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+ target: ldm.models.diffusion.ddpm.LatentDiffusion
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+ params:
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+ linear_end: 0.0120
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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
17
+ scale_factor: 0.18215
18
+ use_ema: False
19
+
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+ scheduler_config: # 10000 warmup steps
21
+ target: ldm.lr_scheduler.LambdaLinearScheduler
22
+ params:
23
+ warm_up_steps: [ 10000 ]
24
+ 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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+ out_channels: 4
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+ params:
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+ out_ch: 3
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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_end: 0.0120
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+ cond_stage_key: "caption"
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+ image_size: 64
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+ channels: 4
14
+ cond_stage_trainable: false # Note: different from the one we trained before
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+ conditioning_key: crossattn
16
+ monitor: val/loss_simple_ema
17
+ scale_factor: 0.18215
18
+ use_ema: False
19
+
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+ scheduler_config: # 10000 warmup steps
21
+ target: ldm.lr_scheduler.LambdaLinearScheduler
22
+ params:
23
+ warm_up_steps: [ 10000 ]
24
+ 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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+ target: ldm.modules.diffusionmodules.openaimodel.UNetModel
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+ params:
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+ in_channels: 4
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+ out_channels: 4
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+ model_channels: 320
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+ attention_resolutions: [ 4, 2, 1 ]
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+ num_heads: 8
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+ use_spatial_transformer: True
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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
50
+ monitor: val/rec_loss
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+ ddconfig:
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+ double_z: true
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+ z_channels: 4
54
+ resolution: 256
55
+ in_channels: 3
56
+ out_ch: 3
57
+ ch: 128
58
+ ch_mult:
59
+ - 1
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+ - 2
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+ - 4
62
+ - 4
63
+ num_res_blocks: 2
64
+ attn_resolutions: [ ]
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+ dropout: 0.0
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+ lossconfig:
67
+ target: torch.nn.Identity
68
+
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+ cond_stage_config:
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+ target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
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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:
5
+ linear_start: 0.00085
6
+ linear_end: 0.0120
7
+ num_timesteps_cond: 1
8
+ log_every_t: 200
9
+ timesteps: 1000
10
+ first_stage_key: "image"
11
+ cond_stage_key: "caption"
12
+ image_size: 64
13
+ channels: 4
14
+ cond_stage_trainable: false # Note: different from the one we trained before
15
+ conditioning_key: crossattn
16
+ monitor: val/loss_simple_ema
17
+ scale_factor: 0.18215
18
+ use_ema: False
19
+
20
+ scheduler_config: # 10000 warmup steps
21
+ target: ldm.lr_scheduler.LambdaLinearScheduler
22
+ params:
23
+ warm_up_steps: [ 10000 ]
24
+ cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
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+ f_start: [ 1.e-6 ]
26
+ f_max: [ 1. ]
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+ f_min: [ 1. ]
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+ unet_config:
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+ in_channels: 4
34
+ out_channels: 4
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+ model_channels: 320
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+ attention_resolutions: [ 4, 2, 1 ]
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+ num_res_blocks: 2
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+ channel_mult: [ 1, 2, 4, 4 ]
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+ num_heads: 8
40
+ use_spatial_transformer: True
41
+ transformer_depth: 1
42
+ context_dim: 768
43
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44
+ legacy: False
45
+
46
+ first_stage_config:
47
+ target: ldm.models.autoencoder.AutoencoderKL
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+ params:
49
+ embed_dim: 4
50
+ monitor: val/rec_loss
51
+ ddconfig:
52
+ double_z: true
53
+ z_channels: 4
54
+ resolution: 256
55
+ in_channels: 3
56
+ out_ch: 3
57
+ ch: 128
58
+ ch_mult:
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60
+ - 2
61
+ - 4
62
+ - 4
63
+ num_res_blocks: 2
64
+ attn_resolutions: [ ]
65
+ dropout: 0.0
66
+ lossconfig:
67
+ target: torch.nn.Identity
68
+
69
+ cond_stage_config:
70
+ target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
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