ZoomLDM / brca /config.yaml
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model:
base_learning_rate: 2.0e-05
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: hybrid
image_size: 64
channels: 3
cond_stage_trainable: true
conditioning_key: crossattn
use_ema: true
x_feat_extracted: true
scheduler_config:
target: ldm.lr_scheduler.LambdaLinearScheduler
params:
warm_up_steps:
- 1000
cycle_lengths:
- 10000000000000
f_start:
- 1.0e-06
f_max:
- 1.0
f_min:
- 1.0
unet_config:
target: ldm.modules.diffusionmodules.openaimodel.UNetModel
params:
use_checkpoint: true
use_fp16: true
image_size: 64
in_channels: 3
out_channels: 3
model_channels: 192
attention_resolutions:
- 8
- 4
- 2
num_res_blocks: 2
channel_mult:
- 1
- 2
- 3
- 5
num_heads: 1
use_spatial_transformer: true
transformer_depth: 1
context_dim: 512
ckpt_path: models/ldm_imgnet_unet.ckpt
first_stage_config:
target: ldm.models.autoencoder.VQModelInterface
params:
# ckpt_path: models/vq_f4.ckpt
embed_dim: 3
n_embed: 8192
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:
target: ldm.modules.encoders.modules.EmbeddingViT2_5
params:
feat_key: ssl_feat
mag_key: mag
num_layers: 12
input_channels: 1024
hidden_channels: 512
vit_mlp_dim: 2048
p_uncond: 0.1
# data:
# target: main.DataModuleFromConfig
# params:
# batch_size: 420
# num_workers: 8
# wrap: false
# train:
# target: ldm.data.brca.TCGADataset
# params:
# config:
# root: ""
# normalize_ssl: true
# feat_target_size: 8