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diff --git a/Drivers/CMSIS/NN/Include/arm_nnsupportfunctions.h b/Drivers/CMSIS/NN/Include/arm_nnsupportfunctions.h new file mode 100644 index 0000000..4b50564 --- /dev/null +++ b/Drivers/CMSIS/NN/Include/arm_nnsupportfunctions.h @@ -0,0 +1,1186 @@ +/* + * Copyright (C) 2010-2022 Arm Limited or its affiliates. + * + * SPDX-License-Identifier: Apache-2.0 + * + * Licensed under the Apache License, Version 2.0 (the License); you may + * not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an AS IS BASIS, WITHOUT + * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +/* ---------------------------------------------------------------------- + * Project: CMSIS NN Library + * Title: arm_nnsupportfunctions.h + * Description: Public header file of support functions for CMSIS NN Library + * + * $Date: 19. April 2022 + * $Revision: V.7.0.1 + * + * Target Processor: Cortex-M CPUs + * -------------------------------------------------------------------- */ + +#ifndef _ARM_NNSUPPORTFUNCTIONS_H_ +#define _ARM_NNSUPPORTFUNCTIONS_H_ + +#include "arm_nn_math_types.h" +#include "arm_nn_types.h" + +#include <stdbool.h> + +#ifdef __cplusplus +extern "C" { +#endif + +#define LEFT_SHIFT(_shift) (_shift > 0 ? _shift : 0) +#define RIGHT_SHIFT(_shift) (_shift > 0 ? 0 : -_shift) +#define MASK_IF_ZERO(x) (x) == 0 ? ~0 : 0 +#define MASK_IF_NON_ZERO(x) (x) != 0 ? ~0 : 0 +#define SELECT_USING_MASK(mask, a, b) ((mask) & (a)) ^ (~(mask) & (b)) + +#define MAX(A, B) ((A) > (B) ? (A) : (B)) +#define MIN(A, B) ((A) < (B) ? (A) : (B)) +#define CLAMP(x, h, l) MAX(MIN((x), (h)), (l)) +#define REDUCE_MULTIPLIER(_mult) ((_mult < 0x7FFF0000) ? ((_mult + (1 << 15)) >> 16) : 0x7FFF) + +/** + * @brief definition to pack four 8 bit values. + */ +#define PACK_Q7x4_32x1(v0, v1, v2, v3) \ + ((((int32_t)(v0) << 0) & (int32_t)0x000000FF) | (((int32_t)(v1) << 8) & (int32_t)0x0000FF00) | \ + (((int32_t)(v2) << 16) & (int32_t)0x00FF0000) | (((int32_t)(v3) << 24) & (int32_t)0xFF000000)) + +/** + * @brief Union for SIMD access of q31/q15/q7 types + */ +union arm_nnword +{ + q31_t word; + /**< q31 type */ + q15_t half_words[2]; + /**< q15 type */ + q7_t bytes[4]; + /**< q7 type */ +}; + +/** + * @brief Union for data type long long + */ +struct arm_nn_double +{ + uint32_t low; + int32_t high; +}; + +union arm_nn_long_long +{ + int64_t long_long; + struct arm_nn_double word; +}; + +/** + * @defgroup nndata_convert Neural Network Data Conversion Functions + * + * Perform data type conversion in-between neural network operations + * + */ + +/** + * @brief Converts the elements of the q7 vector to q15 vector without left-shift + * @param[in] *pSrc points to the q7 input vector + * @param[out] *pDst points to the q15 output vector + * @param[in] blockSize length of the input vector + * + */ +void arm_q7_to_q15_no_shift(const q7_t *pSrc, q15_t *pDst, uint32_t blockSize); + +/** + * @brief Non-saturating addition of elements of a q7 vector + * @param[in] *input Pointer to the q7 input vector + * @param[out] *output Pointer to the q31 output variable. + * @param[in] block_size length of the input vector + * \par Description: + * + * 2^24 samples can be added without saturating the result. + * + * The equation used for the conversion process is: + * + * <pre> + * sum = input[0] + input[1] + .. + input[block_size -1] + * </pre> + * + * */ +void arm_nn_add_q7(const q7_t *input, q31_t *output, uint32_t block_size); + +/** + * @brief Converts the elements of the q7 vector to reordered q15 vector without left-shift + * @param[in] *pSrc points to the q7 input vector + * @param[out] *pDst points to the q15 output vector + * @param[in] blockSize length of the input vector + * @return none. + * + */ +void arm_q7_to_q15_reordered_no_shift(const q7_t *pSrc, q15_t *pDst, uint32_t blockSize); + +/** + * @brief Converts the elements from a q7 vector to a q15 vector with an added offset + * @param[in] src pointer to the q7 input vector + * @param[out] dst pointer to the q15 output vector + * @param[in] block_size length of the input vector + * @param[in] offset q7 offset to be added to each input vector element. + * + * \par Description: + * + * The equation used for the conversion process is: + * + * <pre> + * dst[n] = (q15_t) src[n] + offset; 0 <= n < block_size. + * </pre> + * + */ +void arm_q7_to_q15_with_offset(const q7_t *src, q15_t *dst, uint32_t block_size, q15_t offset); + +/** + * @brief Converts the elements of the q7 vector to reordered q15 vector with an added offset + * @param[in] src pointer to the q7 input vector + * @param[out] dst pointer to the q15 output vector + * @param[in] block_size length of the input vector + * @param[in] offset offset to be added to each input vector element. + * @return none. + * + * @details This function does the q7 to q15 expansion with re-ordering of bytes. Re-ordering is a consequence of + * the sign extension intrinsic(DSP extension). The tail (i.e., last (N % 4) elements) retains its + * original order. + * + */ +void arm_q7_to_q15_reordered_with_offset(const q7_t *src, q15_t *dst, uint32_t block_size, q15_t offset); + +/** + * @brief Converts the elements from a q7 vector and accumulate to a q15 vector + * @param[in] *src points to the q7 input vector + * @param[out] *dst points to the q15 output vector + * @param[in] block_size length of the input vector + * + * \par Description: + * + * The equation used for the conversion process is: + * + * <pre> + * dst[n] += (q15_t) src[n] ; 0 <= n < block_size. + * </pre> + * + */ +void arm_nn_accumulate_q7_to_q15(q15_t *dst, const q7_t *src, uint32_t block_size); + +/** + * @brief Depthwise conv on an im2col buffer where the input channel equals output channel. + * @param[in] row pointer to row + * @param[in] col pointer to im2col buffer, always consists of 2 columns. + * @param[in] num_ch number of channels + * @param[in] out_shift pointer to per output channel requantization shift parameter. + * @param[in] out_mult pointer to per output channel requantization multiplier parameter. + * @param[in] out_offset output tensor offset. + * @param[in] activation_min minimum value to clamp the output to. Range : int8 + * @param[in] activation_max maximum value to clamp the output to. Range : int8 + * @param[in] kernel_size number of elements in one column. + * @param[in] output_bias per output channel bias. Range : int32 + * @param[out] out pointer to output + * @return The function returns one of the two + * 1. The incremented output pointer for a successful operation or + * 2. NULL if implementation is not available. + * + * @details Supported framework: TensorFlow Lite micro. + */ +q7_t *arm_nn_depthwise_conv_s8_core(const q7_t *row, + const q15_t *col, + const uint16_t num_ch, + const int32_t *out_shift, + const int32_t *out_mult, + const int32_t out_offset, + const int32_t activation_min, + const int32_t activation_max, + const uint16_t kernel_size, + const int32_t *const output_bias, + q7_t *out); + +/** + * @brief General Matrix-multiplication function with per-channel requantization. + * @param[in] input_row pointer to row operand + * @param[in] input_col pointer to col operand + * @param[in] output_ch number of rows of input_row + * @param[in] col_batches number of column batches. Range: 1 to 4 + * @param[in] output_shift pointer to per output channel requantization shift parameter. + * @param[in] output_mult pointer to per output channel requantization multiplier parameter. + * @param[in] out_offset output tensor offset. + * @param[in] col_offset input tensor(col) offset. + * @param[in] row_offset kernel offset(row). Not used. + * @param[in] out_activation_min minimum value to clamp the output to. Range : int8 + * @param[in] out_activation_max maximum value to clamp the output to. Range : int8 + * @param[in] row_len number of elements in each row + * @param[in] bias per output channel bias. Range : int32 + * @param[in,out] out pointer to output + * @return The function returns one of the two + * 1. The incremented output pointer for a successful operation or + * 2. NULL if implementation is not available. + * + * @details Supported framework: TensorFlow Lite + */ +q7_t *arm_nn_mat_mult_s8(const q7_t *input_row, + const q7_t *input_col, + const uint16_t output_ch, + const uint16_t col_batches, + const int32_t *output_shift, + const int32_t *output_mult, + const int32_t out_offset, + const int32_t col_offset, + const int32_t row_offset, + const int16_t out_activation_min, + const int16_t out_activation_max, + const uint16_t row_len, + const int32_t *const bias, + q7_t *out); +/** + * @brief Matrix-multiplication function for convolution with per-channel requantization for 16 bits convolution. + * @param[in] input_a pointer to operand A + * @param[in] input_b pointer to operand B, always consists of 2 vectors. + * @param[in] output_ch number of rows of A + * @param[in] out_shift pointer to per output channel requantization shift parameter. + * @param[in] out_mult pointer to per output channel requantization multiplier parameter. + * @param[in] activation_min minimum value to clamp the output to. Range : int16 + * @param[in] activation_max maximum value to clamp the output to. Range : int16 + * @param[in] num_col_a number of columns of A + * @param[in] output_bias per output channel bias. Range : int64 + * @param[in,out] out_0 pointer to output + * @return The function returns one of the two + * 1. The incremented output pointer for a successful operation or + * 2. NULL if implementation is not available. + * + * @details 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. + */ +q15_t *arm_nn_mat_mult_kernel_s16(const q7_t *input_a, + const q15_t *input_b, + const int32_t output_ch, + const int32_t *out_shift, + const int32_t *out_mult, + const int16_t activation_min, + const int16_t activation_max, + const int32_t num_col_a, + const int64_t *const output_bias, + q15_t *out_0); +/** + * @brief General Matrix-multiplication without requantization for one row & one column + * @param[in] row_elements number of row elements + * @param[in] row_base pointer to row operand + * @param[in] col_base pointer to col operand + * @param[out] sum_col pointer to store sum of column elements + * @param[out] output pointer to store result of multiply-accumulate + * @return The function returns the multiply-accumulated result of the row by column. + * + * @details Pseudo-code + * *output = 0 + * sum_col = 0 + * for (i = 0; i < row_elements; i++) + * *output += row_base[i] * col_base[i] + * sum_col += col_base[i] + * + */ +arm_status arm_nn_mat_mul_core_1x_s8(int32_t row_elements, + const int8_t *row_base, + const int8_t *col_base, + int32_t *const sum_col, + int32_t *const output); + +/** + * @brief Matrix-multiplication with requantization & activation function for four rows and one column + * @param[in] row_elements number of row elements + * @param[in] offset offset between rows. Can be the same as row_elements. + * For e.g, in a 1x1 conv scenario with stride as 1. + * @param[in] row_base pointer to row operand + * @param[in] col_base pointer to col operand + * @param[in] out_ch Number of output channels + * @param[in] conv_params Pointer to convolution parameters like offsets and activation values + * @param[in] quant_params Pointer to per-channel quantization parameters + * @param[in] bias Pointer to per-channel bias + * @param[out] output Pointer to output where int8 results are stored. + * + * @return The function returns the updated output pointer or NULL if implementation is not available. + * + * @details Compliant to TFLM int8 specification. MVE implementation only + */ +int8_t *arm_nn_mat_mul_core_4x_s8(const int32_t row_elements, + const int32_t offset, + const int8_t *row_base, + const int8_t *col_base, + const int32_t out_ch, + const cmsis_nn_conv_params *conv_params, + const cmsis_nn_per_channel_quant_params *quant_params, + const int32_t *bias, + int8_t *output); + +/** + * @brief General Matrix-multiplication function with per-channel requantization. + * This function assumes: + * - LHS input matrix NOT transposed (nt) + * - RHS input matrix transposed (t) + * + * @note This operation also performs the broadcast bias addition before the requantization + * + * @param[in] lhs Pointer to the LHS input matrix + * @param[in] rhs Pointer to the RHS input matrix + * @param[in] bias Pointer to the bias vector. The length of this vector is equal to the number of + * output columns (or RHS input rows) + * @param[out] dst Pointer to the output matrix with "m" rows and "n" columns + * @param[in] dst_multipliers Pointer to the multipliers vector needed for the per-channel requantization. + * The length of this vector is equal to the number of output columns (or RHS input + * rows) + * @param[in] dst_shifts Pointer to the shifts vector needed for the per-channel requantization. The length + * of this vector is equal to the number of output columns (or RHS input rows) + * @param[in] lhs_rows Number of LHS input rows + * @param[in] rhs_rows Number of RHS input rows + * @param[in] rhs_cols Number of LHS/RHS input columns + * @param[in] lhs_offset Offset to be applied to the LHS input value + * @param[in] dst_offset Offset to be applied the output result + * @param[in] activation_min Minimum value to clamp down the output. Range : int8 + * @param[in] activation_max Maximum value to clamp up the output. Range : int8 + * + * @return The function returns <code>ARM_MATH_SUCCESS</code> + * + */ +arm_status arm_nn_mat_mult_nt_t_s8(const q7_t *lhs, + const q7_t *rhs, + const q31_t *bias, + q7_t *dst, + const int32_t *dst_multipliers, + const int32_t *dst_shifts, + const int32_t lhs_rows, + const int32_t rhs_rows, + const int32_t rhs_cols, + const int32_t lhs_offset, + const int32_t dst_offset, + const int32_t activation_min, + const int32_t activation_max); + +/** + * @brief s8 Vector by Matrix (transposed) multiplication + * + * @param[in] lhs Input left-hand side vector + * @param[in] rhs Input right-hand side matrix (transposed) + * @param[in] bias Input bias + * @param[out] dst Output vector + * @param[in] lhs_offset Offset to be added to the input values of the left-hand side vector. + * Range: -127 to 128 + * @param[in] rhs_offset Not used + * @param[in] dst_offset Offset to be added to the output values. Range: -127 to 128 + * @param[in] dst_multiplier Output multiplier + * @param[in] dst_shift Output shift + * @param[in] rhs_cols Number of columns in the right-hand side input matrix + * @param[in] rhs_rows Number of rows in the right-hand side input matrix + * @param[in] activation_min Minimum value to clamp the output to. Range: int8 + * @param[in] activation_max Maximum value to clamp the output to. Range: int8 + * @param[in] address_offset Memory position offset for dst. First output is stored at 'dst', the + * second at 'dst + address_offset' and so on. Default value is typically 1. + * + * @return The function returns <code>ARM_MATH_SUCCESS</code> + * + */ +arm_status arm_nn_vec_mat_mult_t_s8(const q7_t *lhs, + const q7_t *rhs, + const q31_t *bias, + q7_t *dst, + const int32_t lhs_offset, + const int32_t rhs_offset, + const int32_t dst_offset, + const int32_t dst_multiplier, + const int32_t dst_shift, + const int32_t rhs_cols, + const int32_t rhs_rows, + const int32_t activation_min, + const int32_t activation_max, + const int32_t address_offset); + +/** + * @brief s16 Vector by Matrix (transposed) multiplication + * + * @param[in] lhs Input left-hand side vector + * @param[in] rhs Input right-hand side matrix (transposed) + * @param[in] bias Input bias + * @param[out] dst Output vector + * @param[in] dst_multiplier Output multiplier + * @param[in] dst_shift Output shift + * @param[in] rhs_cols Number of columns in the right-hand side input matrix + * @param[in] rhs_rows Number of rows in the right-hand side input matrix + * @param[in] activation_min Minimum value to clamp the output to. Range: int16 + * @param[in] activation_max Maximum value to clamp the output to. Range: int16 + * + * @return The function returns <code>ARM_MATH_SUCCESS</code> + * + */ +arm_status arm_nn_vec_mat_mult_t_s16(const q15_t *lhs, + const q7_t *rhs, + const q63_t *bias, + q15_t *dst, + const int32_t dst_multiplier, + const int32_t dst_shift, + const int32_t rhs_cols, + const int32_t rhs_rows, + const int32_t activation_min, + const int32_t activation_max); + +/** + * @brief s8 Vector by Matrix (transposed) multiplication with s16 output + * + * @param[in] lhs Input left-hand side vector + * @param[in] rhs Input right-hand side matrix (transposed) + * @param[out] dst Output vector + * @param[in] lhs_offset Offset to be added to the input values of the left-hand side + * vector. Range: -127 to 128 + * @param[in] rhs_offset Not used + * @param[in] scatter_offset Address offset for dst. First output is stored at 'dst', the + * second at 'dst + scatter_offset' and so on. + * @param[in] dst_multiplier Output multiplier + * @param[in] dst_shift Output shift + * @param[in] rhs_cols Number of columns in the right-hand side input matrix + * @param[in] rhs_rows Number of rows in the right-hand side input matrix + * @param[in] activation_min Minimum value to clamp the output to. Range: int16 + * @param[in] activation_max Maximum value to clamp the output to. Range: int16 + * + * @return The function returns <code>ARM_MATH_SUCCESS</code> + * + */ +arm_status arm_nn_vec_mat_mult_t_svdf_s8(const q7_t *lhs, + const q7_t *rhs, + q15_t *dst, + const int32_t lhs_offset, + const int32_t rhs_offset, + const int32_t scatter_offset, + const int32_t dst_multiplier, + const int32_t dst_shift, + const int32_t rhs_cols, + const int32_t rhs_rows, + const int32_t activation_min, + const int32_t activation_max); + +/** + * @brief Depthwise convolution of transposed rhs matrix with 4 lhs matrices. To be used in padded cases where + * the padding is -lhs_offset(Range: int8). Dimensions are the same for lhs and rhs. + * + * @param[in] lhs Input left-hand side matrix + * @param[in] rhs Input right-hand side matrix (transposed) + * @param[in] lhs_offset LHS matrix offset(input offset). Range: -127 to 128 + * @param[in] num_ch Number of channels in LHS/RHS + * @param[in] out_shift Per channel output shift. Length of vector is equal to number of channels + * @param[in] out_mult Per channel output multiplier. Length of vector is equal to number of channels + * @param[in] out_offset Offset to be added to the output values. Range: -127 to 128 + * @param[in] activation_min Minimum value to clamp the output to. Range: int8 + * @param[in] activation_max Maximum value to clamp the output to. Range: int8 + * @param[in] row_x_col (row_dimension * col_dimension) of LHS/RHS matrix + * @param[in] output_bias Per channel output bias. Length of vector is equal to number of channels + * @param[in] out Output pointer + * + * @return The function returns one of the two + * - Updated output pointer if an implementation is available + * - NULL if no implementation is available. + * + * @note If number of channels is not a multiple of 4, upto 3 elements outside the boundary will be read + * out for the following. + * - Output shift + * - Output multiplier + * - Output bias + * - rhs + */ +q7_t *arm_nn_depthwise_conv_nt_t_padded_s8(const q7_t *lhs, + const q7_t *rhs, + const int32_t lhs_offset, + const uint16_t num_ch, + const int32_t *out_shift, + const int32_t *out_mult, + const int32_t out_offset, + const int32_t activation_min, + const int32_t activation_max, + const uint16_t row_x_col, + const int32_t *const output_bias, + q7_t *out); + +/** + * @brief Depthwise convolution of transposed rhs matrix with 4 lhs matrices. To be used in non-padded cases. + * Dimensions are the same for lhs and rhs. + * + * @param[in] lhs Input left-hand side matrix + * @param[in] rhs Input right-hand side matrix (transposed) + * @param[in] lhs_offset LHS matrix offset(input offset). Range: -127 to 128 + * @param[in] num_ch Number of channels in LHS/RHS + * @param[in] out_shift Per channel output shift. Length of vector is equal to number of channels. + * @param[in] out_mult Per channel output multiplier. Length of vector is equal to number of channels. + * @param[in] out_offset Offset to be added to the output values. Range: -127 to 128 + * @param[in] activation_min Minimum value to clamp the output to. Range: int8 + * @param[in] activation_max Maximum value to clamp the output to. Range: int8 + * @param[in] row_x_col (row_dimension * col_dimension) of LHS/RHS matrix + * @param[in] output_bias Per channel output bias. Length of vector is equal to number of channels. + * @param[in] out Output pointer + * + * @return The function returns one of the two + * - Updated output pointer if an implementation is available + * - NULL if no implementation is available. + * + * @note If number of channels is not a multiple of 4, upto 3 elements outside the boundary will be read + * out for the following. + * - Output shift + * - Output multiplier + * - Output bias + * - rhs + */ +q7_t *arm_nn_depthwise_conv_nt_t_s8(const q7_t *lhs, + const q7_t *rhs, + const int32_t lhs_offset, + const uint16_t num_ch, + const int32_t *out_shift, + const int32_t *out_mult, + const int32_t out_offset, + const int32_t activation_min, + const int32_t activation_max, + const uint16_t row_x_col, + const int32_t *const output_bias, + q7_t *out); + +/** + *@brief Matrix-multiplication function for convolution with reordered columns + *@param[in] pA pointer to operand A + *@param[in] pInBuffer pointer to operand B, always conssists of 2 vectors + *@param[in] ch_im_out numRow of A + *@param[in] numCol_A numCol of A + *@param[in] bias_shift amount of left-shift for bias + *@param[in] out_shift amount of right-shift for output + *@param[in] bias the bias + *@param[in,out] pOut pointer to output + *@return The function returns the incremented output pointer + * + *@details This function assumes that data in pInBuffer are reordered + */ +q7_t *arm_nn_mat_mult_kernel_q7_q15_reordered(const q7_t *pA, + const q15_t *pInBuffer, + const uint16_t ch_im_out, + const uint16_t numCol_A, + const uint16_t bias_shift, + const uint16_t out_shift, + const q7_t *bias, + q7_t *pOut); + +/** + @brief Read 2 q15 elements and post increment pointer. + @param[in] in_q15 Pointer to pointer that holds address of input. + @return q31 value + */ +__STATIC_FORCEINLINE q31_t arm_nn_read_q15x2_ia(const q15_t **in_q15) +{ + q31_t val; + + memcpy(&val, *in_q15, 4); + *in_q15 += 2; + + return (val); +} + +/** + @brief Read 4 q7 from q7 pointer and post increment pointer. + @param[in] in_q7 Pointer to pointer that holds address of input. + @return q31 value + */ +__STATIC_FORCEINLINE q31_t arm_nn_read_q7x4_ia(const q7_t **in_q7) +{ + q31_t val; + memcpy(&val, *in_q7, 4); + *in_q7 += 4; + + return (val); +} + +/** + @brief Read 2 q15 from q15 pointer. + @param[in] in_q15 pointer to address of input. + @return q31 value + */ +__STATIC_FORCEINLINE q31_t arm_nn_read_q15x2(const q15_t *in_q15) +{ + q31_t val; + memcpy(&val, in_q15, 4); + + return (val); +} + +/** + @brief Read 4 q7 values. + @param[in] in_q7 pointer to address of input. + @return q31 value + */ +__STATIC_FORCEINLINE q31_t arm_nn_read_q7x4(const q7_t *in_q7) +{ + q31_t val; + memcpy(&val, in_q7, 4); + + return (val); +} + +/** + @brief Write four q7 to q7 pointer and increment pointer afterwards. + @param[in] in Double pointer to input value + @param[in] value Four bytes to copy + */ +__STATIC_FORCEINLINE void arm_nn_write_q7x4_ia(q7_t **in, q31_t value) +{ + memcpy(*in, &value, 4); + *in += 4; +} + +/** + * @brief memset optimized for MVE + * @param[in, out] dst Destination pointer + * @param[in] val Value to set + * @param[in] block_size Number of bytes to copy. + * + */ +__STATIC_FORCEINLINE void arm_memset_q7(q7_t *dst, const q7_t val, uint32_t block_size) +{ +#if defined(ARM_MATH_MVEI) + __asm volatile(" vdup.8 q0, %[set_val] \n" + " wlstp.8 lr, %[cnt], 1f \n" + "2: \n" + " vstrb.8 q0, [%[in]], #16 \n" + " letp lr, 2b \n" + "1: \n" + : [ in ] "+r"(dst) + : [ cnt ] "r"(block_size), [ set_val ] "r"(val) + : "q0", "memory", "r14"); +#else + memset(dst, val, block_size); +#endif +} + +#if defined(ARM_MATH_DSP) + +/** + * @brief read and expand one q7 word into two q15 words + */ + +__STATIC_FORCEINLINE const q7_t *read_and_pad(const q7_t *source, q31_t *out1, q31_t *out2) +{ + q31_t inA = arm_nn_read_q7x4_ia(&source); + q31_t inAbuf1 = __SXTB16_RORn((uint32_t)inA, 8); + q31_t inAbuf2 = __SXTB16(inA); + +#ifndef ARM_MATH_BIG_ENDIAN + *out2 = (int32_t)(__PKHTB(inAbuf1, inAbuf2, 16)); + *out1 = (int32_t)(__PKHBT(inAbuf2, inAbuf1, 16)); +#else + *out1 = (int32_t)(__PKHTB(inAbuf1, inAbuf2, 16)); + *out2 = (int32_t)(__PKHBT(inAbuf2, inAbuf1, 16)); +#endif + + return source; +} + +/** + * @brief read and expand one q7 word into two q15 words with reordering + */ + +__STATIC_FORCEINLINE const q7_t *read_and_pad_reordered(const q7_t *source, q31_t *out1, q31_t *out2) +{ + q31_t inA = arm_nn_read_q7x4_ia(&source); +#ifndef ARM_MATH_BIG_ENDIAN + *out2 = __SXTB16(__ROR((uint32_t)inA, 8)); + *out1 = __SXTB16(inA); +#else + *out1 = __SXTB16(__ROR((uint32_t)inA, 8)); + *out2 = __SXTB16(inA); +#endif + + return source; +} + +/** + * @brief read and expand one q7 word into two q15 words with reordering and add an offset + */ +__STATIC_FORCEINLINE const q7_t * +read_and_pad_reordered_with_offset(const q7_t *source, q31_t *out1, q31_t *out2, q31_t offset) +{ + q31_t inA = arm_nn_read_q7x4_ia(&source); + +#ifndef ARM_MATH_BIG_ENDIAN + *out2 = __SXTB16(__ROR((uint32_t)inA, 8)); + *out1 = __SXTB16(inA); +#else + *out1 = __SXTB16(__ROR((uint32_t)inA, 8)); + *out2 = __SXTB16(inA); +#endif + *out1 = __QADD16(*out1, offset); + *out2 = __QADD16(*out2, offset); + + return source; +} + +#endif + +/** + * @defgroup NNBasicMath Basic Math Functions for Neural Network Computation + * + * Basic Math Functions for Neural Network Computation + * + */ + +/** + * @brief q7 vector multiplication with variable output shifts + * @param[in] *pSrcA pointer to the first input vector + * @param[in] *pSrcB pointer to the second input vector + * @param[out] *pDst pointer to the output vector + * @param[in] out_shift amount of right-shift for output + * @param[in] blockSize number of samples in each vector + * @return none. + * + * <b>Scaling and Overflow Behavior:</b> + * \par + * The function uses saturating arithmetic. + * Results outside of the allowable q15 range [0x8000 0x7FFF] will be saturated. + */ + +void arm_nn_mult_q15(q15_t *pSrcA, q15_t *pSrcB, q15_t *pDst, const uint16_t out_shift, uint32_t blockSize); + +/** + * @brief q7 vector multiplication with variable output shifts + * @param[in] *pSrcA pointer to the first input vector + * @param[in] *pSrcB pointer to the second input vector + * @param[out] *pDst pointer to the output vector + * @param[in] out_shift amount of right-shift for output + * @param[in] blockSize number of samples in each vector + * @return none. + * + * <b>Scaling and Overflow Behavior:</b> + * \par + * The function uses saturating arithmetic. + * Results outside of the allowable q7 range [0x80 0x7F] will be saturated. + */ + +void arm_nn_mult_q7(q7_t *pSrcA, q7_t *pSrcB, q7_t *pDst, const uint16_t out_shift, uint32_t blockSize); + +/** + * @brief Matrix-multiplication function for convolution with per-channel requantization. + * @param[in] input_a pointer to operand A + * @param[in] input_b pointer to operand B, always consists of 2 vectors. + * @param[in] output_ch number of rows of A + * @param[in] out_shift pointer to per output channel requantization shift parameter. + * @param[in] out_mult pointer to per output channel requantization multiplier parameter. + * @param[in] out_offset output tensor offset. + * @param[in] activation_min minimum value to clamp the output to. Range : int8 + * @param[in] activation_max maximum value to clamp the output to. Range : int8 + * @param[in] num_col_a number of columns of A + * @param[in] output_bias per output channel bias. Range : int32 + * @param[in,out] out_0 pointer to output + * @return The function returns one of the two + * 1. The incremented output pointer for a successful operation or + * 2. NULL if implementation is not available. + * + * @details 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. + */ +q7_t *arm_nn_mat_mult_kernel_s8_s16(const q7_t *input_a, + const q15_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 uint16_t num_col_a, + const int32_t *const output_bias, + q7_t *out_0); + +/** + * @brief Common softmax function for s8 input and s8 or s16 output + * @param[in] input Pointer to the input tensor + * @param[in] num_rows Number of rows in the input tensor + * @param[in] row_size Number of elements in each input row + * @param[in] mult Input quantization multiplier + * @param[in] shift Input quantization shift within the range [0, 31] + * @param[in] diff_min Minimum difference with max in row. Used to check if + * the quantized exponential operation can be performed + * @param[in] int16_output Indicating s8 output if 0 else s16 output + * @param[out] output Pointer to the output tensor + * + * @note Supported framework: TensorFlow Lite micro (bit-accurate) + * + */ +void arm_nn_softmax_common_s8(const int8_t *input, + const int32_t num_rows, + const int32_t row_size, + const int32_t mult, + const int32_t shift, + const int32_t diff_min, + const bool int16_output, + void *output); + +/** + * @brief macro for adding rounding offset + */ +#ifndef ARM_NN_TRUNCATE +#define NN_ROUND(out_shift) ((0x1 << out_shift) >> 1) +#else +#define NN_ROUND(out_shift) 0 +#endif + +// Macros for shortening quantization functions' names and avoid long lines +#define MUL_SAT(a, b) arm_nn_doubling_high_mult((a), (b)) +#define MUL_SAT_MVE(a, b) arm_doubling_high_mult_mve_32x4((a), (b)) +#define MUL_POW2(a, b) arm_nn_mult_by_power_of_two((a), (b)) + +#define DIV_POW2(a, b) arm_nn_divide_by_power_of_two((a), (b)) +#define DIV_POW2_MVE(a, b) arm_divide_by_power_of_two_mve((a), (b)) + +#define EXP_ON_NEG(x) arm_nn_exp_on_negative_values((x)) +#define ONE_OVER1(x) arm_nn_one_over_one_plus_x_for_x_in_0_1((x)) + +/** + * @brief Saturating doubling high multiply. Result matches + * NEON instruction VQRDMULH. + * @param[in] m1 Multiplicand. Range: {NN_Q31_MIN, NN_Q31_MAX} + * @param[in] m2 Multiplier. Range: {NN_Q31_MIN, NN_Q31_MAX} + * @return Result of multiplication. + * + */ +__STATIC_FORCEINLINE q31_t arm_nn_doubling_high_mult(const q31_t m1, const q31_t m2) +{ + q31_t result = 0; + // Rounding offset to add for a right shift of 31 + q63_t mult = 1 << 30; + + if ((m1 < 0) ^ (m2 < 0)) + { + mult = 1 - mult; + } + // Gets resolved as a SMLAL instruction + mult = mult + (q63_t)m1 * m2; + + // Utilize all of the upper 32 bits. This is the doubling step + // as well. + result = (int32_t)(mult / (1ll << 31)); + + if ((m1 == m2) && (m1 == (int32_t)NN_Q31_MIN)) + { + result = NN_Q31_MAX; + } + return result; +} + +/** + * @brief Doubling high multiply without saturation. This is intended + * for requantization where the scale is a positive integer + * + * @param[in] m1 Multiplicand. Range: {NN_Q31_MIN, NN_Q31_MAX} + * @param[in] m2 Multiplier Range: {NN_Q31_MIN, NN_Q31_MAX} + * @return Result of multiplication. + * @note The result of this matches that of neon instruction + * VQRDMULH for m1 in range {NN_Q31_MIN, NN_Q31_MAX} and m2 in + * range {NN_Q31_MIN + 1, NN_Q31_MAX}. Saturation occurs when + * m1 equals m2 equals NN_Q31_MIN and that is not handled by + * this function. + * + */ +__STATIC_FORCEINLINE q31_t arm_nn_doubling_high_mult_no_sat(const q31_t m1, const q31_t m2) +{ + q31_t result = 0; + union arm_nn_long_long mult; + + // Rounding offset to add for a right shift of 31 + mult.word.low = 1 << 30; + mult.word.high = 0; + + // Gets resolved as a SMLAL instruction + mult.long_long = mult.long_long + (q63_t)m1 * m2; + + // Utilize all of the upper 32 bits. This is the doubling step + // as well. + result = (int32_t)(mult.long_long >> 31); + + return result; +} + +/** + * @brief Rounding divide by power of two. + * @param[in] dividend - Dividend + * @param[in] exponent - Divisor = power(2, exponent) + * Range: [0, 31] + * @return Rounded result of division. Midpoint is rounded away from zero. + * + */ +__STATIC_FORCEINLINE q31_t arm_nn_divide_by_power_of_two(const q31_t dividend, const q31_t exponent) +{ + q31_t result = 0; + const q31_t remainder_mask = (1 << exponent) - 1; + int32_t remainder = remainder_mask & dividend; + + // Basic division + result = dividend >> exponent; + + // Adjust 'result' for rounding (mid point away from zero) + q31_t threshold = remainder_mask >> 1; + if (result < 0) + { + threshold++; + } + if (remainder > threshold) + { + result++; + } + + return result; +} + +/** + * @brief Requantize a given value. + * @param[in] val Value to be requantized + * @param[in] multiplier multiplier. Range {NN_Q31_MIN + 1, Q32_MAX} + * @param[in] shift left or right shift for 'val * multiplier' + * + * @return Returns (val * multiplier)/(2 ^ shift) + * + */ +__STATIC_FORCEINLINE q31_t arm_nn_requantize(const q31_t val, const q31_t multiplier, const q31_t shift) +{ +#ifdef CMSIS_NN_USE_SINGLE_ROUNDING + const int64_t total_shift = 31 - shift; + const int64_t new_val = val * (int64_t)multiplier; + + int32_t result = new_val >> (total_shift - 1); + result = (result + 1) >> 1; + + return result; +#else + return arm_nn_divide_by_power_of_two(arm_nn_doubling_high_mult_no_sat(val * (1 << LEFT_SHIFT(shift)), multiplier), + RIGHT_SHIFT(shift)); +#endif +} + +/** + * @brief Requantize a given 64 bit value. + * @param[in] val Value to be requantized in the range {-(1<<47)} to {(1<<47) - 1} + * @param[in] reduced_multiplier Reduced multiplier in the range {NN_Q31_MIN + 1, Q32_MAX} to {Q16_MIN + 1, + * Q16_MAX} + * @param[in] shift Left or right shift for 'val * multiplier' in the range {-31} to {7} + * + * @return Returns (val * multiplier)/(2 ^ shift) + * + */ +__STATIC_FORCEINLINE q31_t arm_nn_requantize_s64(const q63_t val, const q31_t reduced_multiplier, const q31_t shift) +{ + const q63_t new_val = val * reduced_multiplier; + + q31_t result = new_val >> (14 - shift); // 64->32 bit reduction + result = (result + 1) >> 1; // Last shift position and insert round + + return result; +} + +/** + * @brief memcpy optimized for MVE + * @param[in, out] dst Destination pointer + * @param[in] src Source pointer. + * @param[in] block_size Number of bytes to copy. + * + */ +__STATIC_FORCEINLINE void arm_memcpy_q7(q7_t *__RESTRICT dst, const q7_t *__RESTRICT src, uint32_t block_size) +{ +#if defined(ARM_MATH_MVEI) + __asm volatile(" wlstp.8 lr, %[cnt], 1f \n" + "2: \n" + " vldrb.8 q0, [%[in]], #16 \n" + " vstrb.8 q0, [%[out]], #16 \n" + " letp lr, 2b \n" + "1: \n" + : [ in ] "+r"(src), [ out ] "+r"(dst) + : [ cnt ] "r"(block_size) + : "q0", "memory", "r14"); +#else + memcpy(dst, src, block_size); +#endif +} + +#if defined(ARM_MATH_MVEI) +/** + * @brief Vector saturating doubling high multiply returning high half. + * @param[in] m1 Multiplicand + * @param[in] m2 Multiplier + * @return Result of multiplication. + * + */ +__STATIC_FORCEINLINE int32x4_t arm_doubling_high_mult_mve(const int32x4_t m1, const q31_t m2) +{ + return vqrdmulhq_n_s32(m1, m2); +} + +/** + * @brief Vector rounding divide by power of two. + * @param[in] dividend - Dividend vector + * @param[in] exponent - Divisor = power(2, exponent) + * Range: [0, 31] + * @return Rounded result of division. Midpoint is rounded away from zero. + * + */ +__STATIC_FORCEINLINE int32x4_t arm_divide_by_power_of_two_mve(const int32x4_t dividend, const q31_t exponent) +{ + const int32x4_t shift = vdupq_n_s32(-exponent); + const int32x4_t fixup = vshrq_n_s32(vandq_s32(dividend, shift), 31); + const int32x4_t fixed_up_dividend = vqaddq_s32(dividend, fixup); + return vrshlq_s32(fixed_up_dividend, shift); +} + +/** + * @brief Requantize a given vector. + * @param[in] val Vector to be requantized + * @param[in] multiplier multiplier + * @param[in] shift shift + * + * @return Returns (val * multiplier)/(2 ^ shift) + * + */ +__STATIC_FORCEINLINE int32x4_t arm_requantize_mve(const int32x4_t val, const q31_t multiplier, const q31_t shift) +{ +#ifdef CMSIS_NN_USE_SINGLE_ROUNDING + const int right_shift = MIN(-1, shift); + const int left_shift = shift - right_shift; + + const int32x4_t left_shift_dup = vdupq_n_s32(left_shift); + const int32x4_t right_shift_dup = vdupq_n_s32(right_shift); + + int32x4_t result = vqdmulhq_n_s32(vshlq_s32(val, left_shift_dup), multiplier); + result = vrshlq_s32(result, right_shift_dup); + + return result; +#else + return arm_divide_by_power_of_two_mve( + arm_doubling_high_mult_mve(vshlq_s32(val, vdupq_n_s32(LEFT_SHIFT(shift))), multiplier), RIGHT_SHIFT(shift)); +#endif +} + +__STATIC_FORCEINLINE int32x4_t arm_doubling_high_mult_mve_32x4(const int32x4_t m1, const int32x4_t m2) +{ + return vqrdmulhq_s32(m1, m2); +} + +__STATIC_FORCEINLINE int32x4_t arm_divide_by_power_of_two_mve_32x4(const int32x4_t dividend, const int32x4_t exponent) +{ + const int32x4_t shift = -exponent; + const int32x4_t fixup = vshrq_n_s32(vandq_s32(dividend, shift), 31); + const int32x4_t fixed_up_dividend = vqaddq_s32(dividend, fixup); + return vrshlq_s32(fixed_up_dividend, shift); +} + +__STATIC_FORCEINLINE int32x4_t arm_requantize_mve_32x4(const int32x4_t val, + const int32x4_t multiplier, + const int32x4_t shift) +{ +#ifdef CMSIS_NN_USE_SINGLE_ROUNDING + const int32x4_t right_shift = vminq_s32(vdupq_n_s32(-1), shift); + const int32x4_t left_shift = vqsubq_s32(shift, right_shift); + + int32x4_t result = vqdmulhq_s32(vshlq_s32(val, left_shift), multiplier); + result = vrshlq_s32(result, right_shift); + + return result; +#else + const int32x4_t zz = vdupq_n_s32(0); + const mve_pred16_t p = vcmpgtq_n_s32(shift, 0); + + const int32x4_t left_shift = vpselq_s32(shift, zz, p); + const int32x4_t right_shift = -vpselq_s32(zz, shift, p); + + return arm_divide_by_power_of_two_mve_32x4(arm_doubling_high_mult_mve_32x4(vshlq_s32(val, left_shift), multiplier), + right_shift); +#endif +} +#endif + +// @note The following functions are used only for softmax layer, scaled bits = 5 assumed + +__STATIC_FORCEINLINE int32_t arm_nn_exp_on_negative_values(int32_t val) +{ + int32_t mask = 0; + int32_t shift = 24; + + const int32_t val_mod_minus_quarter = (val & ((1 << shift) - 1)) - (1 << shift); + const int32_t remainder = val_mod_minus_quarter - val; + const int32_t x = (val_mod_minus_quarter << 5) + (1 << 28); + const int32_t x2 = MUL_SAT(x, x); + + int32_t result = 1895147668 + + MUL_SAT(1895147668, x + DIV_POW2(MUL_SAT(DIV_POW2(MUL_SAT(x2, x2), 2) + MUL_SAT(x2, x), 715827883) + x2, 1)); + +#define SELECT_IF_NON_ZERO(x) \ + { \ + mask = MASK_IF_NON_ZERO(remainder & (1 << shift++)); \ + result = SELECT_USING_MASK(mask, MUL_SAT(result, x), result); \ + } + + SELECT_IF_NON_ZERO(1672461947) + SELECT_IF_NON_ZERO(1302514674) + SELECT_IF_NON_ZERO(790015084) + SELECT_IF_NON_ZERO(290630308) + SELECT_IF_NON_ZERO(39332535) + SELECT_IF_NON_ZERO(720401) + SELECT_IF_NON_ZERO(242) + +#undef SELECT_IF_NON_ZERO + + mask = MASK_IF_ZERO(val); + return SELECT_USING_MASK(mask, NN_Q31_MAX, result); +} + +__STATIC_FORCEINLINE q31_t arm_nn_mult_by_power_of_two(const int32_t val, const int32_t exp) +{ + const int32_t thresh = ((1 << (31 - exp)) - 1); + int32_t result = val << exp; + result = SELECT_USING_MASK(MASK_IF_NON_ZERO(val > thresh), NN_Q31_MAX, result); + result = SELECT_USING_MASK(MASK_IF_NON_ZERO(val < -thresh), NN_Q31_MIN, result); + return result; +} + +__STATIC_FORCEINLINE int32_t arm_nn_one_over_one_plus_x_for_x_in_0_1(int32_t val) +{ + const int64_t sum = (int64_t)val + (int64_t)NN_Q31_MAX; + const int32_t half_denominator = (int32_t)((sum + (sum >= 0 ? 1 : -1)) / 2L); + int32_t x = 1515870810 + MUL_SAT(half_denominator, -1010580540); + + const int32_t shift = (1 << 29); + x += MUL_POW2(MUL_SAT(x, shift - MUL_SAT(half_denominator, x)), 2); + x += MUL_POW2(MUL_SAT(x, shift - MUL_SAT(half_denominator, x)), 2); + x += MUL_POW2(MUL_SAT(x, shift - MUL_SAT(half_denominator, x)), 2); + + return MUL_POW2(x, 1); +} + +/** + @brief Write 2 q15 elements and post increment pointer. + @param[in] dest_q15 Pointer to pointer that holds address of destination. + @param[in] src_q31 Input value to be written. + */ +__STATIC_FORCEINLINE void arm_nn_write_q15x2_ia(q15_t **dest_q15, q31_t src_q31) +{ + q31_t val = src_q31; + + memcpy(*dest_q15, &val, 4); + *dest_q15 += 2; +} + +#ifdef __cplusplus +} +#endif + +#endif |