Merge branch 'master' of github.com:AUTOMATIC1111/stable-diffusion-webui into gamepad

3 files changed, 18 insertions, 37 deletions

diff --git a/modules/devices.py b/modules/devices.py
index 655ca1d3..919048d0 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -2,6 +2,7 @@ import sys, os, shlex
 import contextlib
 import torch
 from modules import errors
+from modules.sd_hijack_utils import CondFunc
 from packaging import version
 
 
@@ -156,36 +157,7 @@ def test_for_nans(x, where):
     raise NansException(message)
 
 
-# MPS workaround for https://github.com/pytorch/pytorch/issues/79383
-orig_tensor_to = torch.Tensor.to
-def tensor_to_fix(self, *args, **kwargs):
-    if self.device.type != 'mps' and \
-       ((len(args) > 0 and isinstance(args[0], torch.device) and args[0].type == 'mps') or \
-       (isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps')):
-        self = self.contiguous()
-    return orig_tensor_to(self, *args, **kwargs)
-
-
-# MPS workaround for https://github.com/pytorch/pytorch/issues/80800 
-orig_layer_norm = torch.nn.functional.layer_norm
-def layer_norm_fix(*args, **kwargs):
-    if len(args) > 0 and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps':
-        args = list(args)
-        args[0] = args[0].contiguous()
-    return orig_layer_norm(*args, **kwargs)
-
-
-# MPS workaround for https://github.com/pytorch/pytorch/issues/90532
-orig_tensor_numpy = torch.Tensor.numpy
-def numpy_fix(self, *args, **kwargs):
-    if self.requires_grad:
-        self = self.detach()
-    return orig_tensor_numpy(self, *args, **kwargs)
-
-
 # MPS workaround for https://github.com/pytorch/pytorch/issues/89784
-orig_cumsum = torch.cumsum
-orig_Tensor_cumsum = torch.Tensor.cumsum
 def cumsum_fix(input, cumsum_func, *args, **kwargs):
     if input.device.type == 'mps':
         output_dtype = kwargs.get('dtype', input.dtype)
@@ -199,11 +171,20 @@ def cumsum_fix(input, cumsum_func, *args, **kwargs):
 if has_mps():
     if version.parse(torch.__version__) < version.parse("1.13"):
         # PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working
-        torch.Tensor.to = tensor_to_fix
-        torch.nn.functional.layer_norm = layer_norm_fix
-        torch.Tensor.numpy = numpy_fix
+
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/79383
+        CondFunc('torch.Tensor.to', lambda orig_func, self, *args, **kwargs: orig_func(self.contiguous(), *args, **kwargs),
+                                                          lambda _, self, *args, **kwargs: self.device.type != 'mps' and (args and isinstance(args[0], torch.device) and args[0].type == 'mps' or isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps'))
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/80800 
+        CondFunc('torch.nn.functional.layer_norm', lambda orig_func, *args, **kwargs: orig_func(*([args[0].contiguous()] + list(args[1:])), **kwargs),
+                                                                                        lambda _, *args, **kwargs: args and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps')
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/90532
+        CondFunc('torch.Tensor.numpy', lambda orig_func, self, *args, **kwargs: orig_func(self.detach(), *args, **kwargs), lambda _, self, *args, **kwargs: self.requires_grad)
     elif version.parse(torch.__version__) > version.parse("1.13.1"):
         cumsum_needs_int_fix = not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.ShortTensor([1,1]).to(torch.device("mps")).cumsum(0))
         cumsum_needs_bool_fix = not torch.BoolTensor([True,True]).to(device=torch.device("mps"), dtype=torch.int64).equal(torch.BoolTensor([True,False]).to(torch.device("mps")).cumsum(0))
-        torch.cumsum = lambda input, *args, **kwargs: ( cumsum_fix(input, orig_cumsum, *args, **kwargs) )
-        torch.Tensor.cumsum = lambda self, *args, **kwargs: ( cumsum_fix(self, orig_Tensor_cumsum, *args, **kwargs) )
+        cumsum_fix_func = lambda orig_func, input, *args, **kwargs: cumsum_fix(input, orig_func, *args, **kwargs)
+        CondFunc('torch.cumsum', cumsum_fix_func, None)
+        CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None)
+        CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None)
+
diff --git a/modules/shared.py b/modules/shared.py
index 69634fd8..5600d480 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -327,7 +327,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),

     "export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"),

 

-    "use_original_name_batch": OptionInfo(False, "Use original name for output filename during batch process in extras tab"),

+    "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"),

     "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"),

     "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),

     "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),

diff --git a/modules/ui.py b/modules/ui.py
index f910c582..5e34fb07 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -479,8 +479,8 @@ def create_ui():
                                 width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")

                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")

 

+                            res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")

                             if opts.dimensions_and_batch_together:

-                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")

                                 with gr.Column(elem_id="txt2img_column_batch"):

                                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")

                                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")

@@ -757,8 +757,8 @@ def create_ui():
                                 width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")

                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")

 

+                            res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")

                             if opts.dimensions_and_batch_together:

-                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")

                                 with gr.Column(elem_id="img2img_column_batch"):

                                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")

                                     batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")