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fix typo (sinuosoidal -> sinusoidal)
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@ -32,14 +32,14 @@ class RangeEncoder(fl.Chain):
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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.Lambda(self.compute_sinusoidal_embedding),
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fl.Converter(set_device=False, set_dtype=True),
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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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def compute_sinusoidal_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.sinusoidal_embedding_dim)
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@ -28,7 +28,7 @@ class TextTimeEmbedding(fl.Chain):
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fl.Chain(
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fl.UseContext(context="diffusion", key="time_ids"),
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fl.Unsqueeze(dim=-1),
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fl.Lambda(func=self.compute_sinuosoidal_embedding),
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fl.Lambda(func=self.compute_sinusoidal_embedding),
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fl.Reshape(-1),
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),
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dim=1,
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@ -49,7 +49,7 @@ class TextTimeEmbedding(fl.Chain):
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),
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)
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def compute_sinuosoidal_embedding(self, x: Tensor) -> Tensor:
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def compute_sinusoidal_embedding(self, x: Tensor) -> Tensor:
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return compute_sinusoidal_embedding(x=x, embedding_dim=self.time_ids_embedding_dim)
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