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dataset:
dataset: KMNIST
image_size: 32
channels: 1
sample:
method: ${method}
model_path: YOUR PATH of pretrained ckpt
image_output_path: out
batch_size: 5
total_num: 100
work_dir: ${hydra:runtime.cwd}
method: F-PNDM
sample_speed: 50
seed: 42
model:
_target_: src.model.scoresde.ddpm.DDPM
nf: 128
ch_mult:
- 1
- 2
- 2
- 2
num_res_blocks: 2
attn_resolutions:
- 16
dropout: 0.1
num_channels: 1
resamp_with_conv: true
image_size: 32
conditional: true
centered: true
scheduler:
_target_: src.trainer.scheduler.Schedule
beta_start: 0.0001
beta_end: 0.02
diffusion_step: 1000
train:
optim_cfg:
weight_decay: 0.0
optimizer: adam
lr: 0.0002
beta1: 0.9
amsgrad: false
eps: 1.0e-08
grad_clip: 1.0
epochs: 100
ema_rate: 0.9999
use_ema: true
batch_size: 1024
num_workers: 6
save_path: ./save_ckpt
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