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File size: 1,219 Bytes
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model:
target: models.unet.UNetModel
params:
image_size: 512
in_channels: 3
model_channels: 32
out_channels: 6
attention_resolutions: [32, 16, 8]
dropout: 0
channel_mult: [1, 2, 4, 8, 8, 16, 16]
num_res_blocks: [1, 2, 2, 2, 2, 3, 4]
conv_resample: True
dims: 2
use_fp16: False
num_head_channels: 64
use_scale_shift_norm: True
resblock_updown: False
use_new_attention_order: False
diffusion:
target: models.script_util.create_gaussian_diffusion
params:
steps: 1000
learn_sigma: True
sigma_small: False
noise_schedule: linear
use_kl: False
predict_xstart: False
rescale_timesteps: False
rescale_learned_sigmas: True
timestep_respacing: ""
train:
lr: 1e-4
batch: [32, 4] # batchsize for training and validation
microbatch: 8
use_fp16: False
num_workers: 16
prefetch_factor: 2
iterations: 800000
weight_decay: 0
scheduler: step # step or cosin
milestones: [10000, 800000]
ema_rates: [0.999]
save_freq: 10000
val_freq: 5000
log_freq: [1000, 2000]
data:
train:
type: face
params:
ffhq_txt: ./datapipe/files_txt/ffhq512.txt
out_size: 512
transform_type: face
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