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-rw-r--r--modules/sd_samplers.py24
1 files changed, 20 insertions, 4 deletions
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 2ca17d8b..4c123d3b 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -6,6 +6,7 @@ import tqdm
from PIL import Image
import inspect
import k_diffusion.sampling
+import torchsde._brownian.brownian_interval
import ldm.models.diffusion.ddim
import ldm.models.diffusion.plms
from modules import prompt_parser, devices, processing, images
@@ -18,7 +19,7 @@ from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
samplers_k_diffusion = [
- ('Euler a', 'sample_euler_ancestral', ['k_euler_a'], {}),
+ ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}),
('Euler', 'sample_euler', ['k_euler'], {}),
('LMS', 'sample_lms', ['k_lms'], {}),
('Heun', 'sample_heun', ['k_heun'], {}),
@@ -364,7 +365,23 @@ class TorchHijack:
if noise.shape == x.shape:
return noise
- return torch.randn_like(x)
+ if x.device.type == 'mps':
+ return torch.randn_like(x, device=devices.cpu).to(x.device)
+ else:
+ return torch.randn_like(x)
+
+
+# MPS fix for randn in torchsde
+def torchsde_randn(size, dtype, device, seed):
+ if device.type == 'mps':
+ generator = torch.Generator(devices.cpu).manual_seed(int(seed))
+ return torch.randn(size, dtype=dtype, device=devices.cpu, generator=generator).to(device)
+ else:
+ generator = torch.Generator(device).manual_seed(int(seed))
+ return torch.randn(size, dtype=dtype, device=device, generator=generator)
+
+
+torchsde._brownian.brownian_interval._randn = torchsde_randn
class KDiffusionSampler:
@@ -415,8 +432,7 @@ class KDiffusionSampler:
self.model_wrap.step = 0
self.eta = p.eta or opts.eta_ancestral
- if self.sampler_noises is not None:
- k_diffusion.sampling.torch = TorchHijack(self.sampler_noises)
+ k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
extra_params_kwargs = {}
for param_name in self.extra_params: