Function arm_convolve_s8

Function Documentation

arm_cmsis_nn_status arm_convolve_s8(const cmsis_nn_context *ctx, const cmsis_nn_context *weight_sum_ctx, const cmsis_nn_conv_params *conv_params, const cmsis_nn_per_channel_quant_params *quant_params, const cmsis_nn_dims *input_dims, const int8_t *input_data, const cmsis_nn_dims *filter_dims, const int8_t *filter_data, const cmsis_nn_dims *bias_dims, const int32_t *bias_data, const cmsis_nn_dims *upscale_dims, const cmsis_nn_dims *output_dims, int8_t *output_data)

Basic s8 convolution function.

  1. Supported framework: TensorFlow Lite micro

  2. Additional memory is required for optimization. Refer to argument ‘ctx’ for details.

Parameters:

  • ctx – [inout] Function context that contains the additional buffer if required by the function. arm_convolve_s8_get_buffer_size will return the buffer_size if required. The caller is expected to clear the buffer, if applicable, for security reasons.

  • weight_sum_ctx – [inout] Function context that contains the weight sum buffer if required by the function.

  • conv_params – [in] Convolution parameters (e.g. strides, dilations, pads,…). Range of conv_params->input_offset : [-127, 128] Range of conv_params->output_offset : [-128, 127]

  • 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]

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

  • filter_dims – [in] Filter tensor dimensions. Format: [C_OUT, HK, WK, CK] where HK, WK and CK are the spatial filter dimensions. CK != C_IN is used for grouped convolution, in which case the required conditions are C_IN = N * CK and C_OUT = N * M for N groups of size M.

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

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

  • bias_data – [in] Optional bias data pointer. Data type: int32

  • upscale_dims – [in] Upscale tensor dimensions for transpose. Format: [H_UP, W_UP]

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

  • output_data – [out] Output data pointer. Data type: int8

Returns:

The function returns ARM_CMSIS_NN_SUCCESS if successful or ARM_CMSIS_NN_ARG_ERROR if incorrect arguments or ARM_CMSIS_NN_NO_IMPL_ERROR