8029 update load old weights function for diffusion_model_unet.py (#8031)

Fixes #8029  .

### Description

A few sentences describing the changes proposed in this pull request.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: Yiheng Wang <[email protected]>
Signed-off-by: Yiheng Wang <[email protected]>
Co-authored-by: YunLiu <[email protected]>

Author: yiheng-wang-nv

monai/networks/nets/diffusion_model_unet.py

@@ -1837,9 +1837,26 @@ def load_old_state_dict(self, old_state_dict: dict, verbose=False) -> None:
                 new_state_dict[k] = old_state_dict.pop(k)
 
         # fix the attention blocks
-        attention_blocks = [k.replace(".out_proj.weight", "") for k in new_state_dict if "out_proj.weight" in k]
+        attention_blocks = [k.replace(".attn.to_k.weight", "") for k in new_state_dict if "attn.to_k.weight" in k]
         for block in attention_blocks:
+            new_state_dict[f"{block}.attn.to_q.weight"] = old_state_dict.pop(f"{block}.to_q.weight")
+            new_state_dict[f"{block}.attn.to_k.weight"] = old_state_dict.pop(f"{block}.to_k.weight")
+            new_state_dict[f"{block}.attn.to_v.weight"] = old_state_dict.pop(f"{block}.to_v.weight")
+            new_state_dict[f"{block}.attn.to_q.bias"] = old_state_dict.pop(f"{block}.to_q.bias")
+            new_state_dict[f"{block}.attn.to_k.bias"] = old_state_dict.pop(f"{block}.to_k.bias")
+            new_state_dict[f"{block}.attn.to_v.bias"] = old_state_dict.pop(f"{block}.to_v.bias")
+
             # projection
+            new_state_dict[f"{block}.attn.out_proj.weight"] = old_state_dict.pop(f"{block}.proj_attn.weight")
+            new_state_dict[f"{block}.attn.out_proj.bias"] = old_state_dict.pop(f"{block}.proj_attn.bias")
+
+        # fix the cross attention blocks
+        cross_attention_blocks = [
+            k.replace(".out_proj.weight", "")
+            for k in new_state_dict
+            if "out_proj.weight" in k and "transformer_blocks" in k
+        ]
+        for block in cross_attention_blocks:
             new_state_dict[f"{block}.out_proj.weight"] = old_state_dict.pop(f"{block}.to_out.0.weight")
             new_state_dict[f"{block}.out_proj.bias"] = old_state_dict.pop(f"{block}.to_out.0.bias")