Function arm_nn_mean_f16

Function Documentation

arm_cmsis_nn_status arm_nn_mean_f16(const float16_t *input_data, const cmsis_nn_dims *input_dims, const cmsis_nn_dims *axis_dims, float16_t *output_data, const cmsis_nn_dims *output_dims)

Computes the mean of a float16 tensor along the specified axes.

Values are accumulated and divided in float32, then rounded once to float16. NaN and Inf propagate. Vector and scalar builds may differ in final ulps because float accumulation order differs. Builds at -Ofast (the shipped CMSIS_OPTIMIZATION_LEVEL) may additionally differ from lower optimization levels by 1 ulp for non-power-of-two reduction counts: -freciprocal-math turns the divide-by-count into a multiply-by-reciprocal, which rounds differently.

Unlike arm_reduce_sum_f16 (identical signature, null checks only), this kernel validates shapes and returns ARM_CMSIS_NN_ARG_ERROR when any input dimension is less than 1, when any output_dims entry differs from the input shape with the reduced axes collapsed to 1, or when the input element count or the reduction count does not fit in int32_t. output_data must not overlap input_data: each output element is written after reading its whole reduction set, so an aliased write can corrupt inputs still to be read.

Parameters:

  • input_data – [in] Pointer to input tensor

  • input_dims – [in] Input tensor dimensions (4D NHWC)

  • axis_dims – [in] 4D binary axis mask (non-zero = reduce that axis)

  • output_data – [out] Pointer to output tensor

  • output_dims – [in] Output tensor dimensions (reduced axes have size 1)

Returns:

ARM_CMSIS_NN_SUCCESS on success or ARM_CMSIS_NN_ARG_ERROR on invalid arguments.