2020-12-18 23:21:01 +00:00
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#### general settings
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name: train_faces_glean
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use_tb_logger: true
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model: extensibletrainer
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scale: 8
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gpu_ids: [0]
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fp16: false
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start_step: -1
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checkpointing_enabled: true
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wandb: false
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datasets:
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train:
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n_workers: 4
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batch_size: 32
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name: ffhq
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mode: imagefolder
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paths: /content/flickr_faces_hq # <-- Put your data path here.
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target_size: 256
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scale: 8
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networks:
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generator:
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type: generator
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which_model_G: glean
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nf: 64
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2020-12-26 20:49:27 +00:00
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latent_bank_pretrained_weights: ../experiments/stylegan2-ffhq-config-f.pth
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2020-12-18 23:21:01 +00:00
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feature_discriminator:
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type: discriminator
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which_model_D: discriminator_vgg_128_gn
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extra_conv: true
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scale: 2
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nf: 64
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in_nc: 3
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image_size: 256
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#### path
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path:
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#pretrain_model_generator: <insert pretrained *GLEAN* model path if desired. Pretrained stylegan goes above.>
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strict_load: true
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#resume_state: ../experiments/train_faces_glean/training_state/0.state # <-- Uncomment to continue training at a checkpoint.
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steps:
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feature_discriminator:
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training: feature_discriminator
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after: 10000 # Delays starting discriminator training until step 10k
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# Optimizer params
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lr: !!float 2e-4
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weight_decay: 0
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beta1: 0.9
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beta2: 0.99
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injectors:
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dgen_inj:
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type: generator
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generator: generator
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grad: false
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in: lq
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out: dgen
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losses:
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gan_disc_img:
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type: discriminator_gan
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gan_type: gan
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weight: 1
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noise: .004
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gradient_penalty: true
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real: hq
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fake: dgen
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generator:
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training: generator
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optimizer_params:
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# Optimizer params
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lr: !!float 2e-4
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weight_decay: 0
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beta1: 0.9
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beta2: 0.99
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injectors:
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gen_inj:
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type: generator
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generator: generator
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in: lq
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out: gen
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losses:
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pix:
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type: pix
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2020-12-19 15:26:07 +00:00
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weight: 1
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criterion: l2
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2020-12-18 23:21:01 +00:00
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real: hq
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fake: gen
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feature:
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type: feature
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after: 5000
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which_model_F: vgg
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2020-12-19 15:26:07 +00:00
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criterion: l2
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weight: .01
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2020-12-18 23:21:01 +00:00
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real: hq
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fake: gen
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gan_gen_img:
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after: 10000
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type: generator_gan
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gan_type: gan
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2020-12-19 15:26:07 +00:00
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weight: .01
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2020-12-18 23:21:01 +00:00
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noise: .004
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discriminator: feature_discriminator
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fake: gen
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real: hq
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train:
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niter: 500000
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warmup_iter: -1
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mega_batch_factor: 1 # <-- Gradient accumulation factor. If you are running OOM, increase this to [2,4,8].
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val_freq: 4000 # No validation currently in this config, this is irrelevant.
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# Default LR scheduler options
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default_lr_scheme: MultiStepLR
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gen_lr_steps: [40000, 80000, 100000, 120000]
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lr_gamma: 0.5
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eval:
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output_state: gen
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logger:
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print_freq: 30
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save_checkpoint_freq: 2000
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visuals: [gen, hq, lq]
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visual_debug_rate: 100
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