mean#
Compute the mean of the reduction dimensions
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template<typename InType, int D>
__MATX_INLINE__ auto matx::mean(const InType &in, const int (&dims)[D])# Calculate the mean of values in an operator along axes
Performs a sum reduction from tensor “in”, followed by a division by the number of elements in the reduction. Similar to the reduce function, the type of reduction is dependent on the rank of the output tensor. A single value denotes a reduction over the entire input, a 1D tensor denotes a reduction over each row independently, etc.
- 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
- Returns:
Operator with reduced values of mean-reduce computed
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template<typename InType>
__MATX_INLINE__ auto matx::mean(const InType &in)# Calculate the mean of values in an operator
Performs a sum reduction from operator, followed by a division by the number of elements in the reduction. Similar to the reduce function, the type of reduction is dependent on the rank of the output tensor. A single value denotes a reduction over the entire input, a 1D tensor denotes a reduction over each row independently, etc.
- Template Parameters:
InType – Input data type
- Parameters:
in – Input data to reduce
- Returns:
Operator with reduced values of mean-reduce computed
Examples#
auto t0 = make_tensor<TestType>({});
auto t4 = ones<TestType>({30, 40, 50, 60});
// Compute the mean over all dimensions in "t4" and store the result in "t0"
(t0 = mean(t4)).run(exec);