tfg.math.vector.reflect
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Args
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Computes the reflection direction for an incident vector.

tfg.math.vector.reflect(
    vector: TensorLike,
    normal: TensorLike,
    axis: int = -1,
    name: str = 'vector_reflect'
) -> TensorLike

For an incident vector $\mathbf{v}$ and normal $\mathbf{n}$ this function computes the reflected vector as $\mathbf{r} = \mathbf{v} - 2(\mathbf{n}^T\mathbf{v})\mathbf{n}$ .

Note
In the following, A1 to An are optional batch dimensions, which should be broadcast compatible.

Args
`vector`	A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i = axis represents a vector.
`normal`	A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i = axis represents a normal around which the vector needs to be reflected. The normal vector needs to be normalized.
`axis`	The dimension along which to compute the reflection.
`name`	A name for this op which defaults to "vector_reflect".

Returns
A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i = axis represents a reflected vector.

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Args

Returns

tfg.math.vector.reflect
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