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author | AUTOMATIC1111 <16777216c@gmail.com> | 2023-01-06 04:51:45 +0000 |
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committer | GitHub <noreply@github.com> | 2023-01-06 04:51:45 +0000 |
commit | 85fa4eacea859ef2c78d719f36b25a2e19dd0be1 (patch) | |
tree | 1597ed6d494ffb1efd95023f9283be1f9f473b82 | |
parent | 3ea354f274fe91bb224fe8bbe72ae215ac6622cf (diff) | |
parent | 8111b5569d07c7ac3b695e28171aede728b4ae56 (diff) | |
download | stable-diffusion-webui-gfx803-85fa4eacea859ef2c78d719f36b25a2e19dd0be1.tar.gz stable-diffusion-webui-gfx803-85fa4eacea859ef2c78d719f36b25a2e19dd0be1.tar.bz2 stable-diffusion-webui-gfx803-85fa4eacea859ef2c78d719f36b25a2e19dd0be1.zip |
Merge pull request #6402 from brkirch/work-with-nightly-local-builds
Add support for using PyTorch nightly and local builds
-rw-r--r-- | modules/devices.py | 28 | ||||
-rw-r--r-- | webui.py | 7 |
2 files changed, 29 insertions, 6 deletions
diff --git a/modules/devices.py b/modules/devices.py index 800510b7..caeb0276 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -133,8 +133,26 @@ def numpy_fix(self, *args, **kwargs): return orig_tensor_numpy(self, *args, **kwargs) -# PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working -if has_mps() and version.parse(torch.__version__) < version.parse("1.13"): - 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/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) + if any(output_dtype == broken_dtype for broken_dtype in [torch.bool, torch.int8, torch.int16, torch.int64]): + return cumsum_func(input.cpu(), *args, **kwargs).to(input.device) + return cumsum_func(input, *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 + elif version.parse(torch.__version__) > version.parse("1.13.1"): + if not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.Tensor([1,1]).to(torch.device("mps")).cumsum(0, dtype=torch.int16)): + 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) ) + orig_narrow = torch.narrow + torch.narrow = lambda *args, **kwargs: ( orig_narrow(*args, **kwargs).clone() ) @@ -4,7 +4,7 @@ import threading import time
import importlib
import signal
-import threading
+import re
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
@@ -13,6 +13,11 @@ from modules import import_hook, errors from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
from modules.paths import script_path
+import torch
+# Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
+if ".dev" in torch.__version__ or "+git" in torch.__version__:
+ torch.__version__ = re.search(r'[\d.]+', torch.__version__).group(0)
+
from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir
import modules.codeformer_model as codeformer
import modules.extras
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