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model: | |
base_learning_rate: 2.0e-06 | |
target: ldm.models.diffusion.ddpm.LatentDiffusion | |
params: | |
linear_start: 0.0015 | |
linear_end: 0.0195 | |
num_timesteps_cond: 1 | |
log_every_t: 200 | |
timesteps: 1000 | |
first_stage_key: image | |
image_size: 64 | |
channels: 3 | |
monitor: val/loss_simple_ema | |
unet_config: | |
target: ldm.modules.diffusionmodules.openaimodel.UNetModel | |
params: | |
image_size: 64 | |
in_channels: 3 | |
out_channels: 3 | |
model_channels: 224 | |
attention_resolutions: | |
# note: this isn\t actually the resolution but | |
# the downsampling factor, i.e. this corresnponds to | |
# attention on spatial resolution 8,16,32, as the | |
# spatial reolution of the latents is 64 for f4 | |
- 8 | |
- 4 | |
- 2 | |
num_res_blocks: 2 | |
channel_mult: | |
- 1 | |
- 2 | |
- 3 | |
- 4 | |
num_head_channels: 32 | |
first_stage_config: | |
target: ldm.models.autoencoder.VQModelInterface | |
params: | |
ckpt_path: configs/first_stage_models/vq-f4/model.yaml | |
embed_dim: 3 | |
n_embed: 8192 | |
ddconfig: | |
double_z: false | |
z_channels: 3 | |
resolution: 256 | |
in_channels: 3 | |
out_ch: 3 | |
ch: 128 | |
ch_mult: | |
- 1 | |
- 2 | |
- 4 | |
num_res_blocks: 2 | |
attn_resolutions: [] | |
dropout: 0.0 | |
lossconfig: | |
target: torch.nn.Identity | |
cond_stage_config: __is_unconditional__ | |
data: | |
target: main.DataModuleFromConfig | |
params: | |
batch_size: 48 | |
num_workers: 5 | |
wrap: false | |
train: | |
target: ldm.data.lsun.LSUNBedroomsTrain | |
params: | |
size: 256 | |
validation: | |
target: ldm.data.lsun.LSUNBedroomsValidation | |
params: | |
size: 256 | |
lightning: | |
callbacks: | |
image_logger: | |
target: main.ImageLogger | |
params: | |
batch_frequency: 5000 | |
max_images: 8 | |
increase_log_steps: False | |
trainer: | |
benchmark: True |