Update other docs with dumb config options
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@ -293,7 +293,7 @@ class Trainer:
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if __name__ == '__main__':
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_exd_mi1_rrdb_bigboi_pretrain.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_faces_glean.yml')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
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parser.add_argument('--local_rank', type=int, default=0)
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parser.add_argument('--local_rank', type=int, default=0)
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args = parser.parse_args()
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args = parser.parse_args()
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@ -15,8 +15,6 @@ def parse(opt_path, is_train=True):
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print('export CUDA_VISIBLE_DEVICES=' + gpu_list)
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print('export CUDA_VISIBLE_DEVICES=' + gpu_list)
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opt['is_train'] = is_train
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opt['is_train'] = is_train
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if opt['distortion'] == 'sr' or opt['distortion'] == 'downsample':
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scale = opt['scale']
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# datasets
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# datasets
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if 'datasets' in opt.keys():
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if 'datasets' in opt.keys():
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@ -2,7 +2,6 @@
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name: train_div2k_byol
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name: train_div2k_byol
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use_tb_logger: true
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use_tb_logger: true
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model: extensibletrainer
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model: extensibletrainer
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distortion: sr
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scale: 1
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scale: 1
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gpu_ids: [0]
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gpu_ids: [0]
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fp16: false
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fp16: false
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@ -2,7 +2,6 @@
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name: train_div2k_srflow
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name: train_div2k_srflow
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use_tb_logger: true
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use_tb_logger: true
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model: extensibletrainer
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model: extensibletrainer
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distortion: sr
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scale: 4
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scale: 4
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gpu_ids: [0]
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gpu_ids: [0]
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fp16: false
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fp16: false
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@ -17,12 +16,10 @@ datasets:
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name: div2k
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name: div2k
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mode: single_image_extensible
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mode: single_image_extensible
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paths: /content/div2k # <-- Put your path here.
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paths: /content/div2k # <-- Put your path here.
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target_size: 160 # <-- SRFlow trains better with factors of 160 for some reason.
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target_size: 160
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force_multiple: 1
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force_multiple: 1
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scale: 4
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scale: 4
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eval: False
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num_corrupts_per_image: 0
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num_corrupts_per_image: 0
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strict: false
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networks:
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networks:
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generator:
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generator:
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