klein lora: ERROR lora diffusion_model.double_blocks.4.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184

use convert_script:
from safetensors import safe_open
from safetensors.torch import save_file

def convert_flux2_lora_keys(input_file, output_file):
new_data = {}
metadata = {}

with safe_open(input_file, framework="pt") as f:
    if hasattr(f, 'metadata'):
        metadata = f.metadata() or {}
    
    print(f"Converting {len(f.keys())} keys...\n")
    print("=" * 80)
    
    for key in f.keys():
        original_key = key
        new_key = key.replace('.default', '')  # Remove .default suffix
        
        # === SINGLE BLOCKS MAPPING ===
        if new_key.startswith('single_transformer_blocks.'):
            # Replace block name
            new_key = new_key.replace('single_transformer_blocks.', 'single_blocks.')
            
            # Map layer names:
            # to_qkv_mlp_proj -> linear1
            # to_out -> linear2
            new_key = new_key.replace('.attn.to_qkv_mlp_proj.', '.linear1.')
            new_key = new_key.replace('.attn.to_out.', '.linear2.')
        
        # === DOUBLE BLOCKS MAPPING ===
        elif new_key.startswith('transformer_blocks.'):
            new_key = new_key.replace('transformer_blocks.', 'double_blocks.')
            
            # Image attention mappings - keep Q, K, V separate
            if '.attn.to_q.' in new_key:
                new_key = new_key.replace('.attn.to_q.', '.img_attn.qkv.')
            elif '.attn.to_k.' in new_key:
                new_key = new_key.replace('.attn.to_k.', '.img_attn.qkv.')
            elif '.attn.to_v.' in new_key:
                new_key = new_key.replace('.attn.to_v.', '.img_attn.qkv.')
            elif '.attn.to_out.0.' in new_key:
                new_key = new_key.replace('.attn.to_out.0.', '.img_attn.proj.')
            
            # Text attention mappings - keep Q, K, V separate
            elif '.attn.add_q_proj.' in new_key:
                new_key = new_key.replace('.attn.add_q_proj.', '.txt_attn.qkv.')
            elif '.attn.add_k_proj.' in new_key:
                new_key = new_key.replace('.attn.add_k_proj.', '.txt_attn.qkv.')
            elif '.attn.add_v_proj.' in new_key:
                new_key = new_key.replace('.attn.add_v_proj.', '.txt_attn.qkv.')
            elif '.attn.to_add_out.' in new_key:
                new_key = new_key.replace('.attn.to_add_out.', '.txt_attn.proj.')
            
            # Feed-forward mappings
            # ff -> img_mlp
            # ff_context -> txt_mlp
            elif '.ff.linear_in.' in new_key:
                new_key = new_key.replace('.ff.linear_in.', '.img_mlp.0.')
            elif '.ff.linear_out.' in new_key:
                new_key = new_key.replace('.ff.linear_out.', '.img_mlp.2.')
            elif '.ff_context.linear_in.' in new_key:
                new_key = new_key.replace('.ff_context.linear_in.', '.txt_mlp.0.')
            elif '.ff_context.linear_out.' in new_key:
                new_key = new_key.replace('.ff_context.linear_out.', '.txt_mlp.2.')
        
        # Add diffusion_model prefix
        new_key = f"diffusion_model.{new_key}"
        
        print(f"{original_key}")
        print(f"  -> {new_key}")
        
        new_data[new_key] = f.get_tensor(original_key)

print("\n" + "=" * 80)
print(f"Successfully converted {len(new_data)} keys")
save_file(new_data, output_file, metadata=metadata)
print(f"✓ Saved to: {output_file}")
print(f"\nPlace this file in: ComfyUI/models/loras/")

if name == "main":
import sys

if len(sys.argv) > 1:
    input_file = sys.argv[1]
    output_file = sys.argv[2] if len(sys.argv) > 2 else input_file.replace('.safetensors', '_comfy.safetensors')
else:
    input_file = "old_lora.safetensors"
    output_file = "new_lora.safetensors"

convert_flux2_lora_keys(input_file, output_file)

found:

ERROR lora diffusion_model.double_blocks.4.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.4.img_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.3.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.3.img_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.2.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.2.img_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.1.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.1.img_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.0.txt_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184
ERROR lora diffusion_model.double_blocks.0.img_attn.qkv.weight shape '[9216, 3072]' is invalid for input of size 9437184

Start with the inline Python entry point convert_flux2_lora_keys and reproduce the reported conversion and loading errors using the shown script. Inspect the generated double_blocks.*.txt_attn.qkv and img_attn.qkv tensors against the reported shapes. Done means the converted LoRA loads without the invalid-shape errors.