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 = &#x27;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.

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

Args
`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".

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

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

tfg.math.interpolation.slerp.vector_weights

Note

Args

Raises

Returns