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| author | brkirch <brkirch@users.noreply.github.com> | 2022-11-07 19:25:43 -0500 |
|---|---|---|
| committer | brkirch <brkirch@users.noreply.github.com> | 2022-11-17 00:08:21 -0500 |
| commit | abfa22c16fb3d9b1ed8d049c7b68e94d1cca5b82 (patch) | |
| tree | f2e1ef625405fc93408d15dea3d092c7398f4a19 | |
| parent | 98947d173e3f1667eba29c904f681047dea9de90 (diff) | |
Revert "MPS Upscalers Fix"
This reverts commit 768b95394a8500da639b947508f78296524f1836.
| -rw-r--r-- | modules/devices.py | 9 | ||||
| -rw-r--r-- | modules/esrgan_model.py | 2 | ||||
| -rw-r--r-- | modules/scunet_model.py | 3 | ||||
| -rw-r--r-- | modules/swinir_model.py | 2 |
4 files changed, 4 insertions, 12 deletions
diff --git a/modules/devices.py b/modules/devices.py index 67165bf6..a87d0d4c 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -94,12 +94,3 @@ def autocast(disable=False): return contextlib.nullcontext() return torch.autocast("cuda") - - -# MPS workaround for https://github.com/pytorch/pytorch/issues/79383 -def mps_contiguous(input_tensor, device): - return input_tensor.contiguous() if device.type == 'mps' else input_tensor - - -def mps_contiguous_to(input_tensor, device): - return mps_contiguous(input_tensor, device).to(device) diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index c61669b4..9a9c38f1 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -199,7 +199,7 @@ def upscale_without_tiling(model, img): img = img[:, :, ::-1]
img = np.ascontiguousarray(np.transpose(img, (2, 0, 1))) / 255
img = torch.from_numpy(img).float()
- img = devices.mps_contiguous_to(img.unsqueeze(0), devices.device_esrgan)
+ img = img.unsqueeze(0).to(devices.device_esrgan)
with torch.no_grad():
output = model(img)
output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
diff --git a/modules/scunet_model.py b/modules/scunet_model.py index 59532274..36a996bf 100644 --- a/modules/scunet_model.py +++ b/modules/scunet_model.py @@ -54,8 +54,9 @@ class UpscalerScuNET(modules.upscaler.Upscaler): img = img[:, :, ::-1] img = np.moveaxis(img, 2, 0) / 255 img = torch.from_numpy(img).float() - img = devices.mps_contiguous_to(img.unsqueeze(0), device) + img = img.unsqueeze(0).to(device) + img = img.to(device) with torch.no_grad(): output = model(img) output = output.squeeze().float().cpu().clamp_(0, 1).numpy() diff --git a/modules/swinir_model.py b/modules/swinir_model.py index 4253b66d..facd262d 100644 --- a/modules/swinir_model.py +++ b/modules/swinir_model.py @@ -111,7 +111,7 @@ def upscale( img = img[:, :, ::-1] img = np.moveaxis(img, 2, 0) / 255 img = torch.from_numpy(img).float() - img = devices.mps_contiguous_to(img.unsqueeze(0), devices.device_swinir) + img = img.unsqueeze(0).to(devices.device_swinir) with torch.no_grad(), precision_scope("cuda"): _, _, h_old, w_old = img.size() h_pad = (h_old // window_size + 1) * window_size - h_old |