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https://github.com/vladmandic/automatic
synced 2026-09-18 16:54:33 +02:00
Remove Intel ARC 1024x1024 workaround from OpenVINO
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@@ -145,7 +145,7 @@ class StableDiffusionProcessing:
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self.cfg_scale: float = cfg_scale
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self.image_cfg_scale = image_cfg_scale
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self.diffusers_guidance_rescale = diffusers_guidance_rescale
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if (devices.backend == "ipex" or shared.cmd_opts.use_openvino) and width == 1024 and height == 1024:
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if devices.backend == "ipex" and width == 1024 and height == 1024:
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width = 1080
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height = 1080
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self.width: int = width
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@@ -762,7 +762,7 @@ def validate_sample(tensor):
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elif isinstance(tensor, np.ndarray):
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sample = tensor
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else:
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shared.log.warning(f'Unknown sample type: {type(tensor)}')
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shared.log.warning(f'Unknown sample type: {type(tensor)}')
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sample = 255.0 * np.moveaxis(sample, 0, 2) if shared.backend == shared.Backend.ORIGINAL else 255.0 * sample
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with warnings.catch_warnings(record=True) as w:
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cast = sample.astype(np.uint8)
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@@ -1014,7 +1014,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_force: bool = False, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, refiner_steps: int = 5, refiner_start: float = 0, refiner_prompt: str = '', refiner_negative: str = '', **kwargs):
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super().__init__(**kwargs)
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if devices.backend == "ipex" or shared.cmd_opts.use_openvino:
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if devices.backend == "ipex":
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width_curse = bool(hr_resize_x == 1024 and self.height * (hr_resize_x / self.width) == 1024)
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height_curse = bool(hr_resize_y == 1024 and self.width * (hr_resize_y / self.height) == 1024)
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if (width_curse != height_curse) or (height_curse and width_curse):
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