RuntimeError: mat1 and mat2 shapes cannot be multiplied (512x768 and 2048x8192)

[jeffreyrobeson]

Thanks for your error report and we appreciate it a lot.

Checklist 2024-05-24 16:51:43.726 | INFO | hydit.inference:predict:296 - Input (height, width) = (1024, 1024) 2024-05-24 16:51:43.726 | INFO | hydit.inference:predict:301 - Align to 16: (height, width) = (1024, 1024) 2024-05-24 16:51:43.728 | DEBUG | hydit.inference:predict:347 - prompt: 一只可爱的猫 enhanced prompt: None seed: 1 (height, width): (1024, 1024) negative_prompt: 错误的眼睛，糟糕的人脸，毁容，糟糕的艺术，变形，多余的肢体，模糊的颜色，模糊，重复，病态，残缺， batch_size: 1 guidance_scale: 6 infer_steps: 100 image_meta_size: [1024, 1024, 1024, 1024, 0, 0]

C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\transformers\models\bert\modeling_bert.py:435: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\transformers\cuda\sdp_utils.cpp:455.) attn_output = torch.nn.functional.scaled_dot_product_attention( 0%| | 0/100 [00:00<?, ?it/s] Traceback (most recent call last): File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\gradio\queueing.py", line 527, in process_events response = await route_utils.call_process_api( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\gradio\route_utils.py", line 270, in call_process_api output = await app.get_blocks().process_api( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\gradio\blocks.py", line 1887, in process_api result = await self.call_function( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\gradio\blocks.py", line 1472, in call_function prediction = await anyio.to_thread.run_sync( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\anyio\to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\anyio_backends_asyncio.py", line 2144, in run_sync_in_worker_thread return await future File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\anyio_backends_asyncio.py", line 851, in run result = context.run(func, *args) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\gradio\utils.py", line 808, in wrapper response = f(*args, **kwargs) File "E:\software\HunyuanDiT\app\hydit_app.py", line 50, in infer results = gen.predict(prompt, File "E:\software\HunyuanDiT\hydit\inference.py", line 367, in predict samples = self.pipeline( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "E:\software\HunyuanDiT\hydit\diffusion\pipeline.py", line 770, in call noise_pred = self.unet( File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "E:\software\HunyuanDiT\hydit\modules\models.py", line 296, in forward text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5)) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\container.py", line 217, in forward input = module(input) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl return forward_call(*args, **kwargs) File "C:\Users\Administrator\pinokio\bin\miniconda\lib\site-packages\torch\nn\modules\linear.py", line 116, in forward return F.linear(input, self.weight,self.bias) RuntimeError: mat1 and mat2 shapes cannot be multiplied (512x768 and 2048x8192)

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