Official ARM version: v5.6.0
This commit is contained in:
rihab kouki
parent
9f95ff5b6b
commit
96d6da4e25
2939 changed files with 339304 additions and 113320 deletions
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@ -53,7 +53,4 @@ extern const q15_t tanhTable_q15[256];
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extern const q15_t sigmoidHTable_q15[192];
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extern const q15_t sigmoidLTable_q15[128];
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extern const q15_t sigmoidLTable_q15[128];
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extern const q15_t sigmoidHTable_q15[192];
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#endif /* ARM_NN_TABLES_H */
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@ -34,7 +34,7 @@
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* ------------
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*
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* This user manual describes the CMSIS NN software library,
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* a collection of efficient neural network kernels developed to maximize the
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* a collection of efficient neural network kernels developed to maximize the
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* performance and minimize the memory footprint of neural networks on Cortex-M processor cores.
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*
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* The library is divided into a number of functions each covering a specific category:
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@ -47,8 +47,8 @@
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*
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* The library has separate functions for operating on different weight and activation data
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* types including 8-bit integers (q7_t) and 16-bit integers (q15_t). The descrition of the
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* kernels are included in the function description. The implementation details are also
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* described in this paper [1].
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* kernels are included in the function description. The implementation details are also
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* described in this paper [1].
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*
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* Block Diagram
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* --------
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@ -86,7 +86,7 @@
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/**
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* @defgroup groupNN Neural Network Functions
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* These functions perform basic operations for neural network layers.
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* These functions perform basic operations for neural network layers.
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*/
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#ifndef _ARM_NNFUNCTIONS_H
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@ -111,12 +111,12 @@ extern "C"
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*
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* The convolution is implemented in 2 steps: im2col and GEMM
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*
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* im2col is a process of converting each patch of image data into
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* im2col is a process of converting each patch of image data into
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* a column. After im2col, the convolution is computed as matrix-matrix
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* multiplication.
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*
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*
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* To reduce the memory footprint, the im2col is performed partially.
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* Each iteration, only a few column (i.e., patches) are generated and
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* Each iteration, only a few column (i.e., patches) are generated and
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* computed with GEMM kernels similar to CMSIS-DSP arm_mat_mult functions.
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*
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*/
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@ -136,9 +136,9 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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*
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*/
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@ -153,9 +153,9 @@ extern "C"
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -180,7 +180,7 @@ extern "C"
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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*/
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arm_status arm_convolve_HWC_q7_basic_nonsquare(const q7_t * Im_in,
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@ -219,9 +219,9 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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* @return The function returns <code>ARM_MATH_SUCCESS</code>
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*
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*/
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@ -236,9 +236,9 @@ extern "C"
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const q15_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -256,7 +256,7 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -278,9 +278,9 @@ extern "C"
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -303,7 +303,7 @@ extern "C"
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -355,7 +355,7 @@ extern "C"
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -405,7 +405,7 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -426,9 +426,9 @@ extern "C"
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const q7_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -446,7 +446,7 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -468,9 +468,9 @@ extern "C"
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const q15_t * bias,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q15_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -493,7 +493,7 @@ extern "C"
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -508,7 +508,7 @@ extern "C"
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*
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* <b>Input dimension constraints:</b>
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*
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* ch_im_in is multiple of 2
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* ch_im_in is multiple of 2
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*
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* ch_im_out is multipe of 2
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*
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@ -532,10 +532,10 @@ extern "C"
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const uint16_t out_shift,
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q15_t * Im_out,
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const uint16_t dim_im_out_x,
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const uint16_t dim_im_out_y,
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q15_t * bufferA,
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const uint16_t dim_im_out_y,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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* @brief Q7 depthwise separable convolution function
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* @param[in] Im_in pointer to input tensor
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@ -551,7 +551,7 @@ extern "C"
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* @param[in] out_shift amount of right-shift for output
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out output tensor dimension
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -574,8 +574,8 @@ extern "C"
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const uint16_t bias_shift,
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const uint16_t out_shift,
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q7_t * Im_out,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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const uint16_t dim_im_out,
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q15_t * bufferA,
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q7_t * bufferB);
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/**
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@ -598,7 +598,7 @@ extern "C"
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* @param[in,out] Im_out pointer to output tensor
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* @param[in] dim_im_out_x output tensor dimension x
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* @param[in] dim_im_out_y output tensor dimension y
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferA pointer to buffer space for input
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* @param[in,out] bufferB pointer to buffer space for output
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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@ -642,7 +642,7 @@ extern "C"
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*
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* Here we have two types of kernel functions. The basic function
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* implements the function using regular GEMV approach. The opt functions
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* operates with weights in interleaved formats.
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* operates with weights in interleaved formats.
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*
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*/
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@ -666,9 +666,9 @@ extern "C"
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const uint16_t dim_vec,
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut,
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q15_t * vec_buffer);
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/**
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@ -691,9 +691,9 @@ extern "C"
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const uint16_t dim_vec,
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut,
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q15_t * vec_buffer);
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/**
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@ -716,9 +716,9 @@ extern "C"
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const uint16_t dim_vec,
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q15_t * bias,
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q15_t * pOut,
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const uint16_t out_shift,
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const q15_t * bias,
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q15_t * pOut,
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q15_t * vec_buffer);
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/**
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@ -742,8 +742,8 @@ extern "C"
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q15_t * bias,
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q15_t * pOut,
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const q15_t * bias,
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q15_t * pOut,
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q15_t * vec_buffer);
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/**
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@ -767,8 +767,8 @@ extern "C"
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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q15_t * pOut,
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const q7_t * bias,
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q15_t * pOut,
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q15_t * vec_buffer);
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/**
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@ -792,16 +792,16 @@ extern "C"
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const uint16_t num_of_rows,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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q15_t * pOut,
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const q7_t * bias,
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q15_t * pOut,
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q15_t * vec_buffer);
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/**
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* @brief Matrix-Multiplication Kernels for Convolution
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*
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* These functions are used within convolution layer functions for
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* These functions are used within convolution layer functions for
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* matrix multiplication.
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*
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*
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* The implementation is similar to CMSIS-DSP arm_mat_mult functions
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* with one Q7 and one Q15 operands. The Q15 operand is the im2col
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* output which is always with 2 columns.
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@ -826,8 +826,8 @@ extern "C"
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const uint16_t ch_im_out,
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const uint16_t numCol_A,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut);
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/**
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@ -848,8 +848,8 @@ extern "C"
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const uint16_t ch_im_out,
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const uint16_t numCol_A,
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const uint16_t bias_shift,
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const uint16_t out_shift,
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const q7_t * bias,
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const uint16_t out_shift,
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const q7_t * bias,
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q7_t * pOut);
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#ifdef __cplusplus
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@ -902,7 +902,7 @@ extern "C"
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* @return none.
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*/
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void arm_nn_activations_direct_q7(q7_t * data, uint16_t size, uint16_t int_width,
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void arm_nn_activations_direct_q7(q7_t * data, uint16_t size, uint16_t int_width,
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arm_nn_activation_type type);
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/**
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@ -944,9 +944,9 @@ extern "C"
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const uint16_t ch_im_in,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const uint16_t dim_im_out,
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q7_t * bufferA,
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const uint16_t stride,
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const uint16_t dim_im_out,
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q7_t * bufferA,
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q7_t * Im_out);
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/**
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@ -969,9 +969,9 @@ extern "C"
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const uint16_t ch_im_in,
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const uint16_t dim_kernel,
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const uint16_t padding,
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const uint16_t stride,
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const uint16_t dim_im_out,
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q7_t * bufferA,
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const uint16_t stride,
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const uint16_t dim_im_out,
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q7_t * bufferA,
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q7_t * Im_out);
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/**
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@ -1003,6 +1003,71 @@ extern "C"
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void arm_softmax_q15(const q15_t * vec_in, const uint16_t dim_vec, q15_t * p_out);
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/**
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* @brief uint8 depthwise convolution function with asymmetric quantization for even number of channel multiplier
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* and input channels. Unless specified otherwise, arguments are mandatory.
|
||||
*
|
||||
* @param[in] input Pointer to input tensor
|
||||
* @param[in] input_x Width of input tensor
|
||||
* @param[in] input_y Height of input tensor
|
||||
* @param[in] input_ch Channels in input tensor
|
||||
* @param[in] kernel Pointer to kernel weights
|
||||
* @param[in] kernel_x Width of kernel
|
||||
* @param[in] kernel_y Height of kernel
|
||||
* @param[in] ch_mult Number of channel multiplier
|
||||
* @param[in] pad_x Padding sizes x
|
||||
* @param[in] pad_y Padding sizes y
|
||||
* @param[in] stride_x Convolution stride along the width
|
||||
* @param[in] stride_y Convolution stride along the height
|
||||
* @param[in] dilation_x Dilation along width. Not used and intended for future enhancement.
|
||||
* @param[in] dilation_y Dilation along height. Not used and intended for future enhancement.
|
||||
* @param[in] bias Pointer to optional bias values. If no bias is
|
||||
* availble, NULL is expected
|
||||
* @param[in] input_offset Input tensor zero offset
|
||||
* @param[in] filter_offset Kernel tensor zero offset
|
||||
* @param[in] output_offset Output tensor zero offset
|
||||
* @param[in,out] output Pointer to output tensor
|
||||
* @param[in] output_x Width of output tensor
|
||||
* @param[in] output_y Height of output tensor
|
||||
* @param[in] output_activation_min Minimum value to clamp the output to. Range : {0, 255}
|
||||
* @param[in] output_activation_max Minimum value to clamp the output to. Range : {0, 255}
|
||||
* @param[in] out_shift Amount of right-shift for output
|
||||
* @param[in] out_mult Output multiplier for requantization
|
||||
* @return The function returns one of the following
|
||||
* <code>ARM_MATH_SIZE_MISMATCH</code> - Not supported dimension of tensors
|
||||
* <code>ARM_MATH_SUCCESS</code> - Successful operation
|
||||
* <code>ARM_MATH_ARGUMENT_ERROR</code> - Implementation not available
|
||||
*
|
||||
* <b> Input constraints</b>
|
||||
* ch_mult is multiple of 2
|
||||
* kernel_x is multiple of 2
|
||||
*
|
||||
*/
|
||||
arm_status arm_depthwise_conv_u8_basic_ver1(const uint8_t *input,
|
||||
const uint16_t input_x,
|
||||
const uint16_t input_y,
|
||||
const uint16_t input_ch,
|
||||
const uint8_t *kernel,
|
||||
const uint16_t kernel_x,
|
||||
const uint16_t kernel_y,
|
||||
const int16_t ch_mult,
|
||||
const int16_t pad_x,
|
||||
const int16_t pad_y,
|
||||
const int16_t stride_x,
|
||||
const int16_t stride_y,
|
||||
const int16_t dilation_x,
|
||||
const int16_t dilation_y,
|
||||
const int32_t *bias,
|
||||
const int32_t input_offset,
|
||||
const int32_t filter_offset,
|
||||
const int32_t output_offset,
|
||||
uint8_t *output,
|
||||
const uint16_t output_x,
|
||||
const uint16_t output_y,
|
||||
const int32_t output_activation_min,
|
||||
const int32_t output_activation_max,
|
||||
const int32_t out_shift,
|
||||
const int32_t out_mult);
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
|
|
|
|||
|
|
@ -32,13 +32,17 @@
|
|||
|
||||
#include "arm_math.h"
|
||||
#include "arm_common_tables.h"
|
||||
//#include <cstring>
|
||||
|
||||
#ifdef __cplusplus
|
||||
extern "C"
|
||||
{
|
||||
#endif
|
||||
|
||||
#define LEFT_SHIFT(_shift) (_shift > 0 ? _shift : 0)
|
||||
#define RIGHT_SHIFT(_shift) (_shift > 0 ? 0 : -_shift)
|
||||
#define Q31_MIN (0x80000000L)
|
||||
#define Q31_MAX (0x7FFFFFFFL)
|
||||
|
||||
/**
|
||||
* @brief Union for SIMD access of Q31/Q15/Q7 types
|
||||
*/
|
||||
|
|
@ -72,11 +76,11 @@ typedef enum
|
|||
*/
|
||||
|
||||
/**
|
||||
* @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
|
||||
* @return none.
|
||||
* @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
|
||||
* @return none.
|
||||
*
|
||||
*/
|
||||
|
||||
|
|
@ -84,10 +88,10 @@ void arm_q7_to_q15_no_shift(const q7_t * pSrc, q15_t * pDst, uint32_t block
|
|||
|
||||
/**
|
||||
* @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.
|
||||
* @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.
|
||||
*
|
||||
*/
|
||||
|
||||
|
|
@ -163,7 +167,7 @@ void arm_nn_mult_q15(
|
|||
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
|
||||
|
|
@ -185,16 +189,79 @@ void arm_nn_mult_q7(
|
|||
q7_t * pDst,
|
||||
const uint16_t out_shift,
|
||||
uint32_t blockSize);
|
||||
|
||||
|
||||
/**
|
||||
* @brief defition to adding rouding offset
|
||||
* @brief macro for adding rounding offset
|
||||
*/
|
||||
#ifndef ARM_NN_TRUNCATE
|
||||
#define NN_ROUND(out_shift) ( 0x1 << (out_shift - 1) )
|
||||
#define NN_ROUND(out_shift) ( (0x1u << out_shift) >> 1 )
|
||||
#else
|
||||
#define NN_ROUND(out_shift) 0
|
||||
#endif
|
||||
|
||||
/**
|
||||
* @brief Saturating doubling high multiply. Result matches
|
||||
* NEON instruction VQRDMULH.
|
||||
* @param[in] m1 Multiplicand
|
||||
* @param[in] m2 Multiplier
|
||||
* @return Result of multiplication.
|
||||
*
|
||||
*/
|
||||
__STATIC_FORCEINLINE q31_t arm_nn_sat_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 = mult / (1UL << 31);
|
||||
|
||||
if ((m1 == m2) && (m1 == Q31_MIN))
|
||||
{
|
||||
result = Q31_MAX;
|
||||
}
|
||||
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 = (1l << 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;
|
||||
}
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue