add vae config
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model:
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base_learning_rate: 1.5e-7
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target: ldm.models.autoencoder.AutoencoderKL
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params:
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monitor: "val/rec_loss"
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embed_dim: 4
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lossconfig:
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target: ldm.modules.losses.LPIPSWithDiscriminator
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params:
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disc_start: 50001
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kl_weight: 0.000001
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disc_weight: 0.5
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ddconfig:
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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 ] # num_down = len(ch_mult)-1
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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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data:
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target: main.DataModuleFromConfig
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params:
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num_workers: 16
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batch_size: 16
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wrap: True
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train:
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target: ldm.data.localdanbooruvae.LocalDanbooruBaseVAE
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params:
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data_root: "../dataset"
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size: 256
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mode: "train"
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downscale_f: 8
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validation:
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target: ldm.data.localdanbooruvae.LocalDanbooruBaseVAE
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params:
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data_root: "../dataset"
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size: 256
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mode: "val"
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val_split: 64
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downscale_f: 8
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lightning:
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callbacks:
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image_logger:
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target: main.ImageLogger
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params:
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batch_frequency: 200
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max_images: 4
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increase_log_steps: True
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trainer:
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find_unused_parameters: True
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benchmark: True
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limit_val_batches: 0
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num_sanity_val_steps: 0
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accumulate_grad_batches: 1
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