Hancy's picture
init
3274cc5
model:
base_learning_rate: 2.0e-06
target: lidm.models.diffusion.ddpm.LatentDiffusion
params:
linear_start: 0.0015
linear_end: 0.0195
num_timesteps_cond: 1
log_every_t: 100
timesteps: 1000
image_size: [16, 128]
channels: 8
monitor: val/loss_simple_ema
first_stage_key: image
cond_stage_key: camera
conditioning_key: crossattn
cond_stage_trainable: true
verbose: false
unet_config:
target: lidm.modules.diffusion.openaimodel.UNetModel
params:
image_size: [16, 128]
in_channels: 8
out_channels: 8
model_channels: 256
attention_resolutions: [4, 2, 1]
num_res_blocks: 2
channel_mult: [1, 2, 4]
num_head_channels: 32
use_spatial_transformer: true
context_dim: 512
lib_name: lidm
first_stage_config:
target: lidm.models.autoencoder.VQModelInterface
params:
embed_dim: 8
n_embed: 16384
lib_name: lidm
use_mask: False # False
ckpt_path: models/first_stage_models/kitti/f_c2_p4_wo_logscale/model.ckpt
ddconfig:
double_z: false
z_channels: 8
in_channels: 1
out_ch: 1
ch: 64
ch_mult: [1,2,2,4]
strides: [[1,2],[2,2],[2,2]]
num_res_blocks: 2
attn_levels: []
dropout: 0.0
lossconfig:
target: torch.nn.Identity
cond_stage_config:
target: lidm.modules.encoders.modules.FrozenClipMultiImageEmbedder
params:
model: ViT-L/14
split_per_view: 4
key: camera
out_dim: 512
data:
target: main.DataModuleFromConfig
params:
batch_size: 8
num_workers: 8
wrap: true
dataset:
size: [64, 1024]
fov: [ 3,-25 ]
depth_range: [ 1.0,56.0 ]
depth_scale: 56 # np.log2(depth_max + 1)
log_scale: false
x_range: [ -50.0, 50.0 ]
y_range: [ -50.0, 50.0 ]
z_range: [ -3.0, 1.0 ]
resolution: 1
num_channels: 1
num_cats: 10
num_views: 1
num_sem_cats: 19
filtered_map_cats: [ ]
aug:
flip: false
rotate: false
keypoint_drop: false
keypoint_drop_range:
randaug: false
camera_drop: 0.5
train:
target: lidm.data.kitti.KITTI360Train
params:
condition_key: camera
split_per_view: 4
validation:
target: lidm.data.kitti.KITTI360Validation
params:
condition_key: camera
split_per_view: 4
lightning:
callbacks:
image_logger:
target: main.ImageLogger
params:
batch_frequency: 5000
max_images: 8
increase_log_steps: False
trainer:
benchmark: True