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| model: | |
| target: models.swinir.SwinIR | |
| params: | |
| img_size: 64 | |
| patch_size: 1 | |
| in_chans: 3 | |
| embed_dim: 180 | |
| depths: [6, 6, 6, 6, 6, 6, 6, 6] | |
| num_heads: [6, 6, 6, 6, 6, 6, 6, 6] | |
| window_size: 8 | |
| mlp_ratio: 2 | |
| sf: 8 | |
| img_range: 1.0 | |
| upsampler: "nearest+conv" | |
| resi_connection: "1conv" | |
| unshuffle: True | |
| unshuffle_scale: 8 | |
| train: | |
| lr: 1e-4 | |
| lr_min: 5e-6 | |
| batch: [16, 4] # batchsize for training and validation | |
| microbatch: 2 | |
| num_workers: 8 | |
| prefetch_factor: 2 | |
| iterations: 800000 | |
| weight_decay: 0 | |
| save_freq: 20000 | |
| val_freq: 20000 | |
| log_freq: [100, 2000, 50] | |
| data: | |
| train: | |
| type: gfpgan | |
| params: | |
| files_txt: ./datapipe/files_txt/ffhq512_train.txt | |
| io_backend: | |
| type: disk | |
| use_hflip: true | |
| mean: [0.0, 0.0, 0.0] | |
| std: [1.0, 1.0, 1.0] | |
| out_size: 512 | |
| blur_kernel_size: 41 | |
| kernel_list: ['iso', 'aniso'] | |
| kernel_prob: [0.5, 0.5] | |
| blur_sigma: [0.1, 15] | |
| downsample_range: [0.8, 32] | |
| noise_range: [0, 20] | |
| jpeg_range: [30, 100] | |
| color_jitter_prob: ~ | |
| color_jitter_pt_prob: ~ | |
| gray_prob: 0.01 | |
| gt_gray: True | |
| need_gt_path: False | |
| val: | |
| type: folder | |
| params: | |
| dir_path: /mnt/vdb/IRDiff/Face/testing_data/celeba512_lq | |
| dir_path_gt: /mnt/vdb/IRDiff/Face/testing_data/celeba512_hq | |
| ext: png | |
| need_gt_path: False | |
| length: ~ | |