ColossalAI/examples/images/diffusion/configs/Teyvat/train_colossalai_teyvat.yaml

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model:
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base_learning_rate: 1.0e-4
params:
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parameterization: "v"
linear_start: 0.00085
linear_end: 0.0120
num_timesteps_cond: 1
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ckpt: None # use ckpt path
log_every_t: 200
timesteps: 1000
first_stage_key: image
cond_stage_key: txt
image_size: 64
channels: 4
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cond_stage_trainable: false
conditioning_key: crossattn
monitor: val/loss_simple_ema
scale_factor: 0.18215
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use_ema: False
scheduler_config: # 10000 warmup steps
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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 ]
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unet_config:
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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:
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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:
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freeze: True
layer: "penultimate"
data:
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batch_size: 16
num_workers: 4
train:
target: ldm.data.teyvat.hf_dataset
params:
path: Fazzie/Teyvat
image_transforms:
- target: torchvision.transforms.Resize
params:
size: 512
- target: torchvision.transforms.RandomCrop
params:
size: 512
- target: torchvision.transforms.RandomHorizontalFlip
lightning:
trainer:
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accelerator: 'gpu'
devices: 2
log_gpu_memory: all
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max_epochs: 2
precision: 16
auto_select_gpus: False
strategy:
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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/"
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# profiler: pytorch
logger_config:
wandb:
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name: nowname
save_dir: "/tmp/diff_log/"
offline: opt.debug
id: nowname