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config.yml
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config.yml
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### model params
Model:
in_channels: 3
out_channels: 3
model_channels: 128
attention_resolutions: [2, ]
num_res_blocks: 2
dropout: 0.1
channel_mult: [1, 2, 2, 2]
conv_resample: True
num_heads: 4
### dataset params
Dataset:
dataset: "custom"
train: True
data_path: "data/zhugeliang_face_square"
# If mnist and cifar datasets, whether to download it.
download: True
# specify as needed.
image_size: [ 64, 64 ]
# must be one of {'RGB', 'L', 'CMYK'}.
mode: "RGB"
# decide what suffix to load for the image.
suffix: ["png", "jpg"]
# parameters for torch.utils.data.DataLoader
batch_size: 1
shuffle: True
drop_last: True
pin_memory: True
num_workers: 4
### trainer params
Trainer:
# sample time steps
T: 1000
beta: [0.0001, 0.02]
### callback params
Callback:
# The save path for checkpoint.
filepath: "./checkpoint/Zhu_Geliang.pth"
# Frequency of checkpoint saving.
save_freq: 1
### train params
device: "cuda:0"
epochs: 10
# Whether to continue training, True or False
consume: False
# If continue training, which checkpoint to load
consume_path: "./checkpoint/Zhu_Geliang.pth"
### optimizer params
lr: 0.0002