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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: "image" | ||
cond_stage_key: "txt" | ||
image_size: 64 | ||
channels: 4 | ||
cond_stage_trainable: false # Note: different from the one we trained before | ||
conditioning_key: crossattn | ||
scale_factor: 0.18215 | ||
|
||
scheduler_config: # 10000 warmup steps | ||
target: ldm.lr_scheduler.LambdaLinearScheduler | ||
params: | ||
warm_up_steps: [ 1 ] # NOTE for resuming. use 10000 if starting from scratch | ||
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 | ||
ckpt_path: "models/first_stage_models/kl-f8/model.ckpt" | ||
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 | ||
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||
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||
data: | ||
target: main.DataModuleFromConfig | ||
params: | ||
batch_size: 4 | ||
num_workers: 4 | ||
num_val_workers: 0 # Avoid a weird val dataloader issue | ||
train: | ||
# target: ldm.data.simple.hf_dataset | ||
# params: | ||
# name: lambdalabs/pokemon-blip-captions | ||
train: | ||
target: ldm.data.simple.FolderData | ||
params: | ||
root_dir: /home/jovyan/stable-diffusion/data/images/ | ||
caption_file: "/home/jovyan/stable-diffusion/data/captions.json" | ||
image_transforms: | ||
- target: torchvision.transforms.Resize | ||
params: | ||
size: 512 | ||
interpolation: 3 | ||
- target: torchvision.transforms.RandomCrop | ||
params: | ||
size: 512 | ||
- target: torchvision.transforms.RandomHorizontalFlip | ||
validation: | ||
target: ldm.data.simple.TextOnly | ||
params: | ||
captions: | ||
- "the photo of choley bhature with a glass of lassi" | ||
- "the photo of dal makhani in a lunch box" | ||
- "the photo of corn kurkure" | ||
output_size: 512 | ||
n_gpus: 2 # small hack to sure we see all our samples | ||
|
||
|
||
lightning: | ||
find_unused_parameters: False | ||
|
||
modelcheckpoint: | ||
params: | ||
every_n_train_steps: 2000 | ||
save_top_k: -1 | ||
monitor: null | ||
|
||
callbacks: | ||
image_logger: | ||
target: main.ImageLogger | ||
params: | ||
batch_frequency: 2000 | ||
max_images: 4 | ||
increase_log_steps: False | ||
log_first_step: True | ||
log_all_val: True | ||
log_images_kwargs: | ||
use_ema_scope: True | ||
inpaint: False | ||
plot_progressive_rows: False | ||
plot_diffusion_rows: False | ||
N: 4 | ||
unconditional_guidance_scale: 3.0 | ||
unconditional_guidance_label: [""] | ||
|
||
trainer: | ||
benchmark: True | ||
num_sanity_val_steps: 0 | ||
accumulate_grad_batches: 1 |
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