resolved multiple conflicts between PR #683 and subsequent PRs

docs/features/UPSCALE.md

@@ -2,17 +2,16 @@
 title: Upscale
 ---
 
+## Intro
 
-# :material-image-size-select-large: Upscale 
+The script provides the ability to restore faces and upscale. You can apply these operations
+at the time you generate the images, or at any time to a previously-generated PNG file, using 
+the [!fix](#fixing-previously-generated-images) command.
 
-## **Intro**
+## Face Fixing
 
-The script provides the ability to restore faces and upscale.
-
-You can enable these features by passing `--restore` and `--esrgan` to your launch script to enable
-face restoration modules and upscaling modules respectively.
-
-The default face restoration module is GFPGAN and the default upscaling module is ESRGAN.
+The default face restoration module is GFPGAN. The default upscale is Real-ESRGAN. For an alternative
+face restoration module, see [CodeFormer Support] below.
 
 As of version 1.14, environment.yaml will install the Real-ESRGAN package into the standard install
 location for python packages, and will put GFPGAN into a subdirectory of "src" in the
@@ -142,8 +141,6 @@ that is the best restoration possible. This may deviate slightly from the origin
 excellent option to use in situations when there is very little facial data to work with.
 
 `<prompt> -G 1.0 -ft codeformer -cf 0.1`
-<<<<<<< HEAD
-=======
 
 ## Fixing Previously-Generated Images
 
@@ -162,5 +159,3 @@ the `!fix` command does not replace the original file, unlike the behavior at ge
 
 If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries, you can disable them 
 on the dream.py command line with the `--no_restore` and `--no_upscale` options, respectively.
-
->>>>>>> Update UPSCALE.md

ldm/generate.py

@@ -27,11 +27,29 @@ from ldm.util import instantiate_from_config
 from ldm.models.diffusion.ddim import DDIMSampler
 from ldm.models.diffusion.plms import PLMSSampler
 from ldm.models.diffusion.ksampler import KSampler
-from ldm.dream.pngwriter           import PngWriter, retrieve_metadata
-from ldm.dream.args                import metadata_loads
-from ldm.dream.image_util          import InitImageResizer
-from ldm.dream.devices             import choose_torch_device, choose_precision
-from ldm.dream.conditioning        import get_uc_and_c
+from ldm.dream.pngwriter import PngWriter, retrieve_metadata
+from ldm.dream.args import metadata_loads
+from ldm.dream.image_util import InitImageResizer
+from ldm.dream.devices import choose_torch_device
+from ldm.dream.conditioning import get_uc_and_c
+
+def fix_func(orig):
+    if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+        def new_func(*args, **kw):
+            device = kw.get("device", "mps")
+            kw["device"]="cpu"
+            return orig(*args, **kw).to(device)
+        return new_func
+    return orig
+
+torch.rand = fix_func(torch.rand)
+torch.rand_like = fix_func(torch.rand_like)
+torch.randn = fix_func(torch.randn)
+torch.randn_like = fix_func(torch.randn_like)
+torch.randint = fix_func(torch.randint)
+torch.randint_like = fix_func(torch.randint_like)
+torch.bernoulli = fix_func(torch.bernoulli)
+torch.multinomial = fix_func(torch.multinomial)
 
 def fix_func(orig):
     if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():

scripts/dream.py

@@ -76,7 +76,7 @@ def main():
             gfpgan=gfpgan,
             codeformer=codeformer,
             esrgan=esrgan
-        )
+            )
     except (FileNotFoundError, IOError, KeyError) as e:
         print(f'{e}. Aborting.')
         sys.exit(-1)
@@ -414,20 +414,5 @@ def dream_server_loop(gen, host, port, outdir, gfpgan):
 
     dream_server.server_close()
 
-
-<<<<<<< HEAD
-=======
-def write_log_message(results, log_path):
-    """logs the name of the output image, prompt, and prompt args to the terminal and log file"""
-    global output_cntr
-    log_lines = [f'{path}: {prompt}\n' for path, prompt in results]
-    for l in log_lines:
-        output_cntr += 1
-        print(f'[{output_cntr}] {l}', end='')
-
-    with open(log_path, 'a', encoding='utf-8') as file:
-        file.writelines(log_lines)
-
->>>>>>> GFPGAN and Real ESRGAN Implementation Refactor
 if __name__ == '__main__':
     main()