| import torch | |
| from safetensors.torch import save_file, load_file | |
| from collections import OrderedDict | |
| meta = OrderedDict() | |
| meta["format"] ="pt" | |
| attn_dict = load_file("/mnt/Train/out/ip_adapter/sd15_bigG/sd15_bigG_000266000.safetensors") | |
| state_dict = load_file("/home/jaret/Dev/models/hf/OstrisDiffusionV1/unet/diffusion_pytorch_model.safetensors") | |
| attn_list = [] | |
| for key, value in state_dict.items(): | |
| if "attn1" in key: | |
| attn_list.append(key) | |
| attn_names = ['down_blocks.0.attentions.0.transformer_blocks.0.attn2.processor', 'down_blocks.0.attentions.1.transformer_blocks.0.attn2.processor', 'down_blocks.1.attentions.0.transformer_blocks.0.attn2.processor', 'down_blocks.1.attentions.1.transformer_blocks.0.attn2.processor', 'down_blocks.2.attentions.0.transformer_blocks.0.attn2.processor', 'down_blocks.2.attentions.1.transformer_blocks.0.attn2.processor', 'up_blocks.1.attentions.0.transformer_blocks.0.attn2.processor', 'up_blocks.1.attentions.1.transformer_blocks.0.attn2.processor', 'up_blocks.1.attentions.2.transformer_blocks.0.attn2.processor', 'up_blocks.2.attentions.0.transformer_blocks.0.attn2.processor', 'up_blocks.2.attentions.1.transformer_blocks.0.attn2.processor', 'up_blocks.2.attentions.2.transformer_blocks.0.attn2.processor', 'up_blocks.3.attentions.0.transformer_blocks.0.attn2.processor', 'up_blocks.3.attentions.1.transformer_blocks.0.attn2.processor', 'up_blocks.3.attentions.2.transformer_blocks.0.attn2.processor', 'mid_block.attentions.0.transformer_blocks.0.attn2.processor'] | |
| adapter_names = [] | |
| for i in range(100): | |
| if f'te_adapter.adapter_modules.{i}.to_k_adapter.weight' in attn_dict: | |
| adapter_names.append(f"te_adapter.adapter_modules.{i}.adapter") | |
| for i in range(len(adapter_names)): | |
| adapter_name = adapter_names[i] | |
| attn_name = attn_names[i] | |
| adapter_k_name = adapter_name[:-8] + '.to_k_adapter.weight' | |
| adapter_v_name = adapter_name[:-8] + '.to_v_adapter.weight' | |
| state_k_name = attn_name.replace(".processor", ".to_k.weight") | |
| state_v_name = attn_name.replace(".processor", ".to_v.weight") | |
| if adapter_k_name in attn_dict: | |
| state_dict[state_k_name] = attn_dict[adapter_k_name] | |
| state_dict[state_v_name] = attn_dict[adapter_v_name] | |
| else: | |
| print("adapter_k_name", adapter_k_name) | |
| print("state_k_name", state_k_name) | |
| for key, value in state_dict.items(): | |
| state_dict[key] = value.cpu().to(torch.float16) | |
| save_file(state_dict, "/home/jaret/Dev/models/hf/OstrisDiffusionV1/unet/diffusion_pytorch_model.safetensors", metadata=meta) | |
| print("Done") | |