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add extensions profiling

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This commit is contained in:
Vladimir Mandic
2023-06-04 12:14:05 -04:00
parent 7301566353
commit 63ca5c17e7
10 changed files with 118 additions and 32 deletions
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modules/processing.py
+5 -13
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@@ -924,34 +924,26 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
decoded_samples = 2. * decoded_samples - 1.
if shared.opts.sd_vae_sliced_encode and len(decoded_samples) > 1:
samples = torch.stack([
self.sd_model.get_first_stage_encoding(
self.sd_model.encode_first_stage(torch.unsqueeze(decoded_sample, 0))
)[0]
self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(torch.unsqueeze(decoded_sample, 0)))[0]
for decoded_sample
in decoded_samples
])
else:
samples = self.sd_model.get_first_stage_encoding(
self.sd_model.encode_first_stage(decoded_samples)
)
samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples))
image_conditioning = self.img2img_image_conditioning(decoded_samples, samples)
shared.state.nextjob()
img2img_sampler_name = self.sampler_name
force_latent_upscaler = shared.opts.data.get('xyz_fallback_sampler')
if force_latent_upscaler != 'None' and force_latent_upscaler != 'PLMS':
img2img_sampler_name = force_latent_upscaler
elif shared.opts.fallback_sampler != 'PLMS':
img2img_sampler_name = shared.opts.fallback_sampler
else:
img2img_sampler_name = 'UniPC'
if img2img_sampler_name == 'PLMS':
img2img_sampler_name = shared.opts.fallback_sampler if shared.opts.fallback_sampler != 'PLMS' else 'UniPC'
self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model)
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self)
# GC now before running the next img2img to prevent running out of memory
x = None
devices.torch_gc()
devices.torch_gc() # GC now before running the next img2img to prevent running out of memory
# apply token merging optimizations from tomesd for high-res pass
# check if hr_only so we are not redundantly patching
if (cmd_opts.token_merging or opts.token_merging) and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio):
# case where user wants to use separate merge ratios
if not opts.token_merging_hr_only: