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: "images" | |
cond_stage_key: "input_ids" | |
image_size: 64 | |
channels: 4 | |
cond_stage_trainable: true # 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.FrozenCLIPEmbedder |