mirror of
https://github.com/openvinotoolkit/stable-diffusion-webui.git
synced 2024-12-15 15:13:45 +03:00
Removing parts no longer needed to fix vram
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parent
1f50971fb8
commit
82380d9ac1
@ -1,7 +1,6 @@
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import contextlib
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import contextlib
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import torch
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import torch
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import gc
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from modules import errors
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from modules import errors
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@ -20,8 +19,8 @@ def get_optimal_device():
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return cpu
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return cpu
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def torch_gc():
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def torch_gc():
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gc.collect()
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if torch.cuda.is_available():
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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torch.cuda.empty_cache()
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torch.cuda.ipc_collect()
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torch.cuda.ipc_collect()
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@ -346,7 +346,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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state.job_count = p.n_iter
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state.job_count = p.n_iter
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for n in range(p.n_iter):
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for n in range(p.n_iter):
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with torch.no_grad(), precision_scope("cuda"), ema_scope():
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if state.interrupted:
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if state.interrupted:
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break
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break
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@ -396,21 +395,18 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
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x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
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for i, x_sample in enumerate(x_samples_ddim):
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for i, x_sample in enumerate(x_samples_ddim):
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with torch.no_grad(), precision_scope("cuda"), ema_scope():
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x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
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x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
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x_sample = x_sample.astype(np.uint8)
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x_sample = x_sample.astype(np.uint8)
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if p.restore_faces:
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if p.restore_faces:
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with torch.no_grad(), precision_scope("cuda"), ema_scope():
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if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
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if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
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images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
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images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
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devices.torch_gc()
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x_sample = modules.face_restoration.restore_faces(x_sample)
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x_sample = modules.face_restoration.restore_faces(x_sample)
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devices.torch_gc()
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devices.torch_gc()
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devices.torch_gc()
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with torch.no_grad(), precision_scope("cuda"), ema_scope():
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image = Image.fromarray(x_sample)
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image = Image.fromarray(x_sample)
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if p.color_corrections is not None and i < len(p.color_corrections):
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if p.color_corrections is not None and i < len(p.color_corrections):
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@ -444,7 +440,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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state.nextjob()
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state.nextjob()
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with torch.no_grad(), precision_scope("cuda"), ema_scope():
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p.color_corrections = None
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p.color_corrections = None
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index_of_first_image = 0
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index_of_first_image = 0
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