38 lines
1.6 KiB
Python
38 lines
1.6 KiB
Python
import torch
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#from ..modules.attention import GatedSelfAttentionDense
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from comfy.gligen import GatedSelfAttentionDense as GSAD
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class GatedSelfAttentionDense(GSAD):
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def forward(self, x, instance_options={}):
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objs = instance_options['objs']
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x = super().forward(x, objs)
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return x.to(torch.float16)
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def prepare_fusers(fusers_ckpt) -> list[torch.nn.Module]:
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fusers_list = []
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for key in fusers_ckpt['input_blocks']:
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fusers_ckpt['input_blocks'][key]['params']['query_dim'] = fusers_ckpt['input_blocks'][key]['params']['n_heads'] * \
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fusers_ckpt['input_blocks'][key]['params']['d_head']
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fuser = GatedSelfAttentionDense(
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**fusers_ckpt['input_blocks'][key]['params'])
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fuser.load_state_dict(fusers_ckpt['input_blocks'][key]['state'])
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fusers_list.append(fuser)
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fusers_ckpt['middle_block']['1']['params']['query_dim'] = fusers_ckpt['middle_block']['1']['params']['n_heads'] * \
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fusers_ckpt['middle_block']['1']['params']['d_head']
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fuser = GatedSelfAttentionDense(
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**fusers_ckpt['middle_block']['1']['params'])
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fuser.load_state_dict(fusers_ckpt['middle_block']['1']['state'])
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fusers_list.append(fuser)
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for key in fusers_ckpt['output_blocks']:
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fusers_ckpt['output_blocks'][key]['params']['query_dim'] = fusers_ckpt['output_blocks'][key]['params']['n_heads'] * \
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fusers_ckpt['output_blocks'][key]['params']['d_head']
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fuser = GatedSelfAttentionDense(
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**fusers_ckpt['output_blocks'][key]['params'])
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fuser.load_state_dict(fusers_ckpt['output_blocks'][key]['state'])
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fusers_list.append(fuser)
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return fusers_list
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