Function arm_depthwise_conv_s16

Function Documentation

arm_cmsis_nn_status arm_depthwise_conv_s16(const cmsis_nn_context *ctx, const cmsis_nn_dw_conv_params *dw_conv_params, const cmsis_nn_per_channel_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 depthwise convolution function that doesn’t have any constraints on the input dimensions.

  • 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. exists if additional memory is. The caller is expected to clear the buffer, if applicable, for security reasons.

  • dw_conv_params – [in] Depthwise convolution parameters (e.g. strides, dilations, pads,…) conv_params->input_offset : Not used conv_params->output_offset : Not used

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

  • input_dims – [in] Input (activation) tensor dimensions. Format: [N, H, W, C_IN] Batch argument N is not used.

  • input_data – [in] Input (activation) data pointer. Data type: int8

  • filter_dims – [in] Filter tensor dimensions. Format: [1, H, W, C_OUT]

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

  • bias_dims – [in] Bias tensor dimensions. Format: [C_OUT]

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

  • output_dims – [in] Output tensor dimensions. Format: [N, H, W, C_OUT]

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

Returns:

The function returns ARM_CMSIS_NN_SUCCESS