From abfa22c16fb3d9b1ed8d049c7b68e94d1cca5b82 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 7 Nov 2022 19:25:43 -0500
Subject: [PATCH] Revert "MPS Upscalers Fix"

This reverts commit 768b95394a8500da639b947508f78296524f1836.
---
 modules/devices.py      | 9 ---------
 modules/esrgan_model.py | 2 +-
 modules/scunet_model.py | 3 ++-
 modules/swinir_model.py | 2 +-
 4 files changed, 4 insertions(+), 12 deletions(-)

diff --git a/modules/devices.py b/modules/devices.py
index 67165bf66..a87d0d4c9 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 c61669b46..9a9c38f1f 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 59532274f..36a996bf0 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 4253b66d5..facd262db 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