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tfg.math.interpolation.slerp.vector_weights

Spherical linear interpolation (slerp) between two unnormalized vectors.

tfg.math.interpolation.slerp.vector_weights(
    vector1: type_alias.TensorLike,
    vector2: type_alias.TensorLike,
    percent: Union[type_alias.Float, type_alias.TensorLike],
    eps: Optional[type_alias.Float] = None,
    name: str = 'vector_weights'
) -> Tuple[tf.Tensor, tf.Tensor]

This function applies geometric slerp to unnormalized vectors by first normalizing them to return the interpolation weights. It reduces to lerp when input vectors are exactly anti-parallel.

In the following, A1 to An are optional batch dimensions.

vector1 A tensor of shape [A1, ... , An, M], which stores a normalized vector in its last dimension.
vector2 A tensor of shape [A1, ... , An, M], which stores a normalized vector in its last dimension.
percent A float or tensor with shape broadcastable to the shape of input vectors.
eps A small float for operation safety. If left None, its value is automatically selected using dtype of input vectors.
name A name for this op. Defaults to "vector_weights".

ValueError if the shape of vector1, vector2, or percent is not supported.

Two tensors of shape [A1, ... , An, 1], representing interpolation weights for each input vector.