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.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2022-10-28 UTC.
[null,null,["Last updated 2022-10-28 UTC."],[],[]]