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textual_inversion.patch
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textual_inversion.patch
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diff --git a/configs/latent-diffusion/txt2img-1p4B-finetune_save_every_100.yaml b/configs/latent-diffusion/txt2img-1p4B-finetune_save_every_100.yaml
new file mode 100644
index 0000000..e16351d
--- /dev/null
+++ b/configs/latent-diffusion/txt2img-1p4B-finetune_save_every_100.yaml
@@ -0,0 +1,119 @@
+model:
+ base_learning_rate: 5.0e-3
+ target: ldm.models.diffusion.ddpm.LatentDiffusion
+ params:
+ linear_start: 0.00085
+ linear_end: 0.012
+ num_timesteps_cond: 1
+ log_every_t: 200
+ timesteps: 1000
+ first_stage_key: image
+ cond_stage_key: caption
+ image_size: 32
+ channels: 4
+ cond_stage_trainable: true
+ conditioning_key: crossattn
+ monitor: val/loss_simple_ema
+ scale_factor: 0.18215
+ use_ema: False
+ embedding_reg_weight: 0.0
+
+ personalization_config:
+ target: ldm.modules.embedding_manager.EmbeddingManager
+ params:
+ placeholder_strings: ["*"]
+ initializer_words: ["sculpture"]
+ per_image_tokens: false
+ num_vectors_per_token: 10
+ progressive_words: False
+
+ unet_config:
+ target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+ params:
+ image_size: 32
+ in_channels: 4
+ out_channels: 4
+ model_channels: 320
+ attention_resolutions:
+ - 4
+ - 2
+ - 1
+ num_res_blocks: 2
+ channel_mult:
+ - 1
+ - 2
+ - 4
+ - 4
+ num_heads: 8
+ use_spatial_transformer: true
+ transformer_depth: 1
+ context_dim: 1280
+ use_checkpoint: true
+ legacy: False
+
+ first_stage_config:
+ target: ldm.models.autoencoder.AutoencoderKL
+ params:
+ embed_dim: 4
+ monitor: val/rec_loss
+ ddconfig:
+ double_z: true
+ z_channels: 4
+ resolution: 256
+ in_channels: 3
+ out_ch: 3
+ ch: 128
+ ch_mult:
+ - 1
+ - 2
+ - 4
+ - 4
+ num_res_blocks: 2
+ attn_resolutions: []
+ dropout: 0.0
+ lossconfig:
+ target: torch.nn.Identity
+
+ cond_stage_config:
+ target: ldm.modules.encoders.modules.BERTEmbedder
+ params:
+ n_embed: 1280
+ n_layer: 32
+
+
+data:
+ target: main.DataModuleFromConfig
+ params:
+ batch_size: 4
+ num_workers: 2
+ wrap: false
+ train:
+ target: ldm.data.personalized.PersonalizedBase
+ params:
+ size: 256
+ set: train
+ per_image_tokens: false
+ repeats: 100
+ validation:
+ target: ldm.data.personalized.PersonalizedBase
+ params:
+ size: 256
+ set: val
+ per_image_tokens: false
+ repeats: 10
+
+lightning:
+ modelcheckpoint:
+ params:
+ every_n_train_steps: 100
+ callbacks:
+ image_logger:
+ target: main.ImageLogger
+ params:
+ batch_frequency: 500
+ max_images: 8
+ increase_log_steps: False
+
+ trainer:
+ benchmark: True
+ max_steps: 6100
\ No newline at end of file
diff --git a/configs/stable-diffusion/v1-finetune_save_every_100.yaml b/configs/stable-diffusion/v1-finetune_save_every_100.yaml
new file mode 100644
index 0000000..d074f13
--- /dev/null
+++ b/configs/stable-diffusion/v1-finetune_save_every_100.yaml
@@ -0,0 +1,110 @@
+model:
+ base_learning_rate: 5.0e-03
+ target: ldm.models.diffusion.ddpm.LatentDiffusion
+ params:
+ linear_start: 0.00085
+ linear_end: 0.0120
+ num_timesteps_cond: 1
+ log_every_t: 200
+ timesteps: 1000
+ first_stage_key: image
+ cond_stage_key: caption
+ image_size: 64
+ channels: 4
+ cond_stage_trainable: true # Note: different from the one we trained before
+ conditioning_key: crossattn
+ monitor: val/loss_simple_ema
+ scale_factor: 0.18215
+ use_ema: False
+ embedding_reg_weight: 0.0
+ unfreeze_model: False
+ model_lr: 0.0
+
+ personalization_config:
+ target: ldm.modules.embedding_manager.EmbeddingManager
+ params:
+ placeholder_strings: ["*"]
+ initializer_words: ["sculpture"]
+ per_image_tokens: false
+ num_vectors_per_token: 1
+ progressive_words: False
+
+ unet_config:
+ target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+ params:
+ image_size: 32 # unused
+ in_channels: 4
+ out_channels: 4
+ model_channels: 320
+ attention_resolutions: [ 4, 2, 1 ]
+ num_res_blocks: 2
+ channel_mult: [ 1, 2, 4, 4 ]
+ num_heads: 8
+ use_spatial_transformer: True
+ transformer_depth: 1
+ context_dim: 768
+ use_checkpoint: True
+ legacy: False
+
+ first_stage_config:
+ target: ldm.models.autoencoder.AutoencoderKL
+ params:
+ embed_dim: 4
+ monitor: val/rec_loss
+ ddconfig:
+ double_z: true
+ z_channels: 4
+ resolution: 512
+ in_channels: 3
+ out_ch: 3
+ ch: 128
+ ch_mult:
+ - 1
+ - 2
+ - 4
+ - 4
+ num_res_blocks: 2
+ attn_resolutions: []
+ dropout: 0.0
+ lossconfig:
+ target: torch.nn.Identity
+
+ cond_stage_config:
+ target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+
+data:
+ target: main.DataModuleFromConfig
+ params:
+ batch_size: 2
+ num_workers: 2
+ wrap: false
+ train:
+ target: ldm.data.personalized.PersonalizedBase
+ params:
+ size: 512
+ set: train
+ per_image_tokens: false
+ repeats: 100
+ validation:
+ target: ldm.data.personalized.PersonalizedBase
+ params:
+ size: 512
+ set: val
+ per_image_tokens: false
+ repeats: 10
+
+lightning:
+ modelcheckpoint:
+ params:
+ every_n_train_steps: 100
+ callbacks:
+ image_logger:
+ target: main.ImageLogger
+ params:
+ batch_frequency: 100
+ max_images: 8
+ increase_log_steps: False
+
+ trainer:
+ benchmark: True
+ max_steps: 6100
\ No newline at end of file