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* 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>
36 lines
704 B
Python
36 lines
704 B
Python
_base_ = ["t2i2v_768px.py"]
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# no need for parallelism
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plugin = None
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plugin_config = None
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plugin_ae = None
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plugin_config_ae = None
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# model settings
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patch_size = 1
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model = dict(
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from_pretrained="./ckpts/Open_Sora_v2_Video_DC_AE.safetensors",
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in_channels=128,
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cond_embed=True,
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patch_size=1,
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)
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# AE settings
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ae = dict(
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_delete_=True,
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type="dc_ae",
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from_scratch=True,
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model_name="dc-ae-f32t4c128",
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from_pretrained="./ckpts/F32T4C128_AE.safetensors",
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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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ae_spatial_compression = 32
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sampling_option = dict(
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num_frames=128,
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)
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