Function arm_svdf_s8

Function Documentation

arm_cmsis_nn_status arm_svdf_s8(const cmsis_nn_context *ctx, const cmsis_nn_context *input_ctx, const cmsis_nn_context *output_ctx, const cmsis_nn_svdf_params *svdf_params, const cmsis_nn_per_tensor_quant_params *input_quant_params, const cmsis_nn_per_tensor_quant_params *output_quant_params, const cmsis_nn_dims *input_dims, const int8_t *input_data, const cmsis_nn_dims *state_dims, int8_t *state_data, const cmsis_nn_dims *weights_feature_dims, const int8_t *weights_feature_data, const cmsis_nn_dims *weights_time_dims, const int8_t *weights_time_data, const cmsis_nn_dims *bias_dims, const int32_t *bias_data, const cmsis_nn_dims *output_dims, int8_t *output_data)

s8 SVDF function with 8 bit state tensor and 8 bit time weights

  1. Supported framework: TensorFlow Lite micro

Parameters:

  • ctx – [in] Precomputed per-feature-batch kernel sums, supplied by the caller. This is an input the function only reads, not scratch it fills: an allocated but unfilled buffer yields wrong output while still returning ARM_CMSIS_NN_SUCCESS. Mandatory on builds with the MVE extension (ARM_MATH_MVEI), where a NULL ctx->buf is diagnosed with ARM_CMSIS_NN_ARG_ERROR. Unused on every other build, where ctx->buf may be NULL. Sized by arm_svdf_s8_get_buffer_size(weights_feature_dims): weights_feature_dims->n * sizeof(int32_t) where the sums are used, 0 otherwise. Note this is weights_feature_dims->n, not a filter_dims->c - do not size this buffer with arm_fully_connected_s8_get_buffer_size(), which reads a different field and under-allocates. Fill it with arm_vector_sum_s8(ctx->buf, input_dims->h, weights_feature_dims->n, weights_feature_data, -svdf_params->input_offset, 0, NULL) so that entry j holds -input_offset * sum(weights_feature row j). The contents depend only on weights_feature_data and svdf_params->input_offset, so they may be computed once at load time and reused across calls until one of those changes. The buffer is specific to one layer’s weights and cannot be shared between layers. Do NOT clear this buffer between calls: zeroing it is indistinguishable from leaving it unfilled, and produces the silently wrong output described above. If it must be cleared for security reasons, clear it after the last call that uses it, and refill it before any further call.

  • input_ctx – [in]

    Scratch buffer written by this function, holding one int32_t accumulator per (input batch, feature batch). Written before it is read, so its contents on entry do not matter, but it is written on EVERY build, not only under MVE. Mandatory: a NULL buf is diagnosed with ARM_CMSIS_NN_ARG_ERROR on every build. Sized by arm_svdf_s8_input_ctx_get_buffer_size(input_dims,

    weights_feature_dims): input_dims->n * weights_feature_dims->n * sizeof(int32_t) bytes, the same figure on every build target. This function does not read input_ctx->size, so an undersized buffer is not diagnosed: query the sizer above and honour it. The caller is expected to clear the buffer, if applicable, for security reasons.

  • output_ctx – [in]

    Scratch buffer written by this function, holding one int32_t accumulator per (input batch, output unit). Written before it is read, so its contents on entry do not matter, but it is written on EVERY build, not only under MVE. Mandatory: a NULL buf is diagnosed with ARM_CMSIS_NN_ARG_ERROR on every build. Sized by arm_svdf_s8_output_ctx_get_buffer_size(svdf_params, input_dims,

    weights_feature_dims): input_dims->n * (weights_feature_dims->n / svdf_params->rank) * sizeof(int32_t) bytes, truncating division, the same figure on every build target. This function does not read output_ctx->size, so an undersized buffer is not diagnosed: query the sizer above and honour it. The caller is expected to clear the buffer, if applicable, for security reasons.

  • svdf_params – [in] SVDF Parameters Range of svdf_params->input_offset : [-128, 127] Range of svdf_params->output_offset : [-128, 127]

  • input_quant_params – [in] Input quantization parameters

  • output_quant_params – [in] Output quantization parameters

  • input_dims – [in] Input tensor dimensions

  • input_data – [in] Pointer to input tensor

  • state_dims – [in] State tensor dimensions

  • state_data – [in] Pointer to state tensor

  • weights_feature_dims – [in] Weights (feature) tensor dimensions

  • weights_feature_data – [in] Pointer to the weights (feature) tensor

  • weights_time_dims – [in] Weights (time) tensor dimensions

  • weights_time_data – [in] Pointer to the weights (time) tensor

  • bias_dims – [in] Bias tensor dimensions

  • bias_data – [in] Pointer to bias tensor

  • output_dims – [in] Output tensor dimensions

  • output_data – [out] Pointer to the output tensor

Returns:

The function returns either ARM_CMSIS_NN_ARG_ERROR if argument constraints fail. or, ARM_CMSIS_NN_SUCCESS on successful completion.