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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 |