|
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 |
|
conditioning_key: crossattn |
|
monitor: val/loss_simple_ema |
|
scale_factor: 0.18215 |
|
use_ema: False |
|
|
|
scheduler_config: |
|
target: ldm.lr_scheduler.LambdaLinearScheduler |
|
params: |
|
warm_up_steps: [ 10000 ] |
|
cycle_lengths: [ 10000000000000 ] |
|
f_start: [ 1.e-6 ] |
|
f_max: [ 1. ] |
|
f_min: [ 1. ] |
|
|
|
unet_config: |
|
target: ldm.modules.diffusionmodules.openaimodel.UNetModel |
|
params: |
|
image_size: 32 |
|
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.FrozenCLIPEmbedder |
|
|
