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https://github.com/invoke-ai/InvokeAI
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deps: upgrade to PyTorch 2.0 (replaces xformers)
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@ -461,8 +461,7 @@ def get_torch_source() -> (Union[str, None],str):
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url = "https://download.pytorch.org/whl/cpu"
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url = "https://download.pytorch.org/whl/cpu"
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if device == 'cuda':
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if device == 'cuda':
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url = 'https://download.pytorch.org/whl/cu117'
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url = 'https://download.pytorch.org/whl/cu118'
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optional_modules = '[xformers]'
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# in all other cases, Torch wheels should be coming from PyPi as of Torch 1.13
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# in all other cases, Torch wheels should be coming from PyPi as of Torch 1.13
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@ -531,7 +531,8 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
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run_id: str = None,
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run_id: str = None,
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additional_guidance: List[Callable] = None,
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additional_guidance: List[Callable] = None,
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):
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):
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self._adjust_memory_efficient_attention(latents)
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# FIXME: do we still use any slicing now that PyTorch 2.0 has scaled dot-product attention on all platforms?
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# self._adjust_memory_efficient_attention(latents)
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if run_id is None:
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if run_id is None:
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run_id = secrets.token_urlsafe(self.ID_LENGTH)
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run_id = secrets.token_urlsafe(self.ID_LENGTH)
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if additional_guidance is None:
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if additional_guidance is None:
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@ -71,10 +71,10 @@ dependencies = [
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"scikit-image>=0.19",
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"scikit-image>=0.19",
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"send2trash",
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"send2trash",
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"test-tube>=0.7.5",
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"test-tube>=0.7.5",
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"torch>=1.13.1",
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"torch~=2.0",
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"torchvision>=0.14.1",
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"torchvision>=0.14.1",
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"torchmetrics",
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"torchmetrics",
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"transformers~=4.26",
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"transformers~=4.27",
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"uvicorn[standard]==0.20.0",
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"uvicorn[standard]==0.20.0",
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"windows-curses; sys_platform=='win32'",
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"windows-curses; sys_platform=='win32'",
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]
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]
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@ -90,10 +90,6 @@ dependencies = [
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"pudb",
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"pudb",
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]
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]
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"test" = ["pytest>6.0.0", "pytest-cov"]
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"test" = ["pytest>6.0.0", "pytest-cov"]
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"xformers" = [
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"xformers~=0.0.16; sys_platform!='darwin'",
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"triton; sys_platform=='linux'",
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]
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[project.scripts]
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[project.scripts]
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