EasyAnimate / easyanimate /vae /configs /autoencoder /autoencoder_kl_32x32x4_mag_v2.yaml
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Update V5
f62c8b9
model:
base_learning_rate: 1.0e-04
target: easyanimate.vae.ldm.models.omnigen_casual3dcnn.AutoencoderKLMagvit_fromOmnigen
params:
spatial_group_norm: true
mid_block_attention_type: "spatial"
latent_channels: 16
monitor: train/rec_loss
ckpt_path: vae/diffusion_pytorch_model.safetensors
down_block_types: ("SpatialDownBlock3D", "SpatialTemporalDownBlock3D", "SpatialTemporalDownBlock3D",
"SpatialTemporalDownBlock3D",)
up_block_types: ("SpatialUpBlock3D", "SpatialTemporalUpBlock3D", "SpatialTemporalUpBlock3D",
"SpatialTemporalUpBlock3D",)
lossconfig:
target: easyanimate.vae.ldm.modules.losses.LPIPSWithDiscriminator
params:
disc_start: 50001
kl_weight: 1.0e-06
disc_weight: 0.5
l2_loss_weight: 0.1
l1_loss_weight: 1.0
perceptual_weight: 1.0
data:
target: train_vae.DataModuleFromConfig
params:
batch_size: 1
wrap: true
num_workers: 8
train:
target: easyanimate.vae.ldm.data.dataset_image_video.CustomSRTrain
params:
data_json_path: pretrain.json
data_root: /your_data_root # This is used in relative path
size: 256
degradation: pil_nearest
video_size: 256
video_len: 49
slice_interval: 1
validation:
target: easyanimate.vae.ldm.data.dataset_image_video.CustomSRValidation
params:
data_json_path: pretrain.json
data_root: /your_data_root # This is used in relative path
size: 256
degradation: pil_nearest
video_size: 256
video_len: 49
slice_interval: 1
lightning:
callbacks:
image_logger:
target: train_vae.ImageLogger
params:
batch_frequency: 5000
max_images: 8
increase_log_steps: True
trainer:
benchmark: True
accumulate_grad_batches: 1
gpus: "0"
num_nodes: 1