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model: | |
pretrained_checkpoint: checkpoints/dynamicrafter_512_v1/model.ckpt | |
base_learning_rate: 1.0e-05 | |
scale_lr: False | |
target: lvdm.models.ddpm3d.LatentVisualDiffusion | |
params: | |
rescale_betas_zero_snr: True | |
parameterization: "v" | |
linear_start: 0.00085 | |
linear_end: 0.012 | |
num_timesteps_cond: 1 | |
log_every_t: 200 | |
timesteps: 1000 | |
first_stage_key: video | |
cond_stage_key: caption | |
cond_stage_trainable: False | |
image_proj_model_trainable: True | |
conditioning_key: hybrid | |
image_size: [40, 64] | |
channels: 4 | |
scale_by_std: False | |
scale_factor: 0.18215 | |
use_ema: False | |
uncond_prob: 0.05 | |
uncond_type: 'empty_seq' | |
rand_cond_frame: true | |
use_dynamic_rescale: true | |
base_scale: 0.7 | |
fps_condition_type: 'fps' | |
perframe_ae: True | |
unet_config: | |
target: lvdm.modules.networks.openaimodel3d.UNetModel | |
params: | |
in_channels: 8 | |
out_channels: 4 | |
model_channels: 320 | |
attention_resolutions: | |
- 4 | |
- 2 | |
- 1 | |
num_res_blocks: 2 | |
channel_mult: | |
- 1 | |
- 2 | |
- 4 | |
- 4 | |
dropout: 0.1 | |
num_head_channels: 64 | |
transformer_depth: 1 | |
context_dim: 1024 | |
use_linear: true | |
use_checkpoint: True | |
temporal_conv: True | |
temporal_attention: True | |
temporal_selfatt_only: true | |
use_relative_position: false | |
use_causal_attention: False | |
temporal_length: 16 | |
addition_attention: true | |
image_cross_attention: true | |
default_fs: 10 | |
fs_condition: true | |
first_stage_config: | |
target: lvdm.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: lvdm.modules.encoders.condition.FrozenOpenCLIPEmbedder | |
params: | |
freeze: true | |
layer: "penultimate" | |
img_cond_stage_config: | |
target: lvdm.modules.encoders.condition.FrozenOpenCLIPImageEmbedderV2 | |
params: | |
freeze: true | |
image_proj_stage_config: | |
target: lvdm.modules.encoders.resampler.Resampler | |
params: | |
dim: 1024 | |
depth: 4 | |
dim_head: 64 | |
heads: 12 | |
num_queries: 16 | |
embedding_dim: 1280 | |
output_dim: 1024 | |
ff_mult: 4 | |
video_length: 16 | |
data: | |
target: utils_data.DataModuleFromConfig | |
params: | |
batch_size: 2 | |
num_workers: 12 | |
wrap: false | |
train: | |
target: lvdm.data.webvid.WebVid | |
params: | |
data_dir: <WebVid10M DATA> | |
meta_path: <.csv FILE> | |
video_length: 16 | |
frame_stride: 6 | |
load_raw_resolution: true | |
resolution: [320, 512] | |
spatial_transform: resize_center_crop | |
random_fs: true ## if true, we uniformly sample fs with max_fs=frame_stride (above) | |
lightning: | |
precision: 16 | |
# strategy: deepspeed_stage_2 | |
trainer: | |
benchmark: True | |
accumulate_grad_batches: 2 | |
max_steps: 100000 | |
# logger | |
log_every_n_steps: 50 | |
# val | |
val_check_interval: 0.5 | |
gradient_clip_algorithm: 'norm' | |
gradient_clip_val: 0.5 | |
callbacks: | |
model_checkpoint: | |
target: pytorch_lightning.callbacks.ModelCheckpoint | |
params: | |
every_n_train_steps: 9000 #1000 | |
filename: "{epoch}-{step}" | |
save_weights_only: True | |
metrics_over_trainsteps_checkpoint: | |
target: pytorch_lightning.callbacks.ModelCheckpoint | |
params: | |
filename: '{epoch}-{step}' | |
save_weights_only: True | |
every_n_train_steps: 10000 #20000 # 3s/step*2w= | |
batch_logger: | |
target: callbacks.ImageLogger | |
params: | |
batch_frequency: 500 | |
to_local: False | |
max_images: 8 | |
log_images_kwargs: | |
ddim_steps: 50 | |
unconditional_guidance_scale: 7.5 | |
timestep_spacing: uniform_trailing | |
guidance_rescale: 0.7 |