mirror of https://github.com/hpcaitech/ColossalAI
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
110 lines
2.5 KiB
110 lines
2.5 KiB
model:
|
|
base_learning_rate: 1.0e-4
|
|
params:
|
|
parameterization: "v"
|
|
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: txt
|
|
image_size: 64
|
|
channels: 4
|
|
cond_stage_trainable: false
|
|
conditioning_key: crossattn
|
|
monitor: val/loss_simple_ema
|
|
scale_factor: 0.18215
|
|
use_ema: False # we set this to false because this is an inference only config
|
|
|
|
scheduler_config: # 10000 warmup steps
|
|
warm_up_steps: [ 1 ] # NOTE for resuming. use 10000 if starting from scratch
|
|
cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
|
|
f_start: [ 1.e-6 ]
|
|
f_max: [ 1.e-4 ]
|
|
f_min: [ 1.e-10 ]
|
|
|
|
|
|
unet_config:
|
|
use_checkpoint: True
|
|
use_fp16: 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:
|
|
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:
|
|
|
|
|
|
cond_stage_config:
|
|
freeze: True
|
|
layer: "penultimate"
|
|
|
|
data:
|
|
batch_size: 128
|
|
wrap: False
|
|
# num_workwers should be 2 * batch_size, and total num less than 1024
|
|
# e.g. if use 8 devices, no more than 128
|
|
num_workers: 128
|
|
train:
|
|
target: ldm.data.base.Txt2ImgIterableBaseDataset
|
|
params:
|
|
file_path: # YOUR DATASET_PATH
|
|
world_size: 1
|
|
rank: 0
|
|
|
|
lightning:
|
|
trainer:
|
|
accelerator: 'gpu'
|
|
devices: 2
|
|
log_gpu_memory: all
|
|
max_epochs: 2
|
|
precision: 16
|
|
auto_select_gpus: False
|
|
strategy:
|
|
use_chunk: True
|
|
enable_distributed_storage: True
|
|
placement_policy: cuda
|
|
force_outputs_fp32: true
|
|
min_chunk_size: 64
|
|
|
|
log_every_n_steps: 2
|
|
logger: True
|
|
default_root_dir: "/tmp/diff_log/"
|
|
# profiler: pytorch
|
|
|
|
logger_config:
|
|
wandb:
|
|
name: nowname
|
|
save_dir: "/tmp/diff_log/"
|
|
offline: opt.debug
|
|
id: nowname
|