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https://github.com/invoke-ai/InvokeAI
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Make FLUX get_noise(...) consistent across devices/dtypes.
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@ -79,8 +79,6 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
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inference_dtype = torch.bfloat16
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# Prepare input noise.
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# TODO(ryand): Does the seed behave the same on different devices? Should we re-implement this to always use a
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# CPU RNG?
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x = get_noise(
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num_samples=1,
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height=self.height,
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@ -20,16 +20,19 @@ def get_noise(
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dtype: torch.dtype,
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seed: int,
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):
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# We always generate noise on the same device and dtype then cast to ensure consistency across devices/dtypes.
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rand_device = "cpu"
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rand_dtype = torch.float16
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return torch.randn(
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num_samples,
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16,
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# allow for packing
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2 * math.ceil(height / 16),
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2 * math.ceil(width / 16),
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device=device,
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dtype=dtype,
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generator=torch.Generator(device=device).manual_seed(seed),
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)
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device=rand_device,
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dtype=rand_dtype,
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generator=torch.Generator(device=rand_device).manual_seed(seed),
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).to(device=device, dtype=dtype)
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def prepare(t5: HFEncoder, clip: HFEncoder, img: Tensor, prompt: str | list[str]) -> dict[str, Tensor]:
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