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This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,98 @@
|
||||
model:
|
||||
target: sgm.models.diffusion.DiffusionEngine
|
||||
params:
|
||||
scale_factor: 0.13025
|
||||
disable_first_stage_autocast: True
|
||||
|
||||
denoiser_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
|
||||
params:
|
||||
num_idx: 1000
|
||||
|
||||
weighting_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting
|
||||
scaling_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
|
||||
discretization_config:
|
||||
target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
|
||||
|
||||
network_config:
|
||||
target: sgm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
adm_in_channels: 2816
|
||||
num_classes: sequential
|
||||
use_checkpoint: True
|
||||
in_channels: 4
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [4, 2]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [1, 2, 4]
|
||||
num_head_channels: 64
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: [1, 2, 10] # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
|
||||
context_dim: 2048
|
||||
spatial_transformer_attn_type: softmax-xformers
|
||||
legacy: False
|
||||
|
||||
conditioner_config:
|
||||
target: sgm.modules.GeneralConditioner
|
||||
params:
|
||||
emb_models:
|
||||
# crossattn cond
|
||||
- is_trainable: False
|
||||
input_key: txt
|
||||
target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
|
||||
params:
|
||||
layer: hidden
|
||||
layer_idx: 11
|
||||
# crossattn and vector cond
|
||||
- is_trainable: False
|
||||
input_key: txt
|
||||
target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
|
||||
params:
|
||||
arch: ViT-bigG-14
|
||||
version: laion2b_s39b_b160k
|
||||
freeze: True
|
||||
layer: penultimate
|
||||
always_return_pooled: True
|
||||
legacy: False
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: original_size_as_tuple
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: crop_coords_top_left
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: target_size_as_tuple
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
|
||||
first_stage_config:
|
||||
target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
attn_type: vanilla-xformers
|
||||
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
|
||||
@@ -0,0 +1,98 @@
|
||||
model:
|
||||
target: sgm.models.diffusion.DiffusionEngine
|
||||
params:
|
||||
scale_factor: 0.13025
|
||||
disable_first_stage_autocast: True
|
||||
|
||||
denoiser_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
|
||||
params:
|
||||
num_idx: 1000
|
||||
|
||||
weighting_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting
|
||||
scaling_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
|
||||
discretization_config:
|
||||
target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
|
||||
|
||||
network_config:
|
||||
target: sgm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
adm_in_channels: 2816
|
||||
num_classes: sequential
|
||||
use_checkpoint: True
|
||||
in_channels: 9
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [4, 2]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [1, 2, 4]
|
||||
num_head_channels: 64
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: [1, 2, 10] # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
|
||||
context_dim: 2048
|
||||
spatial_transformer_attn_type: softmax-xformers
|
||||
legacy: False
|
||||
|
||||
conditioner_config:
|
||||
target: sgm.modules.GeneralConditioner
|
||||
params:
|
||||
emb_models:
|
||||
# crossattn cond
|
||||
- is_trainable: False
|
||||
input_key: txt
|
||||
target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
|
||||
params:
|
||||
layer: hidden
|
||||
layer_idx: 11
|
||||
# crossattn and vector cond
|
||||
- is_trainable: False
|
||||
input_key: txt
|
||||
target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
|
||||
params:
|
||||
arch: ViT-bigG-14
|
||||
version: laion2b_s39b_b160k
|
||||
freeze: True
|
||||
layer: penultimate
|
||||
always_return_pooled: True
|
||||
legacy: False
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: original_size_as_tuple
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: crop_coords_top_left
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: target_size_as_tuple
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
|
||||
first_stage_config:
|
||||
target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
attn_type: vanilla-xformers
|
||||
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
|
||||
@@ -0,0 +1,91 @@
|
||||
model:
|
||||
target: sgm.models.diffusion.DiffusionEngine
|
||||
params:
|
||||
scale_factor: 0.13025
|
||||
disable_first_stage_autocast: True
|
||||
|
||||
denoiser_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
|
||||
params:
|
||||
num_idx: 1000
|
||||
|
||||
weighting_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting
|
||||
scaling_config:
|
||||
target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
|
||||
discretization_config:
|
||||
target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
|
||||
|
||||
network_config:
|
||||
target: sgm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
adm_in_channels: 2560
|
||||
num_classes: sequential
|
||||
use_checkpoint: True
|
||||
in_channels: 4
|
||||
out_channels: 4
|
||||
model_channels: 384
|
||||
attention_resolutions: [4, 2]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [1, 2, 4, 4]
|
||||
num_head_channels: 64
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 4
|
||||
context_dim: [1280, 1280, 1280, 1280] # 1280
|
||||
spatial_transformer_attn_type: softmax-xformers
|
||||
legacy: False
|
||||
|
||||
conditioner_config:
|
||||
target: sgm.modules.GeneralConditioner
|
||||
params:
|
||||
emb_models:
|
||||
# crossattn and vector cond
|
||||
- is_trainable: False
|
||||
input_key: txt
|
||||
target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
|
||||
params:
|
||||
arch: ViT-bigG-14
|
||||
version: laion2b_s39b_b160k
|
||||
legacy: False
|
||||
freeze: True
|
||||
layer: penultimate
|
||||
always_return_pooled: True
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: original_size_as_tuple
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: crop_coords_top_left
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by two
|
||||
# vector cond
|
||||
- is_trainable: False
|
||||
input_key: aesthetic_score
|
||||
target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
|
||||
params:
|
||||
outdim: 256 # multiplied by one
|
||||
|
||||
first_stage_config:
|
||||
target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
attn_type: vanilla-xformers
|
||||
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
|
||||
@@ -0,0 +1,110 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-03
|
||||
target: invokeai.backend.stable_diffusion.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
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ["sculpture"]
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 1
|
||||
progressive_words: False
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.FrozenCLIPEmbedder
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 1
|
||||
num_workers: 2
|
||||
wrap: false
|
||||
train:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: train
|
||||
per_image_tokens: false
|
||||
repeats: 100
|
||||
validation:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: val
|
||||
per_image_tokens: false
|
||||
repeats: 10
|
||||
|
||||
lightning:
|
||||
modelcheckpoint:
|
||||
params:
|
||||
every_n_train_steps: 500
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 500
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
max_steps: 4000000
|
||||
# max_steps: 4000
|
||||
|
||||
@@ -0,0 +1,103 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-03
|
||||
target: invokeai.backend.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
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ["painting"]
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 1
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.FrozenCLIPEmbedder
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 2
|
||||
num_workers: 16
|
||||
wrap: false
|
||||
train:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized_style.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: train
|
||||
per_image_tokens: false
|
||||
repeats: 100
|
||||
validation:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized_style.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: val
|
||||
per_image_tokens: false
|
||||
repeats: 10
|
||||
|
||||
lightning:
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 500
|
||||
max_images: 8
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
@@ -0,0 +1,80 @@
|
||||
model:
|
||||
base_learning_rate: 1.0e-04
|
||||
target: invokeai.backend.models.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
parameterization: "v"
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false # Note: different from the one we trained before
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False
|
||||
|
||||
scheduler_config: # 10000 warmup steps
|
||||
target: invokeai.backend.stable_diffusion.lr_scheduler.LambdaLinearScheduler
|
||||
params:
|
||||
warm_up_steps: [ 10000 ]
|
||||
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
|
||||
f_start: [ 1.e-6 ]
|
||||
f_max: [ 1. ]
|
||||
f_min: [ 1. ]
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ['sculpture']
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 1
|
||||
progressive_words: False
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.WeightedFrozenCLIPEmbedder
|
||||
@@ -0,0 +1,79 @@
|
||||
model:
|
||||
base_learning_rate: 1.0e-04
|
||||
target: invokeai.backend.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: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false # Note: different from the one we trained before
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False
|
||||
|
||||
scheduler_config: # 10000 warmup steps
|
||||
target: invokeai.backend.stable_diffusion.lr_scheduler.LambdaLinearScheduler
|
||||
params:
|
||||
warm_up_steps: [ 10000 ]
|
||||
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
|
||||
f_start: [ 1.e-6 ]
|
||||
f_max: [ 1. ]
|
||||
f_min: [ 1. ]
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ['sculpture']
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 1
|
||||
progressive_words: False
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.WeightedFrozenCLIPEmbedder
|
||||
@@ -0,0 +1,79 @@
|
||||
model:
|
||||
base_learning_rate: 7.5e-05
|
||||
target: invokeai.backend.models.diffusion.ddpm.LatentInpaintDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false # Note: different from the one we trained before
|
||||
conditioning_key: hybrid # important
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
finetune_keys: null
|
||||
|
||||
scheduler_config: # 10000 warmup steps
|
||||
target: invokeai.backend.stable_diffusion.lr_scheduler.LambdaLinearScheduler
|
||||
params:
|
||||
warm_up_steps: [ 2500 ] # NOTE for resuming. use 10000 if starting from scratch
|
||||
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
|
||||
f_start: [ 1.e-6 ]
|
||||
f_max: [ 1. ]
|
||||
f_min: [ 1. ]
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ['sculpture']
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 8
|
||||
progressive_words: False
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
image_size: 32 # unused
|
||||
in_channels: 9 # 4 data + 4 downscaled image + 1 mask
|
||||
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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.WeightedFrozenCLIPEmbedder
|
||||
@@ -0,0 +1,110 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-03
|
||||
target: invokeai.backend.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
|
||||
|
||||
personalization_config:
|
||||
target: invokeai.backend.stable_diffusion.embedding_manager.EmbeddingManager
|
||||
params:
|
||||
placeholder_strings: ["*"]
|
||||
initializer_words: ['sculpture']
|
||||
per_image_tokens: false
|
||||
num_vectors_per_token: 6
|
||||
progressive_words: False
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.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: invokeai.backend.stable_diffusion.encoders.modules.FrozenCLIPEmbedder
|
||||
|
||||
data:
|
||||
target: main.DataModuleFromConfig
|
||||
params:
|
||||
batch_size: 1
|
||||
num_workers: 2
|
||||
wrap: false
|
||||
train:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: train
|
||||
per_image_tokens: false
|
||||
repeats: 100
|
||||
validation:
|
||||
target: invokeai.backend.stable_diffusion.data.personalized.PersonalizedBase
|
||||
params:
|
||||
size: 512
|
||||
set: val
|
||||
per_image_tokens: false
|
||||
repeats: 10
|
||||
|
||||
lightning:
|
||||
modelcheckpoint:
|
||||
params:
|
||||
every_n_train_steps: 500
|
||||
callbacks:
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
batch_frequency: 500
|
||||
max_images: 5
|
||||
increase_log_steps: False
|
||||
|
||||
trainer:
|
||||
benchmark: False
|
||||
max_steps: 6200
|
||||
# max_steps: 4000
|
||||
|
||||
@@ -0,0 +1,68 @@
|
||||
model:
|
||||
base_learning_rate: 1.0e-4
|
||||
target: invokeai.backend.stable_diffusion.diffusion.ddpm.LatentDiffusion
|
||||
params:
|
||||
parameterization: "v"
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False # we set this to false because this is an inference only config
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
use_fp16: True
|
||||
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_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: invokeai.backend.stable_diffusion.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
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: invokeai.backend.stable_diffusion.encoders.modules.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
@@ -0,0 +1,67 @@
|
||||
model:
|
||||
base_learning_rate: 1.0e-4
|
||||
target: invokeai.backend.stable_diffusion.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: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: crossattn
|
||||
monitor: val/loss_simple_ema
|
||||
scale_factor: 0.18215
|
||||
use_ema: False # we set this to false because this is an inference only config
|
||||
|
||||
unet_config:
|
||||
target: invokeai.backend.stable_diffusion.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
use_fp16: True
|
||||
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_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: invokeai.backend.stable_diffusion.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
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: invokeai.backend.stable_diffusion.encoders.modules.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
@@ -0,0 +1,159 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-05
|
||||
target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
parameterization: "v"
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: hybrid
|
||||
scale_factor: 0.18215
|
||||
monitor: val/loss_simple_ema
|
||||
finetune_keys: null
|
||||
use_ema: False
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
image_size: 32 # unused
|
||||
in_channels: 9
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [ 4, 2, 1 ]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1, 2, 4, 4 ]
|
||||
num_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
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.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
|
||||
|
||||
data:
|
||||
target: ldm.data.laion.WebDataModuleFromConfig
|
||||
params:
|
||||
tar_base: null # for concat as in LAION-A
|
||||
p_unsafe_threshold: 0.1
|
||||
filter_word_list: "data/filters.yaml"
|
||||
max_pwatermark: 0.45
|
||||
batch_size: 8
|
||||
num_workers: 6
|
||||
multinode: True
|
||||
min_size: 512
|
||||
train:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-0/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-1/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-2/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-3/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-4/{00000..18699}.tar -" #{00000-94333}.tar"
|
||||
shuffle: 10000
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.RandomCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
# NOTE use enough shards to avoid empty validation loops in workers
|
||||
validation:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://deep-floyd-s3/datasets/laion_cleaned-part5/{93001..94333}.tar - "
|
||||
shuffle: 0
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.CenterCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
|
||||
lightning:
|
||||
find_unused_parameters: True
|
||||
modelcheckpoint:
|
||||
params:
|
||||
every_n_train_steps: 5000
|
||||
|
||||
callbacks:
|
||||
metrics_over_trainsteps_checkpoint:
|
||||
params:
|
||||
every_n_train_steps: 10000
|
||||
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
enable_autocast: False
|
||||
disabled: False
|
||||
batch_frequency: 1000
|
||||
max_images: 4
|
||||
increase_log_steps: False
|
||||
log_first_step: False
|
||||
log_images_kwargs:
|
||||
use_ema_scope: False
|
||||
inpaint: False
|
||||
plot_progressive_rows: False
|
||||
plot_diffusion_rows: False
|
||||
N: 4
|
||||
unconditional_guidance_scale: 5.0
|
||||
unconditional_guidance_label: [""]
|
||||
ddim_steps: 50 # todo check these out for depth2img,
|
||||
ddim_eta: 0.0 # todo check these out for depth2img,
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
val_check_interval: 5000000
|
||||
num_sanity_val_steps: 0
|
||||
accumulate_grad_batches: 1
|
||||
@@ -0,0 +1,158 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-05
|
||||
target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: hybrid
|
||||
scale_factor: 0.18215
|
||||
monitor: val/loss_simple_ema
|
||||
finetune_keys: null
|
||||
use_ema: False
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
image_size: 32 # unused
|
||||
in_channels: 9
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [ 4, 2, 1 ]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1, 2, 4, 4 ]
|
||||
num_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
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.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
|
||||
|
||||
data:
|
||||
target: ldm.data.laion.WebDataModuleFromConfig
|
||||
params:
|
||||
tar_base: null # for concat as in LAION-A
|
||||
p_unsafe_threshold: 0.1
|
||||
filter_word_list: "data/filters.yaml"
|
||||
max_pwatermark: 0.45
|
||||
batch_size: 8
|
||||
num_workers: 6
|
||||
multinode: True
|
||||
min_size: 512
|
||||
train:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-0/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-1/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-2/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-3/{00000..18699}.tar -"
|
||||
- "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-4/{00000..18699}.tar -" #{00000-94333}.tar"
|
||||
shuffle: 10000
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.RandomCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
# NOTE use enough shards to avoid empty validation loops in workers
|
||||
validation:
|
||||
shards:
|
||||
- "pipe:aws s3 cp s3://deep-floyd-s3/datasets/laion_cleaned-part5/{93001..94333}.tar - "
|
||||
shuffle: 0
|
||||
image_key: jpg
|
||||
image_transforms:
|
||||
- target: torchvision.transforms.Resize
|
||||
params:
|
||||
size: 512
|
||||
interpolation: 3
|
||||
- target: torchvision.transforms.CenterCrop
|
||||
params:
|
||||
size: 512
|
||||
postprocess:
|
||||
target: ldm.data.laion.AddMask
|
||||
params:
|
||||
mode: "512train-large"
|
||||
p_drop: 0.25
|
||||
|
||||
lightning:
|
||||
find_unused_parameters: True
|
||||
modelcheckpoint:
|
||||
params:
|
||||
every_n_train_steps: 5000
|
||||
|
||||
callbacks:
|
||||
metrics_over_trainsteps_checkpoint:
|
||||
params:
|
||||
every_n_train_steps: 10000
|
||||
|
||||
image_logger:
|
||||
target: main.ImageLogger
|
||||
params:
|
||||
enable_autocast: False
|
||||
disabled: False
|
||||
batch_frequency: 1000
|
||||
max_images: 4
|
||||
increase_log_steps: False
|
||||
log_first_step: False
|
||||
log_images_kwargs:
|
||||
use_ema_scope: False
|
||||
inpaint: False
|
||||
plot_progressive_rows: False
|
||||
plot_diffusion_rows: False
|
||||
N: 4
|
||||
unconditional_guidance_scale: 5.0
|
||||
unconditional_guidance_label: [""]
|
||||
ddim_steps: 50 # todo check these out for depth2img,
|
||||
ddim_eta: 0.0 # todo check these out for depth2img,
|
||||
|
||||
trainer:
|
||||
benchmark: True
|
||||
val_check_interval: 5000000
|
||||
num_sanity_val_steps: 0
|
||||
accumulate_grad_batches: 1
|
||||
@@ -0,0 +1,74 @@
|
||||
model:
|
||||
base_learning_rate: 5.0e-07
|
||||
target: ldm.models.diffusion.ddpm.LatentDepth2ImageDiffusion
|
||||
params:
|
||||
linear_start: 0.00085
|
||||
linear_end: 0.0120
|
||||
num_timesteps_cond: 1
|
||||
log_every_t: 200
|
||||
timesteps: 1000
|
||||
first_stage_key: "jpg"
|
||||
cond_stage_key: "txt"
|
||||
image_size: 64
|
||||
channels: 4
|
||||
cond_stage_trainable: false
|
||||
conditioning_key: hybrid
|
||||
scale_factor: 0.18215
|
||||
monitor: val/loss_simple_ema
|
||||
finetune_keys: null
|
||||
use_ema: False
|
||||
|
||||
depth_stage_config:
|
||||
target: ldm.modules.midas.api.MiDaSInference
|
||||
params:
|
||||
model_type: "dpt_hybrid"
|
||||
|
||||
unet_config:
|
||||
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
|
||||
params:
|
||||
use_checkpoint: True
|
||||
image_size: 32 # unused
|
||||
in_channels: 5
|
||||
out_channels: 4
|
||||
model_channels: 320
|
||||
attention_resolutions: [ 4, 2, 1 ]
|
||||
num_res_blocks: 2
|
||||
channel_mult: [ 1, 2, 4, 4 ]
|
||||
num_head_channels: 64 # need to fix for flash-attn
|
||||
use_spatial_transformer: True
|
||||
use_linear_in_transformer: True
|
||||
transformer_depth: 1
|
||||
context_dim: 1024
|
||||
legacy: False
|
||||
|
||||
first_stage_config:
|
||||
target: ldm.models.autoencoder.AutoencoderKL
|
||||
params:
|
||||
embed_dim: 4
|
||||
monitor: val/rec_loss
|
||||
ddconfig:
|
||||
#attn_type: "vanilla-xformers"
|
||||
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.FrozenOpenCLIPEmbedder
|
||||
params:
|
||||
freeze: True
|
||||
layer: "penultimate"
|
||||
|
||||
|
||||
Reference in New Issue
Block a user