Function arm_fully_connected_s16

Function Documentation

arm_cmsis_nn_status arm_fully_connected_s16(const cmsis_nn_context *ctx, const cmsis_nn_fc_params *fc_params, const cmsis_nn_per_tensor_quant_params *quant_params, const cmsis_nn_dims *input_dims, const int16_t *input_data, const cmsis_nn_dims *filter_dims, const int8_t *filter_data, const cmsis_nn_dims *bias_dims, const int64_t *bias_data, const cmsis_nn_dims *output_dims, int16_t *output_data)

Basic s16 Fully Connected function.

  • Supported framework: TensorFlow Lite

Parameters:

  • ctx – [inout] Function context (e.g. temporary buffer). Check the function definition file to see if an additional buffer is required. Optional function {API}_get_buffer_size() provides the buffer size if an additional buffer is required. The caller is expected to clear the buffer, if applicable, for security reasons.

  • fc_params – [in] Fully Connected layer parameters. fc_params->input_offset : 0 fc_params->filter_offset : 0 fc_params->output_offset : 0

  • quant_params – [in] Per-tensor quantization info. It contains the multiplier and shift value to be applied to the output tensor.

  • input_dims – [in] Input (activation) tensor dimensions. Format: [N, H, W, C_IN] Input dimension is taken as Nx(H * W * C_IN)

  • input_data – [in] Input (activation) data pointer. Data type: int16

  • filter_dims – [in] Two dimensional filter dimensions. Format: [N, C] N : accumulation depth and equals (H * W * C_IN) from input_dims C : output depth and equals C_OUT in output_dims H & W : Not used

  • filter_data – [in] Filter data pointer. Data type: int8

  • bias_dims – [in] Bias tensor dimensions. Format: [C_OUT] N, H, W : Not used

  • bias_data – [in] Bias data pointer. Data type: int64

  • output_dims – [in] Output tensor dimensions. Format: [N, C_OUT] N : Batches C_OUT : Output depth H & W : Not used.

  • output_data – [inout] Output data pointer. Data type: int16

Returns:

The function returns ARM_CMSIS_NN_SUCCESS