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@@ -72,7 +72,7 @@ LIAEF128 Cage video:
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[](https://www.youtube.com/watch?v=mRsexePEVco)
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[](https://www.youtube.com/watch?v=mRsexePEVco)
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- **UFM (4GB+)** - U-net Face Morpher model. If "match_style" option choosed, then this model tries to morph src face to target face and fill around face same background. UFM is result of combining modified U-Net, classic face autoencoder, DSSIM and style losses.
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- **UFM (2GB+)** - U-net Face Morpher model. If "match_style" option choosed, then this model tries to morph src face to target face and fill around face same background. UFM is result of combining modified U-Net, classic face autoencoder, DSSIM and style losses.
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@@ -72,6 +72,9 @@ if __name__ == "__main__":
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if 'DFL_BATCH_SIZE' in os.environ.keys():
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if 'DFL_BATCH_SIZE' in os.environ.keys():
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arguments.batch_size = int ( os.environ['DFL_BATCH_SIZE'] )
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arguments.batch_size = int ( os.environ['DFL_BATCH_SIZE'] )
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if 'DFL_WORST_GPU' in os.environ.keys():
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arguments.choose_worst_gpu = True
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from mainscripts import Trainer
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from mainscripts import Trainer
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Trainer.main (
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Trainer.main (
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training_data_src_dir=arguments.training_data_src_dir,
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training_data_src_dir=arguments.training_data_src_dir,
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@@ -106,7 +109,7 @@ if __name__ == "__main__":
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train_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Train on CPU.")
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train_parser.add_argument('--cpu-only', action="store_true", dest="cpu_only", default=False, help="Train on CPU.")
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train_parser.add_argument('--force-gpu-idxs', type=str, dest="force_gpu_idxs", default=None, help="Override final GPU idxs. Example: 0,1,2.")
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train_parser.add_argument('--force-gpu-idxs', type=str, dest="force_gpu_idxs", default=None, help="Override final GPU idxs. Example: 0,1,2.")
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train_parser.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="MultiGPU option (if model supports it). It will select only same best(worst) GPU models.")
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train_parser.add_argument('--multi-gpu', action="store_true", dest="multi_gpu", default=False, help="MultiGPU option (if model supports it). It will select only same best(worst) GPU models.")
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train_parser.add_argument('--choose-worst-gpu', action="store_true", dest="choose_worst_gpu", default=False, help="Choose worst GPU instead of best.")
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train_parser.add_argument('--choose-worst-gpu', action="store_true", dest="choose_worst_gpu", default=False, help="Choose worst GPU instead of best. Environment variable to force True: DFL_WORST_GPU")
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train_parser.add_argument('--force-best-gpu-idx', type=int, dest="force_best_gpu_idx", default=-1, help="Force to choose this GPU idx as best(worst).")
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train_parser.add_argument('--force-best-gpu-idx', type=int, dest="force_best_gpu_idx", default=-1, help="Force to choose this GPU idx as best(worst).")
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train_parser.set_defaults (func=process_train)
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train_parser.set_defaults (func=process_train)
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