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# @package _group_ | |
name: stylenerf_ffhq | |
G_kwargs: | |
class_name: "training.networks.Generator" | |
z_dim: 512 | |
w_dim: 512 | |
mapping_kwargs: | |
num_layers: ${spec.map} | |
synthesis_kwargs: | |
# global settings | |
num_fp16_res: ${num_fp16_res} | |
channel_base: 1 | |
channel_max: 1024 | |
conv_clamp: 256 | |
kernel_size: 1 | |
architecture: skip | |
upsample_mode: "pixelshuffle" | |
z_dim_bg: 0 | |
z_dim: 0 | |
resolution_vol: 128 | |
resolution_start: 32 | |
rgb_out_dim: 256 | |
use_noise: False | |
module_name: "training.stylenerf.NeRFSynthesisNetwork" | |
no_bbox: True | |
margin: 0 | |
magnitude_ema_beta: 0.999 | |
camera_kwargs: | |
range_v: [1.4157963267948965, 1.7257963267948966] | |
range_u: [-3.141592653589793, 3.141592653589793] | |
range_radius: [1.0, 1.0] | |
depth_range: [0.8, 1.2] | |
fov: 16 | |
gaussian_camera: False | |
angular_camera: True | |
depth_transform: ~ | |
dists_normalized: False | |
ray_align_corner: False | |
bg_start: 0.5 | |
renderer_kwargs: | |
n_bg_samples: 0 | |
n_ray_samples: 32 | |
abs_sigma: False | |
hierarchical: True | |
no_background: True | |
foreground_kwargs: | |
downscale_p_by: 1 | |
use_style: "StyleGAN2" | |
predict_rgb: False | |
add_rgb: True | |
use_viewdirs: False | |
n_blocks: 0 | |
input_kwargs: | |
output_mode: 'tri_plane_reshape' | |
input_mode: 'random' | |
in_res: 4 | |
out_res: 256 | |
out_dim: 32 | |
upsampler_kwargs: | |
channel_base: ${model.G_kwargs.synthesis_kwargs.channel_base} | |
channel_max: ${model.G_kwargs.synthesis_kwargs.channel_max} | |
no_2d_renderer: False | |
no_residual_img: False | |
block_reses: ~ | |
shared_rgb_style: False | |
upsample_type: "bilinear" | |
progressive: True | |
# reuglarization | |
n_reg_samples: 0 | |
reg_full: False | |
D_kwargs: | |
class_name: "training.stylenerf.Discriminator" | |
epilogue_kwargs: | |
mbstd_group_size: ${spec.mbstd} | |
num_fp16_res: ${num_fp16_res} | |
channel_base: ${spec.fmaps} | |
channel_max: 512 | |
conv_clamp: 256 | |
architecture: skip | |
progressive: ${model.G_kwargs.synthesis_kwargs.progressive} | |
lowres_head: ${model.G_kwargs.synthesis_kwargs.resolution_start} | |
upsample_type: "bilinear" | |
resize_real_early: True | |
# loss kwargs | |
loss_kwargs: | |
pl_batch_shrink: 2 | |
pl_decay: 0.01 | |
pl_weight: 2 | |
style_mixing_prob: 0.9 | |
curriculum: [500,5000] |