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authorTaesung Park <taesung_park@berkeley.edu>2017-04-20 03:04:34 -0700
committerTaesung Park <taesung_park@berkeley.edu>2017-04-20 03:04:34 -0700
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## Training/test Details
- See `options/train_options.py` and `options/base_options.py` for training flags; see `optoins/test_options.py` and `options/base_options.py` for test flags.
- CPU/GPU: Set `--gpu_ids -1` to use CPU mode; set `--gpu_ids 0,1,2` for multi-GPU mode.
-- During training, you can visualize the result of current training. If you set `--display_id 0`, we will periodically save the training results to `[opt.checkpoints_dir]/[opt.name]/web/`. If you set `--display_id` > 0, the results will be shown on a local graphics web server launched by [szym/display: a lightweight display server for Torch](https://github.com/szym/display). To do this, you should have Torch, Python 3, and the display package installed. You need to invoke `th -ldisplay.start 8000 0.0.0.0` to start the server.
+- During training, you can visualize the result of current training. If you set `--display_id 0`, we will periodically save the training results to `[opt.checkpoints_dir]/[opt.name]/web/`. If you set `--display_id` > 0, the results will be shown on a local graphics web server launched by [visdom](https://github.com/facebookresearch/visdom). To do this, you should visdom installed. You need to invoke `python -m visdom.server` to start the server.
### CycleGAN Datasets
Download the CycleGAN datasets using the following script: