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+ model:
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+ base_learning_rate: 1.0e-04
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+ target: ldm.models.diffusion.ddpm.LatentDiffusion
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+ params:
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+ linear_start: 0.00085
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+ linear_end: 0.0120
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+ num_timesteps_cond: 1
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+ log_every_t: 200
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+ timesteps: 1000
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+ first_stage_key: "image"
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+ cond_stage_key: "caption"
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+ image_size: 64
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+ channels: 4
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+ cond_stage_trainable: false # Note: different from the one we trained before
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+ conditioning_key: crossattn
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+ monitor: val/loss_simple_ema
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+ scale_factor: 0.18215
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+ use_ema: False
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+
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+ scheduler_config: # 10000 warmup steps
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+ target: ldm.lr_scheduler.LambdaLinearScheduler
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+ params:
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+ warm_up_steps: [ 10000 ]
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+ cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
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+ f_start: [ 1.e-6 ]
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+ f_max: [ 1. ]
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+ f_min: [ 1. ]
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+
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+ unet_config:
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+ target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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+ params:
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+ image_size: 32 # unused
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+ in_channels: 4
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+ out_channels: 4
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+ attention_resolutions: [ 4, 2, 1 ]
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+ transformer_depth: 1
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+ context_dim: 768
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+ use_checkpoint: True
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+ legacy: False
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+
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+ first_stage_config:
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+ target: ldm.models.autoencoder.AutoencoderKL
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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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+ 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:
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+ - 1
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+ - 2
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+ - 4
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+ - 4
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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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+
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+ cond_stage_config:
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+ target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
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