lama / configs /training /ablv2_work_no_segmpl_csdilirpl.yaml
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run_title: ''
training_model:
kind: default
visualize_each_iters: 1000
concat_mask: True
store_discr_outputs_for_vis: True
losses:
l1:
weight_missing: 0
weight_known: 10
perceptual:
weight: 0
adversarial:
kind: r1
weight: 10
gp_coef: 0.001
mask_as_fake_target: True
allow_scale_mask: True
feature_matching:
weight: 100
resnet_pl:
weight: 1
segmentation: false
optimizers:
generator:
kind: adam
lr: 0.001
discriminator:
kind: adam
lr: 0.0001
visualizer: # override only keys, the rest parameters are kept from defaults/visualizer
key_order:
- image
- predicted_image
- discr_output_fake
- discr_output_real
- inpainted
rescale_keys:
- discr_output_fake
- discr_output_real
defaults:
- location: docker
- data: abl-04-256-mh-dist
- generator: pix2pixhd_global_sigmoid
- discriminator: pix2pixhd_nlayer
- visualizer: directory
- evaluator: default_inpainted
- trainer: any_gpu_large_ssim_ddp_final_benchmark
- hydra: overrides