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config.json
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config.json
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{
"training": {
"batch_size": 32,
"num_epochs": 100000,
"log_freq": 1000,
"checkpoint_freq": 10000,
"sampling_freq": 10000,
"snapshot_sampling": true,
"sde": "vesde"
},
"sampling": {
"batch_size": 8
},
"data": {
"data_path": "trainH.h5",
"data_size": 8192,
"num_channels": 2
},
"model": {
"sigma_min": 0.1,
"sigma_max": 2000.0,
"num_scales": 1000,
"dropout": 0.1,
"embedding_type": "fourier",
"name": "ncsnpp1d",
"ema_rate": 0.999,
"normalization": "GroupNorm",
"nonlinearity": "swish",
"nf": 32,
"ch_mult": [1,1,2,2,2,2,1,1,1],
"num_res_blocks": 1,
"attn_resolutions": [],
"resamp_with_conv": true,
"conditional": false,
"fir": false,
"fir_kernel": [
1,
3,
1
],
"skip_rescale": true,
"resblock_type": "biggan",
"progressive": "none",
"progressive_input": "none",
"progressive_combine": "sum",
"attention_type": "ddpm",
"init_scale": 0.0,
"fourier_scale": 16,
"conv_size": 3
},
"optim": {
"weight_decay": 0,
"optimizer": "Adam",
"lr": 1e-5,
"beta1": 0.9,
"eps": 1e-8,
"warmup": 5000,
"grad_clip": 1.0
},
"seed": 42
}