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pskun
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Dec 30, 2022
| python gts_engine/gts_engine_inference.py \ | ||
| --task_dir=$TASK_DIR \ | ||
| --engine_type=qiankunding \ | ||
| --task_type=generation \ |
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task type改成keyphrase_generation
| --engine_type=qiankunding \ | ||
| --train_mode=standard \ | ||
| --task_dir=$TASK_DIR \ | ||
| --task_type=generation \ |
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task type改成keyphrase_generation
| --data_dir=$WORK_DIR/examples/text_generation \ | ||
| --save_path=$TASK_DIR/outputs \ | ||
| --pretrained_model_dir=$PRETRAINED_DIR \ | ||
| --train_batchsize=32 \ |
| @@ -0,0 +1,141 @@ | |||
| import json | |||
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目录改成：gts_engine/qiankunding/dataloaders/keyphrase_generation
| @@ -0,0 +1,181 @@ | |||
| from genericpath import exists | |||
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改成：gts_engine/qiankunding/models/keyphrase_generation
| logger = Logger().get_log() | ||
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| class T5KG(BaseModel): |
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叫KeyphraseGenerationT5吧，本身单词也不长
| inputs = self.train_inputs(batch) | ||
| outputs = self.model.generate( | ||
| input_ids = inputs['input_ids'], | ||
| max_length = 32, |
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| outputs = self.model.generate( | ||
| input_ids = inputs['input_ids'], | ||
| max_length=32 |
| self.save_to_file(data_set, results, y_true, y_pred) | ||
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| results.append(pred) | ||
| TP, total_pred, total_true = 0, 0, 0 |
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这里的计算和前面模型的validation_step差不多，为啥不单独抽象出一个公共的函数
| special_tokens += [f"[choice{i+1}]" for i in range(200)] | ||
| # special_tokens += [f"{i+1}" for i in range(200)] | ||
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| print("pretrained_model_path", pretrained_model_path) |
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1.增加Keyphrase Generation项目
2.在examples/text_generation/ 新增 Keyphrase Generation的启动项 以及少量数据
3.新增gts_engine/pipelines/qiankunding_generation.py 主代码
3.新增gts_engine/qiankunding/dataloaders/text_generation/dataloader_kgt5.py的数据处理代码
4.新增gts_engine/qiankunding/models/text_generation/t5_kg.py 模型代码
5.在gts_engine/qiankunding/utils/evaluation.py 中新增 TextGenerateEvaluator 类 用于Generate的评估
6.在gts_engine/qiankunding/utils/tokenization.py中新增 T5的tokenization
7.运行examples/text_generation/run_train_qiankunding.sh 成功如下
8.运行examples/text_generation/run_inference_qiankunding.sh 成功如下
