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set dtype before calling ae closes #1562
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@@ -651,7 +651,7 @@ def train(args):
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else:
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with torch.no_grad():
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# encode images to latents. images are [-1, 1]
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latents = ae.encode(batch["images"])
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latents = ae.encode(batch["images"].to(ae.dtype)).to(accelerator.device, dtype=weight_dtype)
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# NaNが含まれていれば警告を表示し0に置き換える
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if torch.any(torch.isnan(latents)):
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