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model:
target: rdm.models.diffusion.ddpm.RDM
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
class_cond: true
image_size: 1
channels: 768
cond_stage_trainable: true
conditioning_key: crossattn
parameterization: x0
use_mean_pooling: true
unet_config:
target: rdm.modules.diffusionmodules.latentmlp.SimpleMLP
params:
in_channels: 768
time_embed_dim: 256
model_channels: 1536
bottleneck_channels: 1536
out_channels: 768
num_res_blocks: 12
use_context: true
context_channels: 512
pretrained_enc_config:
params:
pretrained_enc_arch: dinov3_vitb16
# Set to the absolute path of the downloaded DINOv3 ViT-B/16 checkpoint
# (e.g., dinov3_vitb16_pretrain_lvd1689m-73cec8be.pth). If left null,
# torch.hub will attempt to download using the dinov3 repo helpers.
pretrained_enc_path: /proj/mmfm/kimhi/EnrichCondImageGenerationUsingRCG/TrainRDM/dinov3_vit_b_16_checkpoint.pth
proj_dim: 768
pretrained_enc_withproj: false
dinov3_check_hash: false
# set to false to allow loading checkpoints that don't exactly match the repo architecture
dinov3_load_strict: false
cond_stage_config:
target: rdm.modules.encoders.modules.ClassEmbedder
params:
embed_dim: 512
n_classes: 1000
key: class_label
# Made with Bob