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AUTOMATIC1111
GitHub Repository: AUTOMATIC1111/stable-diffusion-webui
 Path: blob/master/configs/sd_xl_inpaint.yaml
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model:

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  target: sgm.models.diffusion.DiffusionEngine

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  params:

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    scale_factor: 0.13025

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    disable_first_stage_autocast: True

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    denoiser_config:

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      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser

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      params:

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        num_idx: 1000

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        weighting_config:

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          target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting

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        scaling_config:

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          target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling

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        discretization_config:

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          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization

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    network_config:

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      target: sgm.modules.diffusionmodules.openaimodel.UNetModel

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      params:

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        adm_in_channels: 2816

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        num_classes: sequential

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        use_checkpoint: False

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        in_channels: 9

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        out_channels: 4

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        model_channels: 320

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        attention_resolutions: [4, 2]

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        num_res_blocks: 2

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        channel_mult: [1, 2, 4]

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        num_head_channels: 64

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        use_spatial_transformer: True

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        use_linear_in_transformer: True

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        transformer_depth: [1, 2, 10]  # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16

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        context_dim: 2048

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        spatial_transformer_attn_type: softmax-xformers

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        legacy: False

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    conditioner_config:

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      target: sgm.modules.GeneralConditioner

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      params:

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        emb_models:

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          # crossattn cond

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          - is_trainable: False

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            input_key: txt

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            target: sgm.modules.encoders.modules.FrozenCLIPEmbedder

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            params:

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              layer: hidden

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              layer_idx: 11

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          # crossattn and vector cond

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          - is_trainable: False

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            input_key: txt

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            target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2

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            params:

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              arch: ViT-bigG-14

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              version: laion2b_s39b_b160k

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              freeze: True

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              layer: penultimate

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              always_return_pooled: True

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              legacy: False

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          # vector cond

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          - is_trainable: False

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            input_key: original_size_as_tuple

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            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND

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            params:

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              outdim: 256  # multiplied by two

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          # vector cond

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          - is_trainable: False

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            input_key: crop_coords_top_left

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            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND

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            params:

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              outdim: 256  # multiplied by two

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          # vector cond

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          - is_trainable: False

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            input_key: target_size_as_tuple

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            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND

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            params:

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              outdim: 256  # multiplied by two

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    first_stage_config:

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      target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper

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      params:

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        embed_dim: 4

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        monitor: val/rec_loss

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        ddconfig:

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          attn_type: vanilla-xformers

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          double_z: true

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          z_channels: 4

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          resolution: 256

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          in_channels: 3

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          out_ch: 3

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          ch: 128

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          ch_mult: [1, 2, 4, 4]

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          num_res_blocks: 2

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          attn_resolutions: []

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          dropout: 0.0

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        lossconfig:

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          target: torch.nn.Identity

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