How to use it in SimpleCrossAttnUpBlock2D?

[americanexplorer13]

I've tried to change your code in order to maintain SimpleCrossAttnUpBlock2D however it seems that shapes doesn't fit up. How can I do it? Thanks!

  File "/usr/local/lib/python3.9/dist-packages/gradio/routes.py", line 523, in run_predict
    output = await app.get_blocks().process_api(
  File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 1437, in process_api
    result = await self.call_function(
  File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 1109, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "/usr/local/lib/python3.9/dist-packages/anyio/to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "/usr/local/lib/python3.9/dist-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "/usr/local/lib/python3.9/dist-packages/anyio/_backends/_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "/usr/local/lib/python3.9/dist-packages/gradio/utils.py", line 865, in wrapper
    response = f(*args, **kwargs)
  File "/home/ubuntu/mimesis-ml-gan-backend/app.py", line 128, in generate
    image = pipe(image=input_image,
  File "/usr/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/ubuntu/mimesis-ml-gan-backend/src/diffusions/kandinsky/pipeline_kandinsky_img2img_scheduler.py", line 125, in __call__
    noise_pred = self.unet(
  File "/usr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/lib/python3.9/site-packages/diffusers/models/unet_2d_condition.py", line 1020, in forward
    sample = upsample_block(
  File "/usr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ubuntu/mimesis-ml-gan-backend/free_lunch_utils.py", line 166, in forward
    hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
RuntimeError: Tensors must have same number of dimensions: got 3 and 4 ```