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app/ai_model/teacher_behavior_detection/data/roberta_wwm_ext_large/pytorch_model.bin |
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# teacher_behavior_detection | ||
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#coding:utf-8 | ||
import os | ||
import threading | ||
os.environ["CUDA_VISIBLE_DEVICES"] = "0" | ||
import sys | ||
base_path = os.path.dirname(os.path.realpath(__file__)) | ||
sys.path.append(os.path.join(base_path,'./teacher_behavior_detection')) | ||
sys.path.append(os.path.join(base_path,'./teacher_behavior_detection/src/auto_text_classifier')) | ||
from src.teacher_behavior_detection import detect as model_detect | ||
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m_locker = threading.Lock() | ||
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def detect(*args,**kvargs): | ||
with m_locker: | ||
return model_detect(*args,**kvargs) | ||
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# TeacherBehaviorDetector | ||
输入ASR文本,判断每句话是否为某种教学行为(鼓励、举例、提醒笔记、引导、复述、复习、寒暄、总结)。 | ||
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## 安装 | ||
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1、安装虚拟环境 | ||
```sh | ||
conda create --name=4s_dev python=3.7.5 | ||
source activate behavior_dev | ||
``` | ||
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>确保当前环境是`behavior_dev` | ||
2、安装依赖 | ||
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第一步: | ||
`conda install tensorflow-gpu==1.13.1 cudatoolkit=10.0.130=0` | ||
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第二步: | ||
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`pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html` | ||
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然后 | ||
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`pip install -r requirements_gpu.txt` | ||
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3、为jupyter安装core(可选) | ||
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`ipython kernel install --user --name=behavior_dev` | ||
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这时你发现jupyter 多了一个叫`behavior_dev`的core。 | ||
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删除核心 | ||
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`jupyter kernelspec remove behavior_dev` | ||
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# 算法指标 | ||
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参考算法文档: | ||
https://wiki.zhiyinlou.com/pages/viewpage.action?pageId=99908958 | ||
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# Usage | ||
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参考demo.py |
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app/ai_model/teacher_behavior_detection/data/roberta_wwm_ext_large/config.json
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{ | ||
"architectures": [ | ||
"BertForSequenceClassification" | ||
], | ||
"attention_probs_dropout_prob": 0.1, | ||
"bos_token_id": 0, | ||
"directionality": "bidi", | ||
"eos_token_id": 2, | ||
"eos_token_ids": null, | ||
"hidden_act": "gelu", | ||
"hidden_dropout_prob": 0.1, | ||
"hidden_size": 768, | ||
"id2label": { | ||
"0": "LABEL_0", | ||
"1": "LABEL_1", | ||
"2": "LABEL_2", | ||
"3": "LABEL_3", | ||
"4": "LABEL_4", | ||
"5": "LABEL_5", | ||
"6": "LABEL_6", | ||
"7": "LABEL_7", | ||
"8": "LABEL_8" | ||
}, | ||
"initializer_range": 0.02, | ||
"intermediate_size": 3072, | ||
"label2id": { | ||
"LABEL_0": 0, | ||
"LABEL_1": 1, | ||
"LABEL_2": 2, | ||
"LABEL_3": 3, | ||
"LABEL_4": 4, | ||
"LABEL_5": 5, | ||
"LABEL_6": 6, | ||
"LABEL_7": 7, | ||
"LABEL_8": 8 | ||
}, | ||
"layer_norm_eps": 1e-12, | ||
"max_position_embeddings": 512, | ||
"model_type": "bert", | ||
"num_attention_heads": 12, | ||
"num_hidden_layers": 12, | ||
"output_hidden_states": true, | ||
"output_past": true, | ||
"pad_token_id": 1, | ||
"pooler_fc_size": 768, | ||
"pooler_num_attention_heads": 12, | ||
"pooler_num_fc_layers": 3, | ||
"pooler_size_per_head": 128, | ||
"pooler_type": "first_token_transform", | ||
"type_vocab_size": 2, | ||
"vocab_size": 21128 | ||
} |
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app/ai_model/teacher_behavior_detection/data/roberta_wwm_ext_large/special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |
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app/ai_model/teacher_behavior_detection/data/roberta_wwm_ext_large/tokenizer_config.json
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{"unk_token": "[UNK]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "sep_token": "[SEP]"} |
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