var#
Compute the variance of a tensor. ddof can be used optionally to control the bias term in the denominator
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template<typename InType, int D>
__MATX_INLINE__ auto matx::var(const InType &in, const int (&dims)[D], int ddof = 1)# Compute a variance reduction
Computes the variance of the input according to the output tensor rank and size
- Template Parameters:
InType – Input data type
D – Num of dimensions to reduce over
- Parameters:
in – Input data to reduce
dims – Array containing dimensions to reduce over
ddof – Delta Degrees Of Freedom used in the divisor of the result as N - ddof. Defaults to 1 to give an unbiased estimate
- Returns:
Operator with reduced values of variance computed
-
template<typename InType>
__MATX_INLINE__ auto matx::var(const InType &in, int ddof = 1)# Compute a variance reduction
Computes the variance of the input according to the output tensor rank and size
- Template Parameters:
InType – Input data type
- Parameters:
in – Input data to reduce
ddof – Delta Degrees Of Freedom used in the divisor of the result as N - ddof. Defaults to 1 to give an unbiased estimate
- Returns:
Operator with reduced values of variance computed
Examples#
(t0 = var(t1)).run(exec);