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# File modified by authors of InstructDiffusion from original (https://github.com/CompVis/stable-diffusion).
# See more details in LICENSE.
model:
base_learning_rate: 1.0e-04
weight_decay: 0.01
target: ldm.models.diffusion.ddpm_edit.LatentDiffusion
params:
fp16: True
deepspeed: 'deepspeed_1'
ckpt_path: stable_diffusion/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly-adaption.ckpt
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
log_every_t: 200
timesteps: 1000
first_stage_key: edited
cond_stage_key: edit
image_size: 32
channels: 4
cond_stage_trainable: false # Note: different from the one we trained before
conditioning_key: hybrid
monitor: val/loss_simple_ema
scale_factor: 0.18215
scheduler_config: # 10000 warmup steps
target: ldm.lr_scheduler.LambdaLinearScheduler
params:
warm_up_steps: [ 0 ]
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: 8
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
force_type_convert: True
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
data:
target: main.DataModuleFromConfig
params:
batch_size: 64
num_workers: 4
train:
- ds1:
target: dataset.pose.pose.MPIIDataset
params:
root: data/mpii/
image_set: train
is_train: True
max_prompt_num: 5
min_prompt_num: 1
radius: 10
- ds2:
target: dataset.pose.pose.COCODataset
params:
root: data/coco/
image_set: train2017
is_train: True
max_prompt_num: 5
min_prompt_num: 1
radius: 10
- ds3:
target: dataset.pose.pose.CrowdPoseDataset
params:
root: data/crowdpose/
image_set: train
is_train: True
max_prompt_num: 5
min_prompt_num: 1
radius: 10
- ds4:
target: dataset.pose.pose.AICDataset
params:
root: data/aic/
image_set: train
is_train: True
max_prompt_num: 5
min_prompt_num: 1
radius: 10
sample_weight: 0.1
- ds5:
target: dataset.seg.coco_stuff.COCOStuffDataset
params:
path: data/coco-stuff
split: train2017
crop_res: 256
flip_prob: 0.5
transparency: 0.5
empty_percentage: 0.2
- ds6:
target: dataset.seg.grefcoco_segmentation.GrefCOCODataset
params:
path: data/coco_2014
split: train
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.0
transparency: 0.5
- ds7:
target: dataset.seg.refcoco_segmentation.RefCOCODataset
params:
path: data/coco_2014
split: train
crop_res: 256
flip_prob: 0.0
transparency: 0.5
- ds8:
target: dataset.low_level.lowlevel_gopro.GoPro
params:
path: data/GoPro
split: train
size: 256
flip_prob: 0.5
interpolation: pil_lanczos
sample_weight: 2.0
- ds9:
target: dataset.low_level.lowlevel_reds.REDS
params:
path: data/REDS
split: train
size: 256
flip_prob: 0.5
interpolation: pil_lanczos
sample_weight: 0.2
- ds10:
target: dataset.low_level.lowlevel_sidd.SIDD
params:
path: data/SIDD
split: train
size: 256
flip_prob: 0.5
interpolation: pil_lanczos
sample_weight: 20
- ds11:
target: dataset.low_level.lowlevel_clwd.CLWD
params:
path: data/CLWD
split: train
size: 256
flip_prob: 0.5
interpolation: pil_lanczos
sample_weight: 0.2
- ds12:
target: dataset.editing.edit_zip_dataset.FilteredIP2PDataset
params:
path: data/clip-filtered-dataset
split: train
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.5
sample_weight: 0.2
- ds13:
target: dataset.editing.edit_zip_dataset.GIERDataset
params:
path: data/GIER_editing_data/
split: train
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.0
zip_start_index: 0
zip_end_index: 100
sample_weight: 2.0
- ds14:
target: dataset.editing.edit_zip_dataset.GQAInpaintDataset
params:
path: data/gqa-inpaint
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.0
- ds15:
target: dataset.editing.edit_zip_dataset.MagicBrushDataset
params:
path: data/MagicBrush/
split: train
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.5
zip_start_index: 0
zip_end_index: 100
- ds16:
target: dataset.editing.edit_zip_dataset.IEIWDataset
params:
path: data/ieiw/
split: train
min_resize_res: 256
max_resize_res: 256
crop_res: 256
flip_prob: 0.5
validation:
target: dataset.pose.pose.COCODataset
params:
root: data/coco/
image_set: val2017
is_train: False
max_prompt_num: 5
min_prompt_num: 1
radius: 10
trainer:
initial_scale: 13
max_epochs: 200
save_freq: 5
accumulate_grad_batches: 1
clip_grad: 0.0
optimizer: adamw |