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add configs for training unconditional/class-conditional ldms
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ablattmann
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Dec 22, 2021
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| model: | ||
| base_learning_rate: 2.0e-06 | ||
| target: ldm.models.diffusion.ddpm.LatentDiffusion | ||
| params: | ||
| linear_start: 0.0015 | ||
| linear_end: 0.0195 | ||
| num_timesteps_cond: 1 | ||
| log_every_t: 200 | ||
| timesteps: 1000 | ||
| first_stage_key: image | ||
| image_size: 64 | ||
| channels: 3 | ||
| monitor: val/loss_simple_ema | ||
|
|
||
| unet_config: | ||
| target: ldm.modules.diffusionmodules.openaimodel.UNetModel | ||
| params: | ||
| image_size: 64 | ||
| in_channels: 3 | ||
| out_channels: 3 | ||
| model_channels: 224 | ||
| attention_resolutions: | ||
| # note: this isn\t actually the resolution but | ||
| # the downsampling factor, i.e. this corresnponds to | ||
| # attention on spatial resolution 8,16,32, as the | ||
| # spatial reolution of the latents is 64 for f4 | ||
| - 8 | ||
| - 4 | ||
| - 2 | ||
| num_res_blocks: 2 | ||
| channel_mult: | ||
| - 1 | ||
| - 2 | ||
| - 3 | ||
| - 4 | ||
| num_head_channels: 32 | ||
| first_stage_config: | ||
| target: ldm.models.autoencoder.VQModelInterface | ||
| params: | ||
| embed_dim: 3 | ||
| n_embed: 8192 | ||
| ckpt_path: models/first_stage_models/vq-f4/model.ckpt | ||
| ddconfig: | ||
| double_z: false | ||
| z_channels: 3 | ||
| resolution: 256 | ||
| in_channels: 3 | ||
| out_ch: 3 | ||
| ch: 128 | ||
| ch_mult: | ||
| - 1 | ||
| - 2 | ||
| - 4 | ||
| num_res_blocks: 2 | ||
| attn_resolutions: [] | ||
| dropout: 0.0 | ||
| lossconfig: | ||
| target: torch.nn.Identity | ||
| cond_stage_config: __is_unconditional__ | ||
| data: | ||
| target: main.DataModuleFromConfig | ||
| params: | ||
| batch_size: 48 | ||
| num_workers: 5 | ||
| wrap: false | ||
| train: | ||
| target: taming.data.faceshq.CelebAHQTrain | ||
| params: | ||
| size: 256 | ||
| validation: | ||
| target: taming.data.faceshq.CelebAHQValidation | ||
| params: | ||
| size: 256 | ||
|
|
||
|
|
||
| lightning: | ||
| callbacks: | ||
| image_logger: | ||
| target: main.ImageLogger | ||
| params: | ||
| batch_frequency: 5000 | ||
| max_images: 8 | ||
| increase_log_steps: False | ||
|
|
||
| trainer: | ||
| benchmark: True |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,98 @@ | ||
| model: | ||
| base_learning_rate: 1.0e-06 | ||
| target: ldm.models.diffusion.ddpm.LatentDiffusion | ||
| params: | ||
| linear_start: 0.0015 | ||
| linear_end: 0.0195 | ||
| num_timesteps_cond: 1 | ||
| log_every_t: 200 | ||
| timesteps: 1000 | ||
| first_stage_key: image | ||
| cond_stage_key: class_label | ||
| image_size: 32 | ||
| channels: 4 | ||
| cond_stage_trainable: true | ||
| conditioning_key: crossattn | ||
| monitor: val/loss_simple_ema | ||
| unet_config: | ||
| target: ldm.modules.diffusionmodules.openaimodel.UNetModel | ||
| params: | ||
| image_size: 32 | ||
| in_channels: 4 | ||
| out_channels: 4 | ||
| model_channels: 256 | ||
| attention_resolutions: | ||
| #note: this isn\t actually the resolution but | ||
| # the downsampling factor, i.e. this corresnponds to | ||
| # attention on spatial resolution 8,16,32, as the | ||
| # spatial reolution of the latents is 32 for f8 | ||
| - 4 | ||
| - 2 | ||
| - 1 | ||
| num_res_blocks: 2 | ||
| channel_mult: | ||
| - 1 | ||
| - 2 | ||
| - 4 | ||
| num_head_channels: 32 | ||
| use_spatial_transformer: true | ||
| transformer_depth: 1 | ||
| context_dim: 512 | ||
| first_stage_config: | ||
| target: ldm.models.autoencoder.VQModelInterface | ||
| params: | ||
| embed_dim: 4 | ||
| n_embed: 16384 | ||
| ckpt_path: configs/first_stage_models/vq-f8/model.yaml | ||
| ddconfig: | ||
| double_z: false | ||
| z_channels: 4 | ||
| resolution: 256 | ||
| in_channels: 3 | ||
| out_ch: 3 | ||
| ch: 128 | ||
| ch_mult: | ||
| - 1 | ||
| - 2 | ||
| - 2 | ||
| - 4 | ||
| num_res_blocks: 2 | ||
| attn_resolutions: | ||
| - 32 | ||
| dropout: 0.0 | ||
| lossconfig: | ||
| target: torch.nn.Identity | ||
| cond_stage_config: | ||
| target: ldm.modules.encoders.modules.ClassEmbedder | ||
| params: | ||
| embed_dim: 512 | ||
| key: class_label | ||
| data: | ||
| target: main.DataModuleFromConfig | ||
| params: | ||
| batch_size: 64 | ||
| num_workers: 12 | ||
| wrap: false | ||
| train: | ||
| target: ldm.data.imagenet.ImageNetTrain | ||
| params: | ||
| config: | ||
| size: 256 | ||
| validation: | ||
| target: ldm.data.imagenet.ImageNetValidation | ||
| params: | ||
| config: | ||
| size: 256 | ||
|
|
||
|
|
||
| lightning: | ||
| callbacks: | ||
| image_logger: | ||
| target: main.ImageLogger | ||
| params: | ||
| batch_frequency: 5000 | ||
| max_images: 8 | ||
| increase_log_steps: False | ||
|
|
||
| trainer: | ||
| benchmark: True |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,85 @@ | ||
| model: | ||
| base_learning_rate: 2.0e-06 | ||
| target: ldm.models.diffusion.ddpm.LatentDiffusion | ||
| params: | ||
| linear_start: 0.0015 | ||
| linear_end: 0.0195 | ||
| num_timesteps_cond: 1 | ||
| log_every_t: 200 | ||
| timesteps: 1000 | ||
| first_stage_key: image | ||
| image_size: 64 | ||
| channels: 3 | ||
| monitor: val/loss_simple_ema | ||
| unet_config: | ||
| target: ldm.modules.diffusionmodules.openaimodel.UNetModel | ||
| params: | ||
| image_size: 64 | ||
| in_channels: 3 | ||
| out_channels: 3 | ||
| model_channels: 224 | ||
| attention_resolutions: | ||
| # note: this isn\t actually the resolution but | ||
| # the downsampling factor, i.e. this corresnponds to | ||
| # attention on spatial resolution 8,16,32, as the | ||
| # spatial reolution of the latents is 64 for f4 | ||
| - 8 | ||
| - 4 | ||
| - 2 | ||
| num_res_blocks: 2 | ||
| channel_mult: | ||
| - 1 | ||
| - 2 | ||
| - 3 | ||
| - 4 | ||
| num_head_channels: 32 | ||
| first_stage_config: | ||
| target: ldm.models.autoencoder.VQModelInterface | ||
| params: | ||
| embed_dim: 3 | ||
| n_embed: 8192 | ||
| ckpt_path: configs/first_stage_models/vq-f4/model.yaml | ||
| ddconfig: | ||
| double_z: false | ||
| z_channels: 3 | ||
| resolution: 256 | ||
| in_channels: 3 | ||
| out_ch: 3 | ||
| ch: 128 | ||
| ch_mult: | ||
| - 1 | ||
| - 2 | ||
| - 4 | ||
| num_res_blocks: 2 | ||
| attn_resolutions: [] | ||
| dropout: 0.0 | ||
| lossconfig: | ||
| target: torch.nn.Identity | ||
| cond_stage_config: __is_unconditional__ | ||
| data: | ||
| target: main.DataModuleFromConfig | ||
| params: | ||
| batch_size: 42 | ||
| num_workers: 5 | ||
| wrap: false | ||
| train: | ||
| target: taming.data.faceshq.FFHQTrain | ||
| params: | ||
| size: 256 | ||
| validation: | ||
| target: taming.data.faceshq.FFHQValidation | ||
| params: | ||
| size: 256 | ||
|
|
||
|
|
||
| lightning: | ||
| callbacks: | ||
| image_logger: | ||
| target: main.ImageLogger | ||
| params: | ||
| batch_frequency: 5000 | ||
| max_images: 8 | ||
| increase_log_steps: False | ||
|
|
||
| trainer: | ||
| benchmark: True |
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