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emergency fix for #1199

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AUTOMATIC
2022-09-28 10:49:07 +03:00
parent 15f333a266
commit 2ab64ec81a
1 changed files with 13 additions and 12 deletions
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13
modules/sd_samplers.py
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@@ -3,6 +3,7 @@ import numpy as np
import torch import torch
import tqdm import tqdm
from PIL import Image from PIL import Image
import inspect
import k_diffusion.sampling import k_diffusion.sampling
import ldm.models.diffusion.ddim import ldm.models.diffusion.ddim
@@ -278,9 +279,9 @@ class KDiffusionSampler:
k_diffusion.sampling.torch = TorchHijack(self) k_diffusion.sampling.torch = TorchHijack(self)
extra_params_kwargs = {} extra_params_kwargs = {}
for val in self.extra_params: for param_name in self.extra_params:
if hasattr(p,val): if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:
extra_params_kwargs[val] = getattr(p,val) extra_params_kwargs[param_name] = getattr(p, param_name)
return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs) return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
@@ -300,9 +301,9 @@ class KDiffusionSampler:
k_diffusion.sampling.torch = TorchHijack(self) k_diffusion.sampling.torch = TorchHijack(self)
extra_params_kwargs = {} extra_params_kwargs = {}
for val in self.extra_params: for param_name in self.extra_params:
if hasattr(p,val): if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:
extra_params_kwargs[val] = getattr(p,val) extra_params_kwargs[param_name] = getattr(p, param_name)
samples = self.func(self.model_wrap_cfg, x, sigmas, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs) samples = self.func(self.model_wrap_cfg, x, sigmas, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)