A newer version of the Gradio SDK is available:
6.2.0
Training/test Tips
Flags: see
options/train_options.pyandoptions/base_options.pyfor the training flags; seeoptions/test_options.pyandoptions/base_options.pyfor the test flags. The default values of these options are somtimes adjusted in the model files.CPU/GPU (default
--gpu_ids 0): set--gpu_ids -1to use CPU mode; set--gpu_ids 0,1,2for multi-GPU mode. You need a large batch size (e.g.--batch_size 32) to benefit from multiple GPUs.Visualization: during training, the current results can be viewed using two methods. First, if you set
--display_id> 0, the results and loss plot will appear on a local graphics web server launched by visdom. To do this, you should havevisdominstalled and a server running by the commandpython -m visdom.server. The default server URL ishttp://localhost:8097.display_idcorresponds to the window ID that is displayed on thevisdomserver. Thevisdomdisplay functionality is turned on by default. To avoid the extra overhead of communicating withvisdomset--display_id -1. Second, the intermediate results are saved to[opt.checkpoints_dir]/[opt.name]/web/as an HTML file. To avoid this, set--no_html.Fine-tuning/Resume training: to fine-tune a pre-trained model, or resume the previous training, use the
--continue_trainflag. The program will then load the model based onwhich_epoch. By default, the program will initialize the epoch count as 1. Set--epoch_count <int>to specify a different starting epoch count.