DL-Art-School/recipes/glean/train_ffhq_glean.yml

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