sjc / ncsn /bedroom.yml
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Updated app.py
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training:
batch_size: 128
n_epochs: 500000
n_iters: 150001
snapshot_freq: 5000
snapshot_sampling: true
anneal_power: 2
log_all_sigmas: false
sampling:
batch_size: 36
data_init: false
step_lr: 0.0000018
n_steps_each: 3
ckpt_id: 150000
final_only: true
fid: false
denoise: true
num_samples4fid: 10000
inpainting: false
interpolation: false
n_interpolations: 10
fast_fid:
batch_size: 1000
num_samples: 1000
step_lr: 0.0000018
n_steps_each: 3
begin_ckpt: 100000
end_ckpt: 150000
verbose: false
ensemble: false
test:
begin_ckpt: 5000
end_ckpt: 150000
batch_size: 100
data:
dataset: "LSUN"
category: "bedroom"
image_size: 128
channels: 3
logit_transform: false
uniform_dequantization: false
gaussian_dequantization: false
random_flip: true
rescaled: false
num_workers: 32
model:
sigma_begin: 190
num_classes: 1086
ema: true
ema_rate: 0.999
spec_norm: false
sigma_dist: geometric
sigma_end: 0.01
normalization: InstanceNorm++
nonlinearity: elu
ngf: 128
optim:
weight_decay: 0.000
optimizer: "Adam"
lr: 0.0001
beta1: 0.9
amsgrad: false
eps: 0.00000001