from .sd3_vae_encoder import SD3VAEEncoder, SDVAEEncoderStateDictConverter from .sd3_vae_decoder import SD3VAEDecoder, SDVAEDecoderStateDictConverter class FluxVAEEncoder(SD3VAEEncoder): def __init__(self): super().__init__() self.scaling_factor = 0.3611 self.shift_factor = 0.1159 @staticmethod def state_dict_converter(): return FluxVAEEncoderStateDictConverter() class FluxVAEDecoder(SD3VAEDecoder): def __init__(self): super().__init__() self.scaling_factor = 0.3611 self.shift_factor = 0.1159 @staticmethod def state_dict_converter(): return FluxVAEDecoderStateDictConverter() class FluxVAEEncoderStateDictConverter(SDVAEEncoderStateDictConverter): def __init__(self): pass def from_civitai(self, state_dict): rename_dict = { "encoder.conv_in.bias": "conv_in.bias", "encoder.conv_in.weight": "conv_in.weight", "encoder.conv_out.bias": "conv_out.bias", "encoder.conv_out.weight": "conv_out.weight", "encoder.down.0.block.0.conv1.bias": "blocks.0.conv1.bias", "encoder.down.0.block.0.conv1.weight": "blocks.0.conv1.weight", "encoder.down.0.block.0.conv2.bias": "blocks.0.conv2.bias", "encoder.down.0.block.0.conv2.weight": "blocks.0.conv2.weight", "encoder.down.0.block.0.norm1.bias": "blocks.0.norm1.bias", "encoder.down.0.block.0.norm1.weight": "blocks.0.norm1.weight", "encoder.down.0.block.0.norm2.bias": "blocks.0.norm2.bias", "encoder.down.0.block.0.norm2.weight": "blocks.0.norm2.weight", "encoder.down.0.block.1.conv1.bias": "blocks.1.conv1.bias", "encoder.down.0.block.1.conv1.weight": "blocks.1.conv1.weight", "encoder.down.0.block.1.conv2.bias": "blocks.1.conv2.bias", "encoder.down.0.block.1.conv2.weight": "blocks.1.conv2.weight", "encoder.down.0.block.1.norm1.bias": "blocks.1.norm1.bias", "encoder.down.0.block.1.norm1.weight": "blocks.1.norm1.weight", "encoder.down.0.block.1.norm2.bias": "blocks.1.norm2.bias", "encoder.down.0.block.1.norm2.weight": "blocks.1.norm2.weight", "encoder.down.0.downsample.conv.bias": "blocks.2.conv.bias", "encoder.down.0.downsample.conv.weight": "blocks.2.conv.weight", "encoder.down.1.block.0.conv1.bias": "blocks.3.conv1.bias", "encoder.down.1.block.0.conv1.weight": "blocks.3.conv1.weight", "encoder.down.1.block.0.conv2.bias": "blocks.3.conv2.bias", "encoder.down.1.block.0.conv2.weight": "blocks.3.conv2.weight", "encoder.down.1.block.0.nin_shortcut.bias": "blocks.3.conv_shortcut.bias", "encoder.down.1.block.0.nin_shortcut.weight": "blocks.3.conv_shortcut.weight", "encoder.down.1.block.0.norm1.bias": "blocks.3.norm1.bias", "encoder.down.1.block.0.norm1.weight": "blocks.3.norm1.weight", "encoder.down.1.block.0.norm2.bias": "blocks.3.norm2.bias", "encoder.down.1.block.0.norm2.weight": "blocks.3.norm2.weight", "encoder.down.1.block.1.conv1.bias": "blocks.4.conv1.bias", "encoder.down.1.block.1.conv1.weight": "blocks.4.conv1.weight", "encoder.down.1.block.1.conv2.bias": "blocks.4.conv2.bias", "encoder.down.1.block.1.conv2.weight": "blocks.4.conv2.weight", "encoder.down.1.block.1.norm1.bias": "blocks.4.norm1.bias", "encoder.down.1.block.1.norm1.weight": "blocks.4.norm1.weight", "encoder.down.1.block.1.norm2.bias": "blocks.4.norm2.bias", "encoder.down.1.block.1.norm2.weight": "blocks.4.norm2.weight", "encoder.down.1.downsample.conv.bias": "blocks.5.conv.bias", "encoder.down.1.downsample.conv.weight": "blocks.5.conv.weight", "encoder.down.2.block.0.conv1.bias": "blocks.6.conv1.bias", "encoder.down.2.block.0.conv1.weight": "blocks.6.conv1.weight", "encoder.down.2.block.0.conv2.bias": "blocks.6.conv2.bias", "encoder.down.2.block.0.conv2.weight": "blocks.6.conv2.weight", "encoder.down.2.block.0.nin_shortcut.bias": "blocks.6.conv_shortcut.bias", "encoder.down.2.block.0.nin_shortcut.weight": "blocks.6.conv_shortcut.weight", "encoder.down.2.block.0.norm1.bias": "blocks.6.norm1.bias", "encoder.down.2.block.0.norm1.weight": "blocks.6.norm1.weight", "encoder.down.2.block.0.norm2.bias": "blocks.6.norm2.bias", "encoder.down.2.block.0.norm2.weight": "blocks.6.norm2.weight", "encoder.down.2.block.1.conv1.bias": "blocks.7.conv1.bias", "encoder.down.2.block.1.conv1.weight": "blocks.7.conv1.weight", "encoder.down.2.block.1.conv2.bias": "blocks.7.conv2.bias", "encoder.down.2.block.1.conv2.weight": "blocks.7.conv2.weight", "encoder.down.2.block.1.norm1.bias": "blocks.7.norm1.bias", "encoder.down.2.block.1.norm1.weight": "blocks.7.norm1.weight", "encoder.down.2.block.1.norm2.bias": "blocks.7.norm2.bias", "encoder.down.2.block.1.norm2.weight": "blocks.7.norm2.weight", "encoder.down.2.downsample.conv.bias": "blocks.8.conv.bias", "encoder.down.2.downsample.conv.weight": "blocks.8.conv.weight", "encoder.down.3.block.0.conv1.bias": "blocks.9.conv1.bias", "encoder.down.3.block.0.conv1.weight": "blocks.9.conv1.weight", "encoder.down.3.block.0.conv2.bias": "blocks.9.conv2.bias", "encoder.down.3.block.0.conv2.weight": "blocks.9.conv2.weight", "encoder.down.3.block.0.norm1.bias": "blocks.9.norm1.bias", "encoder.down.3.block.0.norm1.weight": "blocks.9.norm1.weight", "encoder.down.3.block.0.norm2.bias": "blocks.9.norm2.bias", "encoder.down.3.block.0.norm2.weight": "blocks.9.norm2.weight", "encoder.down.3.block.1.conv1.bias": "blocks.10.conv1.bias", "encoder.down.3.block.1.conv1.weight": "blocks.10.conv1.weight", "encoder.down.3.block.1.conv2.bias": "blocks.10.conv2.bias", "encoder.down.3.block.1.conv2.weight": "blocks.10.conv2.weight", "encoder.down.3.block.1.norm1.bias": "blocks.10.norm1.bias", "encoder.down.3.block.1.norm1.weight": "blocks.10.norm1.weight", "encoder.down.3.block.1.norm2.bias": "blocks.10.norm2.bias", "encoder.down.3.block.1.norm2.weight": "blocks.10.norm2.weight", "encoder.mid.attn_1.k.bias": "blocks.12.transformer_blocks.0.to_k.bias", "encoder.mid.attn_1.k.weight": "blocks.12.transformer_blocks.0.to_k.weight", "encoder.mid.attn_1.norm.bias": "blocks.12.norm.bias", "encoder.mid.attn_1.norm.weight": "blocks.12.norm.weight", "encoder.mid.attn_1.proj_out.bias": "blocks.12.transformer_blocks.0.to_out.bias", "encoder.mid.attn_1.proj_out.weight": "blocks.12.transformer_blocks.0.to_out.weight", "encoder.mid.attn_1.q.bias": "blocks.12.transformer_blocks.0.to_q.bias", "encoder.mid.attn_1.q.weight": "blocks.12.transformer_blocks.0.to_q.weight", "encoder.mid.attn_1.v.bias": "blocks.12.transformer_blocks.0.to_v.bias", "encoder.mid.attn_1.v.weight": "blocks.12.transformer_blocks.0.to_v.weight", "encoder.mid.block_1.conv1.bias": "blocks.11.conv1.bias", "encoder.mid.block_1.conv1.weight": "blocks.11.conv1.weight", "encoder.mid.block_1.conv2.bias": "blocks.11.conv2.bias", "encoder.mid.block_1.conv2.weight": "blocks.11.conv2.weight", "encoder.mid.block_1.norm1.bias": "blocks.11.norm1.bias", "encoder.mid.block_1.norm1.weight": "blocks.11.norm1.weight", "encoder.mid.block_1.norm2.bias": "blocks.11.norm2.bias", "encoder.mid.block_1.norm2.weight": "blocks.11.norm2.weight", "encoder.mid.block_2.conv1.bias": "blocks.13.conv1.bias", "encoder.mid.block_2.conv1.weight": "blocks.13.conv1.weight", "encoder.mid.block_2.conv2.bias": "blocks.13.conv2.bias", "encoder.mid.block_2.conv2.weight": "blocks.13.conv2.weight", "encoder.mid.block_2.norm1.bias": "blocks.13.norm1.bias", "encoder.mid.block_2.norm1.weight": "blocks.13.norm1.weight", "encoder.mid.block_2.norm2.bias": "blocks.13.norm2.bias", "encoder.mid.block_2.norm2.weight": "blocks.13.norm2.weight", "encoder.norm_out.bias": "conv_norm_out.bias", "encoder.norm_out.weight": "conv_norm_out.weight", } state_dict_ = {} for name in state_dict: if name in rename_dict: param = state_dict[name] if "transformer_blocks" in rename_dict[name]: param = param.squeeze() state_dict_[rename_dict[name]] = param return state_dict_ class FluxVAEDecoderStateDictConverter(SDVAEDecoderStateDictConverter): def __init__(self): pass def from_civitai(self, state_dict): rename_dict = { "decoder.conv_in.bias": "conv_in.bias", "decoder.conv_in.weight": "conv_in.weight", "decoder.conv_out.bias": "conv_out.bias", "decoder.conv_out.weight": "conv_out.weight", "decoder.mid.attn_1.k.bias": "blocks.1.transformer_blocks.0.to_k.bias", "decoder.mid.attn_1.k.weight": "blocks.1.transformer_blocks.0.to_k.weight", "decoder.mid.attn_1.norm.bias": "blocks.1.norm.bias", "decoder.mid.attn_1.norm.weight": "blocks.1.norm.weight", "decoder.mid.attn_1.proj_out.bias": "blocks.1.transformer_blocks.0.to_out.bias", "decoder.mid.attn_1.proj_out.weight": "blocks.1.transformer_blocks.0.to_out.weight", "decoder.mid.attn_1.q.bias": "blocks.1.transformer_blocks.0.to_q.bias", "decoder.mid.attn_1.q.weight": "blocks.1.transformer_blocks.0.to_q.weight", "decoder.mid.attn_1.v.bias": "blocks.1.transformer_blocks.0.to_v.bias", "decoder.mid.attn_1.v.weight": "blocks.1.transformer_blocks.0.to_v.weight", "decoder.mid.block_1.conv1.bias": "blocks.0.conv1.bias", "decoder.mid.block_1.conv1.weight": "blocks.0.conv1.weight", "decoder.mid.block_1.conv2.bias": "blocks.0.conv2.bias", "decoder.mid.block_1.conv2.weight": "blocks.0.conv2.weight", "decoder.mid.block_1.norm1.bias": "blocks.0.norm1.bias", "decoder.mid.block_1.norm1.weight": "blocks.0.norm1.weight", "decoder.mid.block_1.norm2.bias": "blocks.0.norm2.bias", "decoder.mid.block_1.norm2.weight": "blocks.0.norm2.weight", "decoder.mid.block_2.conv1.bias": "blocks.2.conv1.bias", "decoder.mid.block_2.conv1.weight": "blocks.2.conv1.weight", "decoder.mid.block_2.conv2.bias": "blocks.2.conv2.bias", "decoder.mid.block_2.conv2.weight": "blocks.2.conv2.weight", "decoder.mid.block_2.norm1.bias": "blocks.2.norm1.bias", "decoder.mid.block_2.norm1.weight": "blocks.2.norm1.weight", "decoder.mid.block_2.norm2.bias": "blocks.2.norm2.bias", "decoder.mid.block_2.norm2.weight": "blocks.2.norm2.weight", "decoder.norm_out.bias": "conv_norm_out.bias", "decoder.norm_out.weight": "conv_norm_out.weight", "decoder.up.0.block.0.conv1.bias": "blocks.15.conv1.bias", "decoder.up.0.block.0.conv1.weight": "blocks.15.conv1.weight", "decoder.up.0.block.0.conv2.bias": "blocks.15.conv2.bias", "decoder.up.0.block.0.conv2.weight": "blocks.15.conv2.weight", "decoder.up.0.block.0.nin_shortcut.bias": "blocks.15.conv_shortcut.bias", "decoder.up.0.block.0.nin_shortcut.weight": "blocks.15.conv_shortcut.weight", "decoder.up.0.block.0.norm1.bias": "blocks.15.norm1.bias", "decoder.up.0.block.0.norm1.weight": "blocks.15.norm1.weight", "decoder.up.0.block.0.norm2.bias": "blocks.15.norm2.bias", "decoder.up.0.block.0.norm2.weight": "blocks.15.norm2.weight", "decoder.up.0.block.1.conv1.bias": "blocks.16.conv1.bias", "decoder.up.0.block.1.conv1.weight": "blocks.16.conv1.weight", "decoder.up.0.block.1.conv2.bias": "blocks.16.conv2.bias", "decoder.up.0.block.1.conv2.weight": "blocks.16.conv2.weight", "decoder.up.0.block.1.norm1.bias": "blocks.16.norm1.bias", "decoder.up.0.block.1.norm1.weight": "blocks.16.norm1.weight", "decoder.up.0.block.1.norm2.bias": "blocks.16.norm2.bias", "decoder.up.0.block.1.norm2.weight": "blocks.16.norm2.weight", "decoder.up.0.block.2.conv1.bias": "blocks.17.conv1.bias", "decoder.up.0.block.2.conv1.weight": "blocks.17.conv1.weight", "decoder.up.0.block.2.conv2.bias": "blocks.17.conv2.bias", "decoder.up.0.block.2.conv2.weight": "blocks.17.conv2.weight", "decoder.up.0.block.2.norm1.bias": "blocks.17.norm1.bias", "decoder.up.0.block.2.norm1.weight": "blocks.17.norm1.weight", "decoder.up.0.block.2.norm2.bias": "blocks.17.norm2.bias", "decoder.up.0.block.2.norm2.weight": "blocks.17.norm2.weight", "decoder.up.1.block.0.conv1.bias": "blocks.11.conv1.bias", "decoder.up.1.block.0.conv1.weight": "blocks.11.conv1.weight", "decoder.up.1.block.0.conv2.bias": "blocks.11.conv2.bias", "decoder.up.1.block.0.conv2.weight": "blocks.11.conv2.weight", "decoder.up.1.block.0.nin_shortcut.bias": "blocks.11.conv_shortcut.bias", "decoder.up.1.block.0.nin_shortcut.weight": "blocks.11.conv_shortcut.weight", "decoder.up.1.block.0.norm1.bias": "blocks.11.norm1.bias", "decoder.up.1.block.0.norm1.weight": "blocks.11.norm1.weight", "decoder.up.1.block.0.norm2.bias": "blocks.11.norm2.bias", "decoder.up.1.block.0.norm2.weight": "blocks.11.norm2.weight", "decoder.up.1.block.1.conv1.bias": "blocks.12.conv1.bias", "decoder.up.1.block.1.conv1.weight": "blocks.12.conv1.weight", "decoder.up.1.block.1.conv2.bias": "blocks.12.conv2.bias", "decoder.up.1.block.1.conv2.weight": "blocks.12.conv2.weight", "decoder.up.1.block.1.norm1.bias": "blocks.12.norm1.bias", "decoder.up.1.block.1.norm1.weight": "blocks.12.norm1.weight", "decoder.up.1.block.1.norm2.bias": "blocks.12.norm2.bias", "decoder.up.1.block.1.norm2.weight": "blocks.12.norm2.weight", "decoder.up.1.block.2.conv1.bias": "blocks.13.conv1.bias", "decoder.up.1.block.2.conv1.weight": "blocks.13.conv1.weight", "decoder.up.1.block.2.conv2.bias": "blocks.13.conv2.bias", "decoder.up.1.block.2.conv2.weight": "blocks.13.conv2.weight", "decoder.up.1.block.2.norm1.bias": "blocks.13.norm1.bias", "decoder.up.1.block.2.norm1.weight": "blocks.13.norm1.weight", "decoder.up.1.block.2.norm2.bias": "blocks.13.norm2.bias", "decoder.up.1.block.2.norm2.weight": "blocks.13.norm2.weight", "decoder.up.1.upsample.conv.bias": "blocks.14.conv.bias", "decoder.up.1.upsample.conv.weight": "blocks.14.conv.weight", "decoder.up.2.block.0.conv1.bias": "blocks.7.conv1.bias", "decoder.up.2.block.0.conv1.weight": "blocks.7.conv1.weight", "decoder.up.2.block.0.conv2.bias": "blocks.7.conv2.bias", "decoder.up.2.block.0.conv2.weight": "blocks.7.conv2.weight", "decoder.up.2.block.0.norm1.bias": "blocks.7.norm1.bias", "decoder.up.2.block.0.norm1.weight": "blocks.7.norm1.weight", "decoder.up.2.block.0.norm2.bias": "blocks.7.norm2.bias", "decoder.up.2.block.0.norm2.weight": "blocks.7.norm2.weight", "decoder.up.2.block.1.conv1.bias": "blocks.8.conv1.bias", "decoder.up.2.block.1.conv1.weight": "blocks.8.conv1.weight", "decoder.up.2.block.1.conv2.bias": "blocks.8.conv2.bias", "decoder.up.2.block.1.conv2.weight": "blocks.8.conv2.weight", "decoder.up.2.block.1.norm1.bias": "blocks.8.norm1.bias", "decoder.up.2.block.1.norm1.weight": "blocks.8.norm1.weight", "decoder.up.2.block.1.norm2.bias": "blocks.8.norm2.bias", "decoder.up.2.block.1.norm2.weight": "blocks.8.norm2.weight", "decoder.up.2.block.2.conv1.bias": "blocks.9.conv1.bias", "decoder.up.2.block.2.conv1.weight": "blocks.9.conv1.weight", "decoder.up.2.block.2.conv2.bias": "blocks.9.conv2.bias", "decoder.up.2.block.2.conv2.weight": "blocks.9.conv2.weight", "decoder.up.2.block.2.norm1.bias": "blocks.9.norm1.bias", "decoder.up.2.block.2.norm1.weight": "blocks.9.norm1.weight", "decoder.up.2.block.2.norm2.bias": "blocks.9.norm2.bias", "decoder.up.2.block.2.norm2.weight": "blocks.9.norm2.weight", "decoder.up.2.upsample.conv.bias": "blocks.10.conv.bias", "decoder.up.2.upsample.conv.weight": "blocks.10.conv.weight", "decoder.up.3.block.0.conv1.bias": "blocks.3.conv1.bias", "decoder.up.3.block.0.conv1.weight": "blocks.3.conv1.weight", "decoder.up.3.block.0.conv2.bias": "blocks.3.conv2.bias", "decoder.up.3.block.0.conv2.weight": "blocks.3.conv2.weight", "decoder.up.3.block.0.norm1.bias": "blocks.3.norm1.bias", "decoder.up.3.block.0.norm1.weight": "blocks.3.norm1.weight", "decoder.up.3.block.0.norm2.bias": "blocks.3.norm2.bias", "decoder.up.3.block.0.norm2.weight": "blocks.3.norm2.weight", "decoder.up.3.block.1.conv1.bias": "blocks.4.conv1.bias", "decoder.up.3.block.1.conv1.weight": "blocks.4.conv1.weight", "decoder.up.3.block.1.conv2.bias": "blocks.4.conv2.bias", "decoder.up.3.block.1.conv2.weight": "blocks.4.conv2.weight", "decoder.up.3.block.1.norm1.bias": "blocks.4.norm1.bias", "decoder.up.3.block.1.norm1.weight": "blocks.4.norm1.weight", "decoder.up.3.block.1.norm2.bias": "blocks.4.norm2.bias", "decoder.up.3.block.1.norm2.weight": "blocks.4.norm2.weight", "decoder.up.3.block.2.conv1.bias": "blocks.5.conv1.bias", "decoder.up.3.block.2.conv1.weight": "blocks.5.conv1.weight", "decoder.up.3.block.2.conv2.bias": "blocks.5.conv2.bias", "decoder.up.3.block.2.conv2.weight": "blocks.5.conv2.weight", "decoder.up.3.block.2.norm1.bias": "blocks.5.norm1.bias", "decoder.up.3.block.2.norm1.weight": "blocks.5.norm1.weight", "decoder.up.3.block.2.norm2.bias": "blocks.5.norm2.bias", "decoder.up.3.block.2.norm2.weight": "blocks.5.norm2.weight", "decoder.up.3.upsample.conv.bias": "blocks.6.conv.bias", "decoder.up.3.upsample.conv.weight": "blocks.6.conv.weight", } state_dict_ = {} for name in state_dict: if name in rename_dict: param = state_dict[name] if "transformer_blocks" in rename_dict[name]: param = param.squeeze() state_dict_[rename_dict[name]] = param return state_dict_