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| author | Nuullll <vfirst218@gmail.com> | 2023-12-02 07:54:25 +0000 |
|---|---|---|
| committer | Nuullll <vfirst218@gmail.com> | 2023-12-02 07:54:25 +0000 |
| commit | 87cd07b3af74c447b02570bf3963ba83ade2e203 (patch) | |
| tree | fa4f5127ff28b983f1daaa64cbdbacdf820372ff | |
| parent | 7499148ad4dbd3444215c843d02453f68c459707 (diff) | |
| download | stable-diffusion-webui-gfx803-87cd07b3af74c447b02570bf3963ba83ade2e203.tar.gz stable-diffusion-webui-gfx803-87cd07b3af74c447b02570bf3963ba83ade2e203.tar.bz2 stable-diffusion-webui-gfx803-87cd07b3af74c447b02570bf3963ba83ade2e203.zip | |
Fix fp64
| -rw-r--r-- | modules/sd_samplers_timesteps_impl.py | 4 | ||||
| -rw-r--r-- | modules/xpu_specific.py | 2 |
2 files changed, 3 insertions, 3 deletions
diff --git a/modules/sd_samplers_timesteps_impl.py b/modules/sd_samplers_timesteps_impl.py index a72daafd..930a64af 100644 --- a/modules/sd_samplers_timesteps_impl.py +++ b/modules/sd_samplers_timesteps_impl.py @@ -11,7 +11,7 @@ from modules.models.diffusion.uni_pc import uni_pc def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta=0.0):
alphas_cumprod = model.inner_model.inner_model.alphas_cumprod
alphas = alphas_cumprod[timesteps]
- alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)
+ alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' and x.device.type != 'xpu' else torch.float32)
sqrt_one_minus_alphas = torch.sqrt(1 - alphas)
sigmas = eta * np.sqrt((1 - alphas_prev.cpu().numpy()) / (1 - alphas.cpu()) * (1 - alphas.cpu() / alphas_prev.cpu().numpy()))
@@ -43,7 +43,7 @@ def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta= def plms(model, x, timesteps, extra_args=None, callback=None, disable=None):
alphas_cumprod = model.inner_model.inner_model.alphas_cumprod
alphas = alphas_cumprod[timesteps]
- alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)
+ alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' and x.device.type != 'xpu' else torch.float32)
sqrt_one_minus_alphas = torch.sqrt(1 - alphas)
extra_args = {} if extra_args is None else extra_args
diff --git a/modules/xpu_specific.py b/modules/xpu_specific.py index 2df68665..d933c790 100644 --- a/modules/xpu_specific.py +++ b/modules/xpu_specific.py @@ -4,7 +4,7 @@ from modules.sd_hijack_utils import CondFunc has_ipex = False try: import torch - import intel_extension_for_pytorch as ipex + import intel_extension_for_pytorch as ipex # noqa: F401 has_ipex = True except Exception: pass |