LayerNormKernelImpl" not implemented for 'Half'
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To create a public link, set share=True
in launch()
.
C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\functional.py:3737: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
Traceback (most recent call last):
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\gradio\queueing.py", line 495, in call_prediction
output = await route_utils.call_process_api(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
output = await app.get_blocks().process_api(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\gradio\blocks.py", line 1561, in process_api
result = await self.call_function(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\gradio\blocks.py", line 1179, in call_function
prediction = await anyio.to_thread.run_sync(
File "C:\Users\ggrov\anaconda3\envs\magicloth\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\ggrov\anaconda3\envs\magicloth\lib\site-packages\anyio_backends_asyncio.py", line 2144, in run_sync_in_worker_thread
return await future
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\anyio_backends_asyncio.py", line 851, in run
result = context.run(func, *args)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\gradio\utils.py", line 695, in wrapper
response = f(*args, **kwargs)
File "F:\MagicClothing-main\gradio_generate.py", line 29, in process
images, cloth_mask_image = full_net.generate(cloth_image, cloth_mask_image, prompt, a_prompt, num_samples, n_prompt, seed, scale, cloth_guidance_scale, sample_steps, height, width)
File "F:\MagicClothing-main\garment_adapter\garment_diffusion.py", line 82, in generate
prompt_embeds, negative_prompt_embeds = self.pipe.encode_prompt(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py", line 403, in encode_prompt
prompt_embeds = self.text_encoder(text_input_ids.to(device), attention_mask=attention_mask)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\transformers\models\clip\modeling_clip.py", line 823, in forward
return self.text_model(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\transformers\models\clip\modeling_clip.py", line 741, in forward
encoder_outputs = self.encoder(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\transformers\models\clip\modeling_clip.py", line 655, in forward
layer_outputs = encoder_layer(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\transformers\models\clip\modeling_clip.py", line 384, in forward
hidden_states = self.layer_norm1(hidden_states)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\modules\normalization.py", line 190, in forward
return F.layer_norm(
File "C:\Users\ggrov\anaconda3\envs\magicloth\lib\site-packages\torch\nn\functional.py", line 2515, in layer_norm
return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: "LayerNormKernelImpl" not implemented for 'Half'