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| from visualizr.choices import GenerativeType, ModelName | |
| from visualizr.config import PretrainConfig, TrainConfig | |
| def ddpm(): | |
| """ | |
| base configuration for all DDIM-based models. | |
| """ | |
| conf = TrainConfig() | |
| conf.batch_size = 32 | |
| conf.beatgans_gen_type = GenerativeType.ddim | |
| conf.beta_scheduler = "linear" | |
| conf.data_name = "ffhq" | |
| conf.diffusion_type = "beatgans" | |
| conf.eval_ema_every_samples = 200_000 | |
| conf.eval_every_samples = 200_000 | |
| conf.fp16 = True | |
| conf.lr = 1e-4 | |
| conf.model_name = ModelName.beatgans_ddpm | |
| conf.net_attn = (16,) | |
| conf.net_beatgans_attn_head = 1 | |
| conf.net_beatgans_embed_channels = 512 | |
| conf.net_ch_mult = (1, 2, 4, 8) | |
| conf.net_ch = 64 | |
| conf.sample_size = 32 | |
| conf.T_eval = 20 | |
| conf.T = 1000 | |
| conf.make_model_conf() | |
| return conf | |
| def autoenc_base(): | |
| """ | |
| base configuration for all Diff-AE models. | |
| """ | |
| conf = TrainConfig() | |
| conf.batch_size = 32 | |
| conf.beatgans_gen_type = GenerativeType.ddim | |
| conf.beta_scheduler = "linear" | |
| conf.data_name = "ffhq" | |
| conf.diffusion_type = "beatgans" | |
| conf.eval_ema_every_samples = 200_000 | |
| conf.eval_every_samples = 200_000 | |
| conf.fp16 = True | |
| conf.lr = 1e-4 | |
| conf.model_name = ModelName.beatgans_autoenc | |
| conf.net_attn = (16,) | |
| conf.net_beatgans_attn_head = 1 | |
| conf.net_beatgans_embed_channels = 512 | |
| conf.net_beatgans_resnet_two_cond = True | |
| conf.net_ch_mult = (1, 2, 4, 8) | |
| conf.net_ch = 64 | |
| conf.net_enc_channel_mult = (1, 2, 4, 8, 8) | |
| conf.net_enc_pool = "adaptivenonzero" | |
| conf.sample_size = 32 | |
| conf.T_eval = 20 | |
| conf.T = 1000 | |
| conf.make_model_conf() | |
| return conf | |
| def ffhq64_ddpm(): | |
| conf = ddpm() | |
| conf.data_name = "ffhqlmdb256" | |
| conf.warmup = 0 | |
| conf.total_samples = 72_000_000 | |
| conf.scale_up_gpus(4) | |
| return conf | |
| def ffhq64_autoenc(): | |
| conf = autoenc_base() | |
| conf.data_name = "ffhqlmdb256" | |
| conf.warmup = 0 | |
| conf.total_samples = 72_000_000 | |
| conf.net_ch_mult = (1, 2, 4, 8) | |
| conf.net_enc_channel_mult = (1, 2, 4, 8, 8) | |
| conf.eval_every_samples = 1_000_000 | |
| conf.eval_ema_every_samples = 1_000_000 | |
| conf.scale_up_gpus(4) | |
| conf.make_model_conf() | |
| return conf | |
| def celeba64d2c_ddpm(): | |
| conf = ffhq128_ddpm() | |
| conf.data_name = "celebalmdb" | |
| conf.eval_every_samples = 10_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.total_samples = 72_000_000 | |
| conf.name = "celeba64d2c_ddpm" | |
| return conf | |
| def celeba64d2c_autoenc(): | |
| conf = ffhq64_autoenc() | |
| conf.data_name = "celebalmdb" | |
| conf.eval_every_samples = 10_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.total_samples = 72_000_000 | |
| conf.name = "celeba64d2c_autoenc" | |
| return conf | |
| def ffhq128_ddpm(): | |
| conf = ddpm() | |
| conf.data_name = "ffhqlmdb256" | |
| conf.warmup = 0 | |
| conf.total_samples = 48_000_000 | |
| conf.img_size = 128 | |
| conf.net_ch = 128 | |
| # channels: | |
| # 3 => 128 * 1 => 128 * 1 => 128 * 2 => 128 * 3 => 128 * 4 | |
| # sizes: | |
| # 128 => 128 => 64 => 32 => 16 => 8 | |
| conf.net_ch_mult = (1, 1, 2, 3, 4) | |
| conf.eval_every_samples = 1_000_000 | |
| conf.eval_ema_every_samples = 1_000_000 | |
| conf.scale_up_gpus(4) | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.make_model_conf() | |
| return conf | |
| def ffhq128_autoenc_base(): | |
| conf = autoenc_base() | |
| conf.data_name = "ffhqlmdb256" | |
| conf.scale_up_gpus(4) | |
| conf.img_size = 128 | |
| conf.net_ch = 128 | |
| # final resolution = 8x8 | |
| conf.net_ch_mult = (1, 1, 2, 3, 4) | |
| # final resolution = 4x4 | |
| conf.net_enc_channel_mult = (1, 1, 2, 3, 4, 4) | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.make_model_conf() | |
| return conf | |
| def ffhq256_autoenc(): | |
| conf = ffhq128_autoenc_base() | |
| conf.img_size = 256 | |
| conf.net_ch = 128 | |
| conf.net_ch_mult = (1, 1, 2, 2, 4, 4) | |
| conf.net_enc_channel_mult = (1, 1, 2, 2, 4, 4, 4) | |
| conf.eval_every_samples = 10_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.total_samples = 200_000_000 | |
| conf.batch_size = 64 | |
| conf.make_model_conf() | |
| conf.name = "ffhq256_autoenc" | |
| return conf | |
| def ffhq256_autoenc_eco(): | |
| conf = ffhq128_autoenc_base() | |
| conf.img_size = 256 | |
| conf.net_ch = 128 | |
| conf.net_ch_mult = (1, 1, 2, 2, 4, 4) | |
| conf.net_enc_channel_mult = (1, 1, 2, 2, 4, 4, 4) | |
| conf.eval_every_samples = 10_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.total_samples = 200_000_000 | |
| conf.batch_size = 64 | |
| conf.make_model_conf() | |
| conf.name = "ffhq256_autoenc_eco" | |
| return conf | |
| def ffhq128_ddpm_72M(): | |
| conf = ffhq128_ddpm() | |
| conf.total_samples = 72_000_000 | |
| conf.name = "ffhq128_ddpm_72M" | |
| return conf | |
| def ffhq128_autoenc_72M(): | |
| conf = ffhq128_autoenc_base() | |
| conf.total_samples = 72_000_000 | |
| conf.name = "ffhq128_autoenc_72M" | |
| return conf | |
| def ffhq128_ddpm_130M(): | |
| conf = ffhq128_ddpm() | |
| conf.total_samples = 130_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.name = "ffhq128_ddpm_130M" | |
| return conf | |
| def ffhq128_autoenc_130M(): | |
| conf = ffhq128_autoenc_base() | |
| conf.total_samples = 130_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.name = "ffhq128_autoenc_130M" | |
| return conf | |
| def horse128_ddpm(): | |
| conf = ffhq128_ddpm() | |
| conf.data_name = "horse256" | |
| conf.total_samples = 130_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.name = "horse128_ddpm" | |
| return conf | |
| def horse128_autoenc(): | |
| conf = ffhq128_autoenc_base() | |
| conf.data_name = "horse256" | |
| conf.total_samples = 130_000_000 | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.name = "horse128_autoenc" | |
| return conf | |
| def bedroom128_ddpm(): | |
| conf = ffhq128_ddpm() | |
| conf.data_name = "bedroom256" | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.total_samples = 120_000_000 | |
| conf.name = "bedroom128_ddpm" | |
| return conf | |
| def bedroom128_autoenc(): | |
| conf = ffhq128_autoenc_base() | |
| conf.data_name = "bedroom256" | |
| conf.eval_ema_every_samples = 10_000_000 | |
| conf.eval_every_samples = 10_000_000 | |
| conf.total_samples = 120_000_000 | |
| conf.name = "bedroom128_autoenc" | |
| return conf | |
| def pretrain_celeba64d2c_72M(): | |
| conf = celeba64d2c_autoenc() | |
| conf.pretrain = PretrainConfig( | |
| name="72M", | |
| path=f"checkpoints/{celeba64d2c_autoenc().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{celeba64d2c_autoenc().name}/latent.pkl" | |
| return conf | |
| def pretrain_ffhq128_autoenc72M(): | |
| conf = ffhq128_autoenc_base() | |
| conf.postfix = "" | |
| conf.pretrain = PretrainConfig( | |
| name="72M", | |
| path=f"checkpoints/{ffhq128_autoenc_72M().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{ffhq128_autoenc_72M().name}/latent.pkl" | |
| return conf | |
| def pretrain_ffhq128_autoenc130M(): | |
| conf = ffhq128_autoenc_base() | |
| conf.pretrain = PretrainConfig( | |
| name="130M", | |
| path=f"checkpoints/{ffhq128_autoenc_130M().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{ffhq128_autoenc_130M().name}/latent.pkl" | |
| return conf | |
| def pretrain_ffhq256_autoenc(): | |
| conf = ffhq256_autoenc() | |
| conf.pretrain = PretrainConfig( | |
| name="90M", | |
| path=f"checkpoints/{ffhq256_autoenc().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{ffhq256_autoenc().name}/latent.pkl" | |
| return conf | |
| def pretrain_horse128(): | |
| conf = horse128_autoenc() | |
| conf.pretrain = PretrainConfig( | |
| name="82M", | |
| path=f"checkpoints/{horse128_autoenc().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{horse128_autoenc().name}/latent.pkl" | |
| return conf | |
| def pretrain_bedroom128(): | |
| conf = bedroom128_autoenc() | |
| conf.pretrain = PretrainConfig( | |
| name="120M", | |
| path=f"checkpoints/{bedroom128_autoenc().name}/last.ckpt", | |
| ) | |
| conf.latent_infer_path = f"checkpoints/{bedroom128_autoenc().name}/latent.pkl" | |
| return conf | |