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initial support for training textual inversion
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@@ -32,10 +32,9 @@ def enable_tf32():
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errors.run(enable_tf32, "Enabling TF32")
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device = get_optimal_device()
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device_codeformer = cpu if has_mps else device
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dtype = torch.float16
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def randn(seed, shape):
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# Pytorch currently doesn't handle setting randomness correctly when the metal backend is used.
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