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febf3ad4b2
* upload v2.0 * update docs * [hotfix] fit latest fa3 (#802) * update readme * update readme * update readme * update train readme * update readme * update readme: motion score * cleaning video dc ae WIP * update config * add dependency functions * undo cleaning * use latest dcae * complete high compression training * update hcae config * cleaned up vae * update ae.md * further cleanup * update vae & ae paths * align naming of ae * [hotfix] fix ring attn bwd for fa3 (#803) * train ae default without wandb * update config * update evaluation results * added hcae report * update readme * update readme demo * update readme demo * update readme gif * display demo directly in readme * update paper * delete files --------- Co-authored-by: Hongxin Liu <lhx0217@gmail.com> Co-authored-by: Shen-Chenhui <shen_chenhui@u.nus.edu> Co-authored-by: wuxiwen <wuxiwen.simon@gmail.com>
33 lines
632 B
Python
33 lines
632 B
Python
dtype = "bf16"
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batch_size = 1
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seed = 42
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dataset = dict(
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type="video_text",
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transform_name="resize_crop",
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fps_max=16,
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data_path="datasets/pexels_45k_necessary.csv",
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)
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bucket_config = {
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"512px_ar1:1": {96: (1.0, 1)},
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}
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model = dict(
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type="dc_ae",
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model_name="dc-ae-f32t4c128",
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from_pretrained="./ckpts/F32T4C128_AE.safetensors",
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from_scratch=True,
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use_spatial_tiling=True,
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use_temporal_tiling=True,
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spatial_tile_size=256,
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temporal_tile_size=32,
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tile_overlap_factor=0.25,
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)
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save_dir = "samples/video_dc_ae"
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num_workers = 24
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num_bucket_build_workers = 16
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prefetch_factor = 4
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