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fix typo (sinuosidal -> sinusoidal)
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@ -24,23 +24,23 @@ def compute_sinusoidal_embedding(
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class RangeEncoder(fl.Chain):
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def __init__(
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self,
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sinuosidal_embedding_dim: int,
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sinusoidal_embedding_dim: int,
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embedding_dim: int,
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device: Device | str | None = None,
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dtype: DType | None = None,
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) -> None:
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self.sinuosidal_embedding_dim = sinuosidal_embedding_dim
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self.sinusoidal_embedding_dim = sinusoidal_embedding_dim
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self.embedding_dim = embedding_dim
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super().__init__(
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fl.Lambda(self.compute_sinuosoidal_embedding),
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fl.Converter(set_device=False, set_dtype=True),
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fl.Linear(in_features=sinuosidal_embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
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fl.Linear(in_features=sinusoidal_embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
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fl.SiLU(),
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fl.Linear(in_features=embedding_dim, out_features=embedding_dim, device=device, dtype=dtype),
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)
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def compute_sinuosoidal_embedding(self, x: Int[Tensor, "*batch 1"]) -> Float[Tensor, "*batch 1 embedding_dim"]:
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return compute_sinusoidal_embedding(x, embedding_dim=self.sinuosidal_embedding_dim)
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return compute_sinusoidal_embedding(x, embedding_dim=self.sinusoidal_embedding_dim)
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class RangeAdapter2d(fl.Sum, Adapter[fl.Conv2d]):
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@ -61,7 +61,7 @@ class TimestepEncoder(fl.Passthrough):
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fl.Chain(
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fl.UseContext(context="diffusion", key="timestep"),
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RangeEncoder(
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sinuosidal_embedding_dim=320,
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sinusoidal_embedding_dim=320,
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embedding_dim=self.timestep_embedding_dim,
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device=device,
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dtype=dtype,
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