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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>
37 lines
834 B
Python
37 lines
834 B
Python
use_t2i2v = True
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# flux configurations
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img_flux = dict(
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type="flux",
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from_pretrained="./ckpts/flux1-dev.safetensors",
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guidance_embed=True,
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# model architecture
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in_channels=64,
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vec_in_dim=768,
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context_in_dim=4096,
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hidden_size=3072,
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mlp_ratio=4.0,
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num_heads=24,
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depth=19,
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depth_single_blocks=38,
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axes_dim=[16, 56, 56],
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theta=10_000,
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qkv_bias=True,
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cond_embed=False, # pass i2v & v2v info, for t2v need this layer too but with x_cond and mask all set to 0
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)
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img_flux_ae = dict(
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type="autoencoder_2d",
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from_pretrained="./ckpts/flux1-dev-ae.safetensors",
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resolution=256,
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in_channels=3,
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ch=128,
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out_ch=3,
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ch_mult=[1, 2, 4, 4],
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num_res_blocks=2,
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z_channels=16,
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scale_factor=0.3611,
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shift_factor=0.1159,
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)
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img_resolution = "768px"
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