Delete lyco.toml
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lyco.toml
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enable_conv = true
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# An example for use different algo/settings in "full" preset
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unet_target_module = [
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"Transformer2DModel",
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"ResnetBlock2D",
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"Downsample2D",
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"Upsample2D",
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"HunYuanDiTBlock",
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"DoubleStreamBlock",
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"SingleStreamBlock",
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"SingleDiTBlock",
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"MMDoubleStreamBlock", #HunYuanVideo
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"MMSingleStreamBlock", #HunYuanVideo
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]
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unet_target_name = [
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"conv_in",
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"conv_out",
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"time_embedding.linear_1",
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"time_embedding.linear_2",
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]
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text_encoder_target_module = [
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"CLIPAttention",
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"CLIPSdpaAttention",
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"CLIPMLP",
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"MT5Block",
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"BertLayer",
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]
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text_encoder_target_name = [
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# "token_embedding", # not supported, Embedding module in CLIP
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]
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[module_algo_map]
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[module_algo_map.CrossAttention]
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algo = "lokr"
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dim = 10000
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alpha = 10000
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factor = 4
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[module_algo_map.FeedForward] # MLP Layer in UNet
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algo = "lokr"
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dim = 10000
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alpha = 10000
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factor = 2
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[module_algo_map.ResnetBlock2D] # ResBlock in UNet
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algo = "lokr"
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dim = 10000
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alpha = 10000
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use_tucker = true # Use tucker decomposition for convolution
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factor = 8
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[module_algo_map.CLIPAttention] # Attention Layer in TE
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algo = "lokr"
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dim = 10000
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alpha = 10000
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factor = 8
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[module_algo_map.CLIPMLP] # MLP Layer in TE
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algo = "lokr"
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dim = 10000
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alpha = 10000
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factor = 8
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