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feat: Support Krea2 (#14589)
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@@ -818,6 +818,44 @@ def z_image_to_diffusers(mmdit_config, output_prefix=""):
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return key_map
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def krea2_to_diffusers(mmdit_config, output_prefix=""):
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n_layers = mmdit_config.get("layers", 0)
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n_txt_layerwise = 2 # TextFusionTransformer hardcodes 2 layerwise + 2 refiner blocks
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n_txt_refiner = 2
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key_map = {}
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def add_block(prefix_to, prefix_from):
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block_map = {
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"attn.to_q": "attn.wq", "attn.to_k": "attn.wk", "attn.to_v": "attn.wv",
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"attn.to_gate": "attn.gate", "attn.to_out.0": "attn.wo",
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"attn.to_out": "attn.wo", # some tools drop the ".0" on to_out
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"ff.gate": "mlp.gate", "ff.up": "mlp.up", "ff.down": "mlp.down",
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}
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for d, c in block_map.items():
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key_map["{}.{}.weight".format(prefix_to, d)] = "{}{}.{}.weight".format(output_prefix, prefix_from, c)
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for i in range(n_layers):
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add_block("transformer_blocks.{}".format(i), "blocks.{}".format(i))
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for i in range(n_txt_layerwise):
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add_block("text_fusion.layerwise_blocks.{}".format(i), "txtfusion.layerwise_blocks.{}".format(i))
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for i in range(n_txt_refiner):
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add_block("text_fusion.refiner_blocks.{}".format(i), "txtfusion.refiner_blocks.{}".format(i))
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MAP_BASIC = [
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("img_in", "first"),
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("time_embed.linear_1", "tmlp.0"),
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("time_embed.linear_2", "tmlp.2"),
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("time_mod_proj", "tproj.1"),
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("txt_in.linear_1", "txtmlp.1"),
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("txt_in.linear_2", "txtmlp.3"),
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("text_fusion.projector", "txtfusion.projector"),
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("final_layer.linear", "last.linear"),
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]
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for d, c in MAP_BASIC:
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key_map["{}.weight".format(d)] = "{}{}.weight".format(output_prefix, c)
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return key_map
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def repeat_to_batch_size(tensor, batch_size, dim=0):
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if tensor.shape[dim] > batch_size:
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return tensor.narrow(dim, 0, batch_size)
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