________________________________________________________________________________
layer_time_distributed (TimeDis (None, 19, 28)       7196        layer_dropout[0][0]              
__________________________________________________________________________________________________
activation (Activation)         (None, 19, 28)       0           layer_time_distributed[0][0]     
==================================================================================================
Total params: 104,583,452
Trainable params: 3,285,020
Non-trainable params: 101,298,432
__________________________________________________________________________________________________
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
Train for 34 steps, validate for 9 steps
Epoch 1/10
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
 1/34 [..............................] - ETA: 7:33 - loss: 2.0536 - accuracy: 0.0359调试： (2, 32, 19) (32, 19, 28)
 2/34 [>.............................] - ETA: 3:52 - loss: 1.6021 - accuracy: 0.2511调试： (2, 32, 19) (32, 19, 28)
 3/34 [=>............................] - ETA: 2:38 - loss: 1.4376 - accuracy: 0.3538调试： (2, 32, 19) (32, 19, 28)
 4/34 [==>...........................] - ETA: 2:00 - loss: 1.3595 - accuracy: 0.4127调试： (2, 32, 19) (32, 19, 28)
 5/34 [===>..........................] - ETA: 1:37 - loss: 1.1987 - accuracy: 0.4639调试： (2, 32, 19) (32, 19, 28)
 6/34 [====>.........................] - ETA: 1:22 - loss: 1.1163 - accuracy: 0.5097调试： (2, 32, 19) (32, 19, 28)
 7/34 [=====>........................] - ETA: 1:11 - loss: 1.0587 - accuracy: 0.5357调试： (2, 32, 19) (32, 19, 28)
 8/34 [======>.......................] - ETA: 1:02 - loss: 1.0047 - accuracy: 0.5641调试： (2, 32, 19) (32, 19, 28)
 9/34 [======>.......................] - ETA: 55s - loss: 0.9655 - accuracy: 0.5874 调试： (2, 32, 19) (32, 19, 28)
10/34 [=======>......................] - ETA: 49s - loss: 0.9282 - accuracy: 0.6052调试： (2, 32, 19) (32, 19, 28)
11/34 [========>.....................] - ETA: 44s - loss: 0.8912 - accuracy: 0.6181调试： (2, 32, 19) (32, 19, 28)
12/34 [=========>....................] - ETA: 40s - loss: 0.8562 - accuracy: 0.6300调试： (2, 32, 19) (32, 19, 28)
13/34 [==========>...................] - ETA: 37s - loss: 0.8188 - accuracy: 0.6435调试： (2, 32, 19) (32, 19, 28)
14/34 [===========>..................] - ETA: 33s - loss: 0.7916 - accuracy: 0.6580调试： (2, 32, 19) (32, 19, 28)
15/34 [============>.................] - ETA: 30s - loss: 0.7680 - accuracy: 0.6694调试： (2, 32, 19) (32, 19, 28)
16/34 [=============>................] - ETA: 28s - loss: 0.7402 - accuracy: 0.6817调试： (2, 32, 19) (32, 19, 28)
17/34 [==============>...............] - ETA: 25s - loss: 0.7168 - accuracy: 0.6905调试： (2, 32, 19) (32, 19, 28)
18/34 [==============>...............] - ETA: 23s - loss: 0.6946 - accuracy: 0.7007调试： (2, 32, 19) (32, 19, 28)
19/34 [===============>..............] - ETA: 21s - loss: 0.6740 - accuracy: 0.7101调试： (2, 32, 19) (32, 19, 28)
20/34 [================>.............] - ETA: 19s - loss: 0.6528 - accuracy: 0.7183调试： (2, 4, 19) (4, 19, 28)
21/34 [=================>............] - ETA: 17s - loss: 0.6361 - accuracy: 0.7262调试： (2, 32, 19) (32, 19, 28)
22/34 [==================>...........] - ETA: 16s - loss: 0.6218 - accuracy: 0.7328调试： (2, 32, 19) (32, 19, 28)
23/34 [===================>..........] - ETA: 14s - loss: 0.6055 - accuracy: 0.7383调试： (2, 32, 19) (32, 19, 28)
24/34 [====================>.........] - ETA: 13s - loss: 0.5948 - accuracy: 0.7431调试： (2, 32, 19) (32, 19, 28)
25/34 [=====================>........] - ETA: 11s - loss: 0.5825 - accuracy: 0.7467调试： (2, 32, 19) (32, 19, 28)
26/34 [=====================>........] - ETA: 10s - loss: 0.5685 - accuracy: 0.7535调试： (2, 32, 19) (32, 19, 28)
27/34 [======================>.......] - ETA: 8s - loss: 0.5560 - accuracy: 0.7586 调试： (2, 32, 19) (32, 19, 28)
28/34 [=======================>......] - ETA: 7s - loss: 0.5412 - accuracy: 0.7647调试： (2, 32, 19) (32, 19, 28)
29/34 [========================>.....] - ETA: 6s - loss: 0.5315 - accuracy: 0.7697调试： (2, 32, 19) (32, 19, 28)
30/34 [=========================>....] - ETA: 4s - loss: 0.5233 - accuracy: 0.7725调试： (2, 32, 19) (32, 19, 28)
31/34 [==========================>...] - ETA: 3s - loss: 0.5119 - accuracy: 0.7775调试： (2, 32, 19) (32, 19, 28)
32/34 [===========================>..] - ETA: 2s - loss: 0.5017 - accuracy: 0.7815调试： (2, 32, 19) (32, 19, 28)
33/34 [============================>.] - ETA: 1s - loss: 0.4938 - accuracy: 0.7853调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)

Epoch 00001: val_loss improved from inf to 0.13893, saving model to entity_weights.h5
34/34 [==============================] - 52s 2s/step - loss: 0.4808 - accuracy: 0.7861 - val_loss: 0.1389 - val_accuracy: 0.9488
Epoch 2/10
调试： (2, 32, 19) (32, 19, 28)
 1/34 [..............................] - ETA: 28s - loss: 0.1619 - accuracy: 0.9385调试： (2, 32, 19) (32, 19, 28)
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32/34 [===========================>..] - ETA: 1s - loss: 0.1215 - accuracy: 0.9483调试： (2, 32, 19) (32, 19, 28)
33/34 [============================>.] - ETA: 0s - loss: 0.1213 - accuracy: 0.9477调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)

Epoch 00002: val_loss improved from 0.13893 to 0.05201, saving model to entity_weights.h5
34/34 [==============================] - 36s 1s/step - loss: 0.1214 - accuracy: 0.9475 - val_loss: 0.0520 - val_accuracy: 0.9846
Epoch 3/10
调试： (2, 32, 19) (32, 19, 28)
 1/34 [..............................] - ETA: 24s - loss: 0.1003 - accuracy: 0.9642调试： (2, 32, 19) (32, 19, 28)
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32/34 [===========================>..] - ETA: 1s - loss: 0.0693 - accuracy: 0.9718调试： (2, 32, 19) (32, 19, 28)
33/34 [============================>.] - ETA: 0s - loss: 0.0697 - accuracy: 0.9715调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)

Epoch 00003: val_loss improved from 0.05201 to 0.04645, saving model to entity_weights.h5
34/34 [==============================] - 35s 1s/step - loss: 0.0692 - accuracy: 0.9716 - val_loss: 0.0464 - val_accuracy: 0.9837
Epoch 4/10
调试： (2, 32, 19) (32, 19, 28)
 1/34 [..............................] - ETA: 24s - loss: 0.0412 - accuracy: 0.9848调试： (2, 32, 19) (32, 19, 28)
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32/34 [===========================>..] - ETA: 1s - loss: 0.0450 - accuracy: 0.9825调试： (2, 32, 19) (32, 19, 28)
33/34 [============================>.] - ETA: 0s - loss: 0.0444 - accuracy: 0.9828调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 9, 19) (9, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)
调试： (2, 32, 19) (32, 19, 28)

Epoch 00004: val_loss improved from 0.04645 to 0.04206, saving model to entity_weights.h5
34/34 [==============================] - 35s 1s/step - loss: 0.0444 - accuracy: 0.9827 - val_loss: 0.0421 - val_accuracy: 0.9858
Epoch 5/10
调试： (2, 32, 19) (32, 19, 28)
 1/34 [..............................] - ETA: 25s - loss: 0.0393 - accuracy: 0.9857调试： (2, 32, 19) (32, 19, 28)
 2/34 [>.............................] - ETA: 24s - loss: 0.0553 - accuracy: 0.9816调试： (2, 32, 19) (32, 19, 28)
 3/34 [=>............................] - ETA: 23s - loss: 0.0487 - accuracy: 0.9846调试： (2, 32, 19) (32, 19, 28)
 4/34 [==>...........................] - ETA: 23s - loss: 0.0454 - accuracy: 0.9843调试： (2, 32, 19) (32, 19, 28)
 5/34 [===>..........................] - ETA: 22s - loss: 0.0418 - accuracy: 0.9852调试： (2, 32, 19) (32, 19, 28)
 6/34 [====>.........................] - ETA: 21s - loss: 0.0408 - accuracy: 0.9854调试： (2, 32, 19) (32, 19, 28)
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10/34 [=======>......................] - ETA: 18s - loss: 0.0372 - accuracy: 0.9883调试： (2, 32, 19) (32, 19, 28)
11/34 [========>.....................] - ETA: 17s - loss: 0.0364 - accuracy: 0.9877调试： (2, 32, 19) (32, 19, 28)
12/34 [=========>....................] - ETA: 16s - loss: 0.0371 - accuracy: 0.9878调试： (2, 32, 19) (32, 19, 28)
13/34 [==========>...................] - ETA: 16s - loss: 0.0366 - accuracy: 0.9881调试： (2, 32, 19) (32, 19, 28)
14/34 [===========>..................] - ETA: 15s - loss: 0.0351 - accuracy: 0.9887调试： (2, 32, 19) (32, 19, 28)
15/34 [============>.................] - ETA: 14s - loss: 0.0346 - accuracy: 0.9888调试： (2, 32, 19) (32, 19, 28)
16/34 [=============>................] - ETA: 13s - loss: 0.0357 - accuracy: 0.9877调试： (2, 32, 19) (32, 19, 28)
17/34 [==============>...............] - ETA: 12s - loss: 0.0345 - accuracy: 0.9883调试： (2, 32, 19) (32, 19, 28)

9、Core解析（数据、训练）

9.1、Core相关数据解析

from rasa.core.train import get_no_of_stories
from rasa.core.domain import TemplateDomain
from rasa.core.training.dsl import StoryFileReader
from rasa.core.training.structures import Story,StoryGraph,StoryStep,StoryStringHelper

story_file = 'data/stories.md'
stories = await StoryFileReader.read_from_folder(story_file, 
                               TemplateDomain.load(domain_file)) #返回Story类的元素List[StoryStep]

stories_generate = Story(story_steps=stories, story_name='my_stories') #Story类中包含StoryStep--即单个story
# <rasa.core.training.structures.Story at 0x2eb464dee08>
print(stories_generate.__dict__)

storyStep_0 = stories[0]
print(storyStep_0.__dict__)
print(storyStep_0.events[0].__dict__)
print(storyStep_0.events[4].__dict__)

storyStep_2 = stories[2]
print(storyStep_2.__dict__)
print(storyStep_2.events[0].__dict__)
storyStep_2.events[14].__dict__

no_stories = await get_no_of_stories('data/stories.md', domain_file)
#no_stories = len(stories)
storyGraph = StoryGraph(stories)
print(storyGraph.__dict__)

9.2、stories训练数据扩增方法解析

##加载stories文件，生成训练数据
from rasa.importers.importer import TrainingDataImporter
from rasa.core.training import load_data
from rasa.core.training.generator import (
    TrainingDataGenerator,                                 
    TrackerLookupDict,TrackersTuple,
    TrackerWithCachedStates
)

trainingDataImporter = TrainingDataImporter().load_from_config(configs_file,
                                           domain_file,training_files)

await trainingDataImporter.get_config()
await trainingDataImporter.get_nlu_data()

trainDataGenerator = TrainingDataGenerator(storyGraph, domain)
trainDataGenerator.__dict__
'''
{'story_graph': <rasa.core.training.structures.c at 0x2eb47d88348>,
 'domain': <rasa.core.domain.Domain at 0x2eb46595d08>,
 'config': ExtractorConfig(remove_duplicates=True, unique_last_num_states=None, augmentation_factor=50, max_number_of_augmented_trackers=500, tracker_limit=None, use_story_concatenation=True, rand=<random.Random object at 0x000002EAFE7BB0F8>),
 'hashed_featurizations': set()}
'''
list_TrackerWithCachedStates = trainDataGenerator.generate()
len(list_TrackerWithCachedStates) #522
trackerWithCachedStates = list_TrackerWithCachedStates[100]
trackerWithCachedStates.__dict__
agent.train(list_TrackerWithCachedStates)

##story数据扩增解析
#from  rasa.core.training.generator import generate
from rasa.core.training.dsl import StoryFileReader
from rasa.core.training.structures import Story,StoryGraph,StoryStep
from rasa.core.training.generator import TrainingDataGenerator
from rasa.core.domain import TemplateDomain

story_file = 'data_1/stories_4.md'
stories = await StoryFileReader.read_from_folder(story_file, 
                               TemplateDomain.load(domain_file)) #返回Story类的元素List[StoryStep]
storyGraph = StoryGraph(stories)
storyGraph.__dict__ #保存到storyGraph.txt中

trainDataGenerator = TrainingDataGenerator(storyGraph, domain)
list_TrackerWithCachedStates = trainDataGenerator.generate()
len(list_TrackerWithCachedStates) #244
trackerWithCachedStates = list_TrackerWithCachedStates[4]
trackerWithCachedStates.__dict__
trackerWithCachedStates.export_stories()

export_stories_path = r'parsed_datas\stories augment\augmented_stories.md'
for tr in list_TrackerWithCachedStates:
    tr.export_stories_to_file(export_stories_path)

9.3、Policy训练解析

policy_ensemble生成

ensemble = agent._create_ensemble(policies)
ensemble.__dict__
ensemble.policies
'''
[<rasa.core.policies.two_stage_fallback.TwoStageFallbackPolicy at 0x20b41124a48>,
 <rasa.core.policies.memoization.MemoizationPolicy at 0x20b410d3fc8>,
 <rasa.core.policies.form_policy.FormPolicy at 0x20b411249c8>,
 <rasa.core.policies.mapping_policy.MappingPolicy at 0x20b41124108>,
 <rasa.core.policies.keras_policy.KerasPolicy at 0x20b41207a88>]
'''
twoStageFallbackPolicy = ensemble.policies[0]
twoStageFallbackPolicy.__dict__
memoizationPolicy = ensemble.policies[1]
memoizationPolicy.__dict__
formPolicy = ensemble.policies[2]
formPolicy.__dict__
mappingPolicy = ensemble.policies[3]
mappingPolicy.__dict__
kerasPolicy = ensemble.policies[4]
kerasPolicy.__dict__
kerasPolicy.train(list_TrackerWithCachedStates, domain)

keras_policy 单独训练

###keras_policy train
from rasa.core.featurizers import MaxHistoryTrackerFeaturizer

maxHistoryTrackerFeaturizer = kerasPolicy.featurizer
maxHistoryTrackerFeaturizer.use_intent_probabilities = True

training_data = kerasPolicy.featurize_for_training(list_TrackerWithCachedStates, domain)
training_data.y.shape #(1266, 74)
training_data.X.shape #(1266, 5, 135)
training_data.max_history()  #5

list_TrackerWithCachedStates[0].events
list_TrackerWithCachedStates[0].as_dialogue().as_dict()
states = maxHistoryTrackerFeaturizer._create_states(list_TrackerWithCachedStates[0], domain)
trackers_as_states = maxHistoryTrackerFeaturizer.prediction_states(list_TrackerWithCachedStates, domain)
tracker_0 = list_TrackerWithCachedStates[0]
tracker_0.export_stories()
tracker_0.export_stories_to_file('tracker_0.json')

ted_policy单独训练

tEDPolicy = ensemble.policies[5]
tEDPolicy.__dict__
tEDPolicy.train(list_TrackerWithCachedStates, domain)
tEDPolicy
label_data = tEDPolicy._create_label_data(domain)
label_data.__dict__