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model:
target: cldm.cldm.PAIRDiffusion
learning_rate: 1.5e-05
sd_locked: True
only_mid_control: False
init_ckpt: './models/pair_diff_init.ckpt'
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"
control_key: "hint"
image_size: 64
channels: 4
cond_stage_trainable: false
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
use_ema: False
only_mid_control: False
appearance_net_locked: True
app_net: 'DINO'
control_stage_config:
target: cldm.controlnet.ControlNetPAIR
params:
image_size: 32 # unused
in_channels: 4
concat_indices: [0,1]
concat_channels: 130
hint_channels: [1026, 1026, -1, -1] #(1024 + 2)
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
attn_class: ['maskguided', 'maskguided', 'softmax', 'softmax']
unet_config:
target: cldm.cldm.ControlledUnetModel
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: ldm.models.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: ldm.modules.encoders.modules.FrozenCLIPEmbedder
data:
target: cldm.data.DataModuleFromConfig
params:
batch_size: 2
wrap: True
num_workers: 4
train:
target: dataset.txtseg.COCOTrain
params:
image_dir:
caption_file:
panoptic_mask_dir:
seg_dir:
size: 512
validation:
target: dataset.txtseg.COCOValidation
params:
size: 512
image_dir:
caption_file:
panoptic_mask_dir:
seg_dir:
lightning:
callbacks:
image_logger:
target: main.ImageLogger
params:
batch_frequency: 2000
max_images: 4
increase_log_steps: False
log_first_step: True
trainer:
benchmark: True
accumulate_grad_batches: 2 |