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task: train
runtime_path: ${hydra:runtime.cwd}
ckpt_dir: ${runtime_path}/runs
run_name: train_enc_vq_f8c4_FM
cache_dir: ${ckpt_dir}/cache
run_dir: ${ckpt_dir}/jobs/${run_name}
checkpoint_path: ${run_dir}/checkpoints
dataset:
imagenet_root: imagenet_data
im_size: 128
batch_size: 192
aug_scale: 2
limit: null
distill_teacher: false
dc_ssdae:
compile: false
checkpoint: null
encoder: f8c4
encoder_checkpoint: null
encoder_train: true
decoder: S
trainer_type: FM
encoder_type: vq
sampler:
steps: 10
ema:
decay: 0.999
start_iter: 50000
aux_losses:
compile: ${dc_ssdae.compile}
repa:
i_extract: 4
n_layers: 2
lpips: true
training:
sdpa_kernel: 2
mixed_precision: bf16
grad_accumulate: 1
grad_clip: 0.1
epochs: 20
eval_freq: 1
save_on_best: FID
log_freq: 100
lr: 0.0003
weight_decay: 0.001
losses:
diffusion: 1
repa: 0.25
lpips: 0.5
kl: 1.0e-06
show_samples: 8
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