This is a great work! But the web demo has a problem shown as follows:

[QvQKing]

Traceback (most recent call last):
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/routes.py", line 437, in run_predict
output = await app.get_blocks().process_api(
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/blocks.py", line 1352, in process_api
result = await self.call_function(
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/blocks.py", line 1093, in call_function
prediction = await utils.async_iteration(iterator)
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/utils.py", line 341, in async_iteration
return await iterator.anext()
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/utils.py", line 334, in anext
return await anyio.to_thread.run_sync(
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/anyio/to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 2134, in run_sync_in_worker_thread
return await future
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 851, in run
result = context.run(func, *args)
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/gradio/utils.py", line 317, in run_sync_iterator_async
return next(iterator)
File "/hy-tmp/LLMGA-master/llmga/serve/gradio_web_server.py", line 198, in generation_bot
image = pipe(caption,num_inference_steps=num_inference_steps).images[0]
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/hy-tmp/LLMGA-master/llmga/diffusers/pipeline_stable_diffusion_xl_lpw.py", line 903, in call
latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs, return_dict=False)[0]
File "/usr/local/miniconda3/envs/llmga/lib/python3.9/site-packages/diffusers/schedulers/scheduling_euler_discrete.py", line 498, in step
pred_original_sample = sample - sigma_hat * model_output
RuntimeError: The size of tensor a (9) must match the size of tensor b (4) at non-singleton dimension 1