tfg.math.interpolation.slerp.interpolate_with_weights

Interpolates vectors by taking their weighted sum.

tfg.math.interpolation.slerp.interpolate_with_weights(
    vector1: type_alias.TensorLike,
    vector2: type_alias.TensorLike,
    weight1: Union[type_alias.Float, type_alias.TensorLike],
    weight2: Union[type_alias.Float, type_alias.TensorLike],
    name: str = 'interpolate_with_weights'
) -> tf.Tensor

Interpolation for all variants of slerp is a simple weighted sum over inputs. Therefore this function simply returns weight1 * vector1 + weight2 * vector2.

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.
`weight1`	A `float` or a tensor describing weights for the `vector1` and with a shape broadcastable to the shape of the input vectors.
`weight2`	A `float` or a tensor describing weights for the `vector2` and with a shape broadcastable to the shape of the input vectors.
`name`	A name for this op. Defaults to "interpolate_with_weights".

Returns
A tensor of shape `[A1, ... , An, M]` containing the result of the interpolation.

tfg.math.interpolation.slerp.interpolate_with_weights

Note

Args

Returns