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Merge pull request #1 from vicgalle/dev
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model: | ||
base_learning_rate: 1.0e-04 | ||
target: ldm.models.diffusion.ddpm.LatentDiffusion | ||
params: | ||
linear_start: 0.00085 | ||
linear_end: 0.0120 | ||
num_timesteps_cond: 1 | ||
log_every_t: 200 | ||
timesteps: 1000 | ||
first_stage_key: "jpg" | ||
cond_stage_key: "txt" | ||
image_size: 64 | ||
channels: 4 | ||
cond_stage_trainable: false # Note: different from the one we trained before | ||
conditioning_key: crossattn | ||
monitor: val/loss_simple_ema | ||
scale_factor: 0.18215 | ||
use_ema: False | ||
|
||
scheduler_config: # 10000 warmup steps | ||
target: ldm.lr_scheduler.LambdaLinearScheduler | ||
params: | ||
warm_up_steps: [10000] | ||
cycle_lengths: [10000000000000] # incredibly large number to prevent corner cases | ||
f_start: [1.e-6] | ||
f_max: [1.] | ||
f_min: [1.] | ||
|
||
unet_config: | ||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel | ||
params: | ||
image_size: 32 # unused | ||
in_channels: 4 | ||
out_channels: 4 | ||
model_channels: 320 | ||
attention_resolutions: [4, 2, 1] | ||
num_res_blocks: 2 | ||
channel_mult: [1, 2, 4, 4] | ||
num_heads: 8 | ||
use_spatial_transformer: True | ||
transformer_depth: 1 | ||
context_dim: 768 | ||
use_checkpoint: True | ||
legacy: False | ||
|
||
first_stage_config: | ||
target: ldm.models.autoencoder.AutoencoderKL | ||
params: | ||
embed_dim: 4 | ||
monitor: val/rec_loss | ||
ddconfig: | ||
double_z: true | ||
z_channels: 4 | ||
resolution: 256 | ||
in_channels: 3 | ||
out_ch: 3 | ||
ch: 128 | ||
ch_mult: | ||
- 1 | ||
- 2 | ||
- 4 | ||
- 4 | ||
num_res_blocks: 2 | ||
attn_resolutions: [] | ||
dropout: 0.0 | ||
lossconfig: | ||
target: torch.nn.Identity | ||
|
||
cond_stage_config: | ||
target: ldm.modules.encoders.modules.PersonalizedCLIPEmbedder | ||
params: | ||
aesthetic_embedding_path: "aesthetic_embeddings/sac_8plus.pt" | ||
T: 3 | ||
lr: 0.0001 |
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