not working with high res fix

[IkariDevGIT]

To create a public link, set share=True in launch().
Unloading hypernetwork
daam run
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Error executing callback before_image_saved_callback for D:\stable-diffusion-webui\extensions\stable-diffusion-webui-daam\scripts\daam_script.py
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\script_callbacks.py", line 121, in before_image_saved_callback
c.callback(params)
File "D:\stable-diffusion-webui\extensions\stable-diffusion-webui-daam\scripts\daam_script.py", line 88, in before_image_saved
global_heat_map = self.tracer.compute_global_heat_map(params.p.prompt)
AttributeError: 'NoneType' object has no attribute 'prompt'

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Error executing callback before_image_saved_callback for D:\stable-diffusion-webui\extensions\stable-diffusion-webui-daam\scripts\daam_script.py
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\script_callbacks.py", line 121, in before_image_saved_callback
c.callback(params)
File "D:\stable-diffusion-webui\extensions\stable-diffusion-webui-daam\scripts\daam_script.py", line 88, in before_image_saved
global_heat_map = self.tracer.compute_global_heat_map(params.p.prompt)
File "D:\stable-diffusion-webui\extensions\stable-diffusion-webui-daam\scripts\daam\trace.py", line 167, in compute_global_heat_map
maps = torch.stack([torch.stack(x, 0) for x in all_merges], dim=0)
RuntimeError: stack expects each tensor to be equal size, but got [2, 154, 1, 64, 32] at entry 0 and [4, 154, 1, 64, 32] at entry 59

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[kousw]

Thank you for reporting the problem. However, it may be a bit difficult.
Highres fix first generates a low-resolution image, then the desired resolution.
The current implementation only combines heatmaps of consistent resolution.
I will give it some thought.

[ghost]

This works but only for specific resolution combination(s). As an example, and the only one I've seen that works, 1536x1024, with a firstpass size of 768x512, produces no error, and the heatmap generates fine. The width/height can be swapped in each as well. I can share an example if needed but this looks to be consistently reproducable.