Function arm_nn_mat_mult_kernel_s8_s16

Function Documentation

int8_t *arm_nn_mat_mult_kernel_s8_s16(const int8_t *input_a, const int16_t *input_b, const uint16_t output_ch, const int32_t *out_shift, const int32_t *out_mult, const int32_t out_offset, const int16_t activation_min, const int16_t activation_max, const int32_t num_col_a, const int32_t aligned_num_col_a, const int32_t *const output_bias, int8_t *out_0)

Matrix-multiplication function for convolution with per-channel requantization.

Parameters:

  • input_a – [in] pointer to operand A

  • input_b – [in] pointer to operand B, always consists of 2 vectors.

  • output_ch – [in] number of rows of A

  • out_shift – [in] pointer to per output channel requantization shift parameter.

  • out_mult – [in] pointer to per output channel requantization multiplier parameter.

  • out_offset – [in] output tensor offset.

  • activation_min – [in] minimum value to clamp the output to. Range : int8

  • activation_max – [in] maximum value to clamp the output to. Range : int8

  • num_col_a – [in] number of columns of A

  • aligned_num_col_a – [in] number of columns of A aligned by 4

  • output_bias – [in] per output channel bias. Range : int32

  • out_0 – [inout] pointer to output

Returns:

The function returns one of the two

  1. The incremented output pointer for a successful operation or

  2. NULL if implementation is not available.

    This function does the matrix multiplication of weight matrix for all output channels with 2 columns from im2col and produces two elements/output_channel. The outputs are clamped in the range provided by activation min and max. Supported framework: TensorFlow Lite micro.