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float | nnfw::cker::round_nearest (float value) |
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template<typename Out , typename In > |
Out | nnfw::cker::mean_reducer (const Out data1, const In data2, int normalizer) |
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template<typename In > |
int | nnfw::cker::sum_reducer (const int data1, const In data2) |
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template<typename In , typename Out > |
bool | nnfw::cker::ReduceMeanImpl (const In *input_data, const Shape &input_shape, const int *axis, const int num_axis, int *input_iter, Out reducer(const Out current, const In in, int normalizer), Out *output_data) |
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template<typename In > |
size_t | nnfw::cker::ReduceSumQuantImpl (const In *input_data, const Shape &input_shape, const int *axis, const int num_axis, int *input_iter, int reducer(const int current, const In in), int *temp_sum) |
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template<typename In , typename Out > |
void | nnfw::cker::Mean (const Shape &input_shape, const In *input_data, const Shape &output_shape, Out *output_data, const std::vector< int > &axes) |
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template<typename In , typename Out > |
void | nnfw::cker::MeanQ8Asymm (const Shape &input_shape, const In *input_data, float input_scale, int32_t input_offset, const Shape &output_shape, Out *output_data, float output_scale, int32_t output_offset, const std::vector< int > &axes) |
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template<typename In , typename Out > |
void | nnfw::cker::MeanAxis1And2 (const Shape &input_shape, const In *input_data, const Shape &output_shape, Out *output_data) |
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