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update readme and names

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Yicong Hong 2021-01-14 16:44:01 +11:00
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README.md
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@ -47,8 +47,6 @@ Please refer to [vlnbert_init.py](https://github.com/YicongHong/Recurrent-VLN-BE
Please read Peter Anderson's VLN paper for the [R2R Navigation task](https://arxiv.org/abs/1711.07280). Please read Peter Anderson's VLN paper for the [R2R Navigation task](https://arxiv.org/abs/1711.07280).
Our code is based on the code structure of the [EnvDrop](https://github.com/airsplay/R2R-EnvDrop).
### Reproduce Testing Results ### Reproduce Testing Results
To replicate the performance reported in our paper, load the trained network weights and run validation: To replicate the performance reported in our paper, load the trained network weights and run validation:
@ -56,7 +54,7 @@ To replicate the performance reported in our paper, load the trained network wei
bash run/test_agent.bash bash run/test_agent.bash
``` ```
You can simply switch between the OSCAR-based and the PREVALENT-based VLN models by changing the arguments `vlnmodel` (oscar or prevalent) and `load` (trained model paths). You can simply switch between the OSCAR-based and the PREVALENT-based VLN models by changing the arguments `vlnbert` (oscar or prevalent) and `load` (trained model paths).
### Training ### Training

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run/test_agent.bash
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name=VLNBERT-test name=VLNBERT-test-Prevalent
flag="--vlnbert prevalent flag="--vlnbert prevalent

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run/train_agent.bash
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name=VLNBERT-train name=VLNBERT-train-Prevalent
flag="--vlnbert prevalent flag="--vlnbert prevalent