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authorbrkirch <brkirch@users.noreply.github.com>2023-01-25 04:51:45 +0000
committerbrkirch <brkirch@users.noreply.github.com>2023-01-25 06:13:02 +0000
commit84d9ce30cb427759547bc7876ed80ab91787d175 (patch)
treea87ca1a7094ca9b7af4e573a211b1dcf8146af67 /modules/devices.py
parent48a15821de768fea76e66f26df83df3fddf18f4b (diff)
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Add option for float32 sampling with float16 UNet
This also handles type casting so that ROCm and MPS torch devices work correctly without --no-half. One cast is required for deepbooru in deepbooru_model.py, some explicit casting is required for img2img and inpainting. depth_model can't be converted to float16 or it won't work correctly on some systems (it's known to have issues on MPS) so in sd_models.py model.depth_model is removed for model.half().
Diffstat (limited to 'modules/devices.py')
-rw-r--r--modules/devices.py2
1 files changed, 2 insertions, 0 deletions
diff --git a/modules/devices.py b/modules/devices.py
index 524ec7af..0981ef80 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -79,6 +79,8 @@ cpu = torch.device("cpu")
device = device_interrogate = device_gfpgan = device_esrgan = device_codeformer = None
dtype = torch.float16
dtype_vae = torch.float16
+dtype_unet = torch.float16
+unet_needs_upcast = False
def randn(seed, shape):