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model:
base_learning_rate: 1.0e-04
target: ldm.models.diffusion.ddpm.ImageEmbeddingConditionedLatentDiffusion
params:
embedding_dropout: 0.25
parameterization: "v"
linear_start: 0.00085
linear_end: 0.0120
log_every_t: 200
timesteps: 1000
first_stage_key: "jpg"
cond_stage_key: "txt"
image_size: 96
channels: 4
cond_stage_trainable: false
conditioning_key: crossattn-adm
scale_factor: 0.18215
monitor: val/loss_simple_ema
use_ema: False
embedder_config:
target: ldm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder
noise_aug_config:
target: ldm.modules.encoders.modules.CLIPEmbeddingNoiseAugmentation
params:
timestep_dim: 1024
noise_schedule_config:
timesteps: 1000
beta_schedule: squaredcos_cap_v2
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
num_classes: "sequential"
adm_in_channels: 2048
use_checkpoint: 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: 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"
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