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Merge pull request #391 from yinhaofeng/ncf
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Ncf
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seemingwang authored Mar 23, 2021
2 parents 26ef070 + f7caf1d commit 623e14d
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2 changes: 1 addition & 1 deletion models/recall/ncf/config.yaml
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Expand Up @@ -24,7 +24,7 @@ runner:

test_data_dir: "data/test"
infer_reader_path: "movielens_reader" # importlib format
infer_batch_size: 5
infer_batch_size: 1
infer_load_path: "output_model_ncf"
infer_start_epoch: 2
infer_end_epoch: 3
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4 changes: 3 additions & 1 deletion models/recall/ncf/readme.md
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Expand Up @@ -61,7 +61,7 @@ os : windows/linux/macos
# 动态图训练
python -u ../../../tools/trainer.py -m config.yaml # 全量数据运行config_bigdata.yaml
# 动态图预测
python -u infer.py -m config.yaml
python -u ../../../tools/infer.py -m config.yaml

# 静态图训练
python -u ../../../tools/static_trainer.py -m config.yaml # 全量数据运行config_bigdata.yaml
Expand All @@ -85,11 +85,13 @@ python -u ../../../tools/static_infer.py -m config.yaml

1. 确认您当前所在目录为PaddleRec/models/recall/ncf
2. 进入paddlerec/datasets/movielens_pinterest_NCF目录下,执行该脚本,会从国内源的服务器上下载我们预处理完成的movielens和pinterest全量数据集,并解压到指定文件夹。

``` bash
cd ../../../datasets/movielens_pinterest_NCF
sh run.sh
```
3. 切回模型目录,执行命令运行全量数据

```bash
cd - # 切回模型目录
# 动态图训练并得到指标(这里需要使用bash启动脚本)
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