feat: add paddings if LoRA ranks for `q, k, v` are different (#603)

* Add paddings if LoRA ranks for q, k, v are different

* No need to create a list

nunchaku/lora/flux/compose.py

@@ -29,6 +29,7 @@ import argparse
 import os
 
 import torch
+import torch.nn.functional as F
 from safetensors.torch import save_file
 
 from .diffusers_converter import to_diffusers
@@ -120,8 +121,14 @@ def compose_lora(
                         .replace(".add_q_proj.", ".add_v_proj.")
                     ]
 
-                    assert q_a.shape[0] == k_a.shape[0] == v_a.shape[0]
-                    assert q_b.shape[1] == k_b.shape[1] == v_b.shape[1]
+                    # Add paddings if their ranks are different
+                    max_rank = max(q_a.shape[0], k_a.shape[0], v_a.shape[0])
+                    q_a = F.pad(q_a, (0, 0, 0, max_rank - q_a.shape[0]))
+                    k_a = F.pad(k_a, (0, 0, 0, max_rank - k_a.shape[0]))
+                    v_a = F.pad(v_a, (0, 0, 0, max_rank - v_a.shape[0]))
+                    q_b = F.pad(q_b, (0, max_rank - q_b.shape[1]))
+                    k_b = F.pad(k_b, (0, max_rank - k_b.shape[1]))
+                    v_b = F.pad(v_b, (0, max_rank - v_b.shape[1]))
 
                     if torch.isclose(q_a, k_a).all() and torch.isclose(q_a, v_a).all():
                         lora_a = q_a