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| steps_offset=1, | ||
| timestep_spacing="leading", | ||
| ) | ||
| scheduler = EulerDiscreteScheduler.from_config(scheduler_dict) |
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can we pass a scheduler in? i would like to be able to convert it and attach DDIM, as that's a better sampler for SDXL even though it's divergent from their upstream impl.
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I like the idea of being able to customize the scheduler. I like Euler, but I usually customize the settings of the scheduler.
| original_size: Tuple[int, int] = (1024, 1024), | ||
| original_size: Tuple[int, int] = None, | ||
| crops_coords_top_left: Tuple[int, int] = (0, 0), | ||
| target_size: Tuple[int, int] = (1024, 1024), | ||
| target_size: Tuple[int, int] = None, |
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why is this now defaulting to None? can you explain a bit?
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It will then later be set to the passed height and width this makes sure we generate correct outputs for different input sizes than 1024
bghira
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thank you for fixing the CKPT converter.
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i want to increase the batch_size to get larger throughput,but i got linear growth of latency.if i run some incorrect settings? |
* improve sd xl * correct more * finish * make style * fix more
* improve sd xl * correct more * finish * make style * fix more
What does this PR do?
This PR makes sure
diffusersStable Diffusion XL can generate images of any size. We also make sure that both single file format and diffusers format can be loaded.Diffusers format:
Single File Format:
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