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Nn/nonsquare 1d #592

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Nn/nonsquare 1d #592

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ac045f0
created first pass at nonsquare pooling functions
May 9, 2019
1d2a75e
added ref function and proposed test
May 9, 2019
f42d943
updated reference and armnn functions
May 9, 2019
4d6b1ed
added 1d inline wrappers for pooling
May 9, 2019
07591ee
added 1d pooling functions and cleaned up 1d wrappers, plus built bas…
May 9, 2019
6d2e9b9
cleaned up comments on 1d functions
May 9, 2019
cdfce23
kept warnings from fast implementations
May 9, 2019
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322 changes: 319 additions & 3 deletions CMSIS/NN/Include/arm_nnfunctions.h
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Original file line number Diff line number Diff line change
Expand Up @@ -204,6 +204,65 @@ extern "C"
q15_t * bufferA,
q7_t * bufferB);

/**
* @brief Basic Q7 convolution function (1D)
* @param[in] Im_in pointer to input tensor
* @param[in] dim_im_in input tensor dimention y
* @param[in] ch_im_in number of input tensor channels
* @param[in] wt pointer to kernel weights
* @param[in] ch_im_out number of filters, i.e., output tensor channels
* @param[in] dim_kernel filter kernel size y
* @param[in] padding padding size y
* @param[in] stride. convolution stride y
* @param[in] bias pointer to bias
* @param[in] bias_shift amount of left-shift for bias
* @param[in] out_shift amount of right-shift for output
* @param[in,out] Im_out pointer to output tensor
* @param[in] dim_im_out. output tensor dimension y
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] bufferB pointer to buffer space for output
* @return The function returns <code>ARM_MATH_SUCCESS</code>
*/

static inline arm_status arm_convolve_HWC_q7_basic_1d(
const q7_t * Im_in,
const uint16_t dim_im_in,
const uint16_t ch_im_in,
const q7_t * wt,
const uint16_t ch_im_out,
const uint16_t dim_kernel,
const uint16_t padding,
const uint16_t stride,
const q7_t * bias,
const uint16_t bias_shift,
const uint16_t out_shift,
q7_t * Im_out,
const uint16_t dim_im_out,
q15_t * bufferA,
q7_t * bufferB ) {
return arm_convolve_HWC_q7_basic_nonsquare(
Im_in, //const q7_t * Im_in
dim_im_in, //const uint16_t dim_im_in_x,
1, //const uint16_t dim_im_in_y,
ch_im_in, //const uint16_t ch_im_in,
wt, //const q7_t * wt,
ch_im_out, //const uint16_t ch_im_out,
dim_kernel, //const uint16_t dim_kernel_x,
1, //const uint16_t dim_kernel_y,
padding, //const uint16_t padding_x,
1, //const uint16_t padding_y,
stride, //const uint16_t stride_x,
1, //const uint16_t stride_y,
bias, //const q7_t * bias,
bias_shift, //const uint16_t bias_shift,
out_shift, //const uint16_t out_shift,
Im_out, //q7_t * Im_out,
dim_im_out, //const uint16_t dim_im_out_x,
1, //const uint16_t dim_im_out_y,
bufferA, //q15_t * bufferA,
bufferB); //q7_t * bufferB);
}

/**
* @brief Basic Q15 convolution function
* @param[in] Im_in pointer to input tensor
Expand Down Expand Up @@ -335,6 +394,71 @@ extern "C"
q15_t * bufferA,
q7_t * bufferB);

/**
* @brief Fast Q7 convolution function (1D)
* @param[in] Im_in pointer to input tensor
* @param[in] dim_im_in input tensor dimention y
* @param[in] ch_im_in number of input tensor channels
* @param[in] wt pointer to kernel weights
* @param[in] ch_im_out number of filters, i.e., output tensor channels
* @param[in] dim_kernel filter kernel size y
* @param[in] padding padding size y
* @param[in] stride. convolution stride y
* @param[in] bias pointer to bias
* @param[in] bias_shift amount of left-shift for bias
* @param[in] out_shift amount of right-shift for output
* @param[in,out] Im_out pointer to output tensor
* @param[in] dim_im_out. output tensor dimension y
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] bufferB pointer to buffer space for output
* @return The function returns <code>ARM_MATH_SUCCESS</code>
* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
*
* This function is the version with full list of optimization tricks, but with
* some contraints:
* ch_im_in is multiple of 4
* ch_im_out is multiple of 2
*/

static inline arm_status arm_convolve_HWC_q7_fast_1d(
const q7_t * Im_in,
const uint16_t dim_im_in,
const uint16_t ch_im_in,
const q7_t * wt,
const uint16_t ch_im_out,
const uint16_t dim_kernel,
const uint16_t padding,
const uint16_t stride,
const q7_t * bias,
const uint16_t bias_shift,
const uint16_t out_shift,
q7_t * Im_out,
const uint16_t dim_im_out,
q15_t * bufferA,
q7_t * bufferB ) {
return arm_convolve_HWC_q7_fast_nonsquare(
Im_in, //const q7_t * Im_in
dim_im_in, //const uint16_t dim_im_in_x,
1, //const uint16_t dim_im_in_y,
ch_im_in, //const uint16_t ch_im_in,
wt, //const q7_t * wt,
ch_im_out, //const uint16_t ch_im_out,
dim_kernel, //const uint16_t dim_kernel_x,
1, //const uint16_t dim_kernel_y,
padding, //const uint16_t padding_x,
1, //const uint16_t padding_y,
stride, //const uint16_t stride_x,
1, //const uint16_t stride_y,
bias, //const q7_t * bias,
bias_shift, //const uint16_t bias_shift,
out_shift, //const uint16_t out_shift,
Im_out, //q7_t * Im_out,
dim_im_out, //const uint16_t dim_im_out_x,
1, //const uint16_t dim_im_out_y,
bufferA, //q15_t * bufferA,
bufferB); //q7_t * bufferB);
}

/**
* @brief Fast Q7 version of 1x1 convolution (non-sqaure shape)
* @param[in] Im_in pointer to input tensor
Expand Down Expand Up @@ -502,7 +626,7 @@ extern "C"
*
* <b>Buffer size:</b>
*
* bufferA size: 2*ch_im_in*dim_kernel*dim_kernel
* bufferA size: 2*ch_im_in*dim_kernel_x*dim_kernel_y
*
* bufferB size: 0
*
Expand Down Expand Up @@ -535,7 +659,83 @@ extern "C"
const uint16_t dim_im_out_y,
q15_t * bufferA,
q7_t * bufferB);



/**
* @brief Fast Q15 convolution function (1D)
* @param[in] Im_in pointer to input tensor
* @param[in] dim_im_in input tensor dimention y
* @param[in] ch_im_in number of input tensor channels
* @param[in] wt pointer to kernel weights
* @param[in] ch_im_out number of filters, i.e., output tensor channels
* @param[in] dim_kernel filter kernel size y
* @param[in] padding padding size y
* @param[in] stride. convolution stride y
* @param[in] bias pointer to bias
* @param[in] bias_shift amount of left-shift for bias
* @param[in] out_shift amount of right-shift for output
* @param[in,out] Im_out pointer to output tensor
* @param[in] dim_im_out. output tensor dimension y
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] bufferB pointer to buffer space for output
* @return The function returns <code>ARM_MATH_SUCCESS</code>
* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
*
* @details
*
* <b>Buffer size:</b>
*
* bufferA size: 2*ch_im_in*dim_kernel_x*dim_kernel_y
*
* bufferB size: 0
*
* <b>Input dimension constraints:</b>
*
* ch_im_in is multiple of 2
*
* ch_im_out is multipe of 2
*
*/
static inline arm_status arm_convolve_HWC_q15_fast_1d(
const q7_t * Im_in,
const uint16_t dim_im_in,
const uint16_t ch_im_in,
const q7_t * wt,
const uint16_t ch_im_out,
const uint16_t dim_kernel,
const uint16_t padding,
const uint16_t stride,
const q7_t * bias,
const uint16_t bias_shift,
const uint16_t out_shift,
q7_t * Im_out,
const uint16_t dim_im_out,
q15_t * bufferA,
q7_t * bufferB ) {
return arm_convolve_HWC_q15_fast_nonsquare(
Im_in, //const q7_t * Im_in
dim_im_in, //const uint16_t dim_im_in_x,
1, //const uint16_t dim_im_in_y,
ch_im_in, //const uint16_t ch_im_in,
wt, //const q7_t * wt,
ch_im_out, //const uint16_t ch_im_out,
dim_kernel, //const uint16_t dim_kernel_x,
1, //const uint16_t dim_kernel_y,
padding, //const uint16_t padding_x,
1, //const uint16_t padding_y,
stride, //const uint16_t stride_x,
1, //const uint16_t stride_y,
bias, //const q7_t * bias,
bias_shift, //const uint16_t bias_shift,
out_shift, //const uint16_t out_shift,
Im_out, //q7_t * Im_out,
dim_im_out, //const uint16_t dim_im_out_x,
1, //const uint16_t dim_im_out_y,
bufferA, //q15_t * bufferA,
bufferB); //q7_t * bufferB);
}


/**
* @brief Q7 depthwise separable convolution function
* @param[in] Im_in pointer to input tensor
Expand Down Expand Up @@ -629,7 +829,6 @@ extern "C"
q15_t * bufferA,
q7_t * bufferB);


/**
* @defgroup FC Fully-connected Layer Functions
*
Expand Down Expand Up @@ -949,6 +1148,64 @@ extern "C"
q7_t * bufferA,
q7_t * Im_out);

/**
* @brief Q7 max pooling function
* @param[in, out] Im_in pointer to input tensor
* @param[in] dim_im_in_x input tensor dimention along X axis
* @param[in] dim_im_in_y input tensor dimention along Y axis
* @param[in] ch_im_in number of input tensor channels
* @param[in] dim_kernel_x filter kernel size along X axis
* @param[in] dim_kernel_y filter kernel size along Y axis
* @param[in] padding_x padding sizes along X axis
* @param[in] padding_y padding sizes along Y axis
* @param[in] stride_x convolution stride along X axis
* @param[in] stride_y convolution stride along Y axis
* @param[in] dim_im_out_x output tensor dimension along X axis
* @param[in] dim_im_out_y output tensor dimension along Y axis
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] Im_out pointer to output tensor
* @return none.
*/

void arm_maxpool_q7_HWC_nonsquare(q7_t * Im_in,
const uint16_t dim_im_in_x,
const uint16_t dim_im_in_y,
const uint16_t ch_im_in,
const uint16_t dim_kernel_x,
const uint16_t dim_kernel_y,
const uint16_t padding_x,
const uint16_t padding_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint16_t dim_im_out_x,
const uint16_t dim_im_out_y,
q7_t * bufferA,
q7_t * Im_out);

/**
* @brief Q7 1-D max pooling function
* @param[in, out] Im_in pointer to input tensor
* @param[in] dim_im_in input tensor dimention
* @param[in] ch_im_in number of input tensor channels
* @param[in] dim_kernel filter kernel size
* @param[in] padding padding sizes
* @param[in] stride convolution stride
* @param[in] dim_im_out output tensor dimension
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] Im_out pointer to output tensor
* @return none.
*/

void arm_maxpool_q7_HWC_1d(const q7_t * Im_in, // input image
const uint16_t dim_im_in, // input image dimension
const uint16_t ch_im_in, // number of input image channels
const uint16_t dim_kernel, // window kernel size
const uint16_t padding, // padding sizes
const uint16_t stride, // stride
const uint16_t dim_im_out, // output image dimension
q7_t * bufferA, // a buffer for local storage
q7_t * Im_out);

/**
* @brief Q7 average pooling function
* @param[in] Im_in pointer to input tensor
Expand All @@ -974,6 +1231,65 @@ extern "C"
q7_t * bufferA,
q7_t * Im_out);

/**
* @brief Q7 average pooling function
* @param[in, out] Im_in pointer to input tensor
* @param[in] dim_im_in_x input tensor dimention along X axis
* @param[in] dim_im_in_y input tensor dimention along Y axis
* @param[in] ch_im_in number of input tensor channels
* @param[in] dim_kernel_x filter kernel size along X axis
* @param[in] dim_kernel_y filter kernel size along Y axis
* @param[in] padding_x padding sizes along X axis
* @param[in] padding_y padding sizes along Y axis
* @param[in] stride_x convolution stride along X axis
* @param[in] stride_y convolution stride along Y axis
* @param[in] dim_im_out_x output tensor dimension along X axis
* @param[in] dim_im_out_y output tensor dimension along Y axis
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] Im_out pointer to output tensor
* @return none.
*/

void arm_avepool_q7_HWC_nonsquare(q7_t * Im_in,
const uint16_t dim_im_in_x,
const uint16_t dim_im_in_y,
const uint16_t ch_im_in,
const uint16_t dim_kernel_x,
const uint16_t dim_kernel_y,
const uint16_t padding_x,
const uint16_t padding_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint16_t dim_im_out_x,
const uint16_t dim_im_out_y,
q7_t * bufferA,
q7_t * Im_out);

/**
* @brief Q7 1-D max pooling function
* @param[in, out] Im_in pointer to input tensor
* @param[in] dim_im_in input tensor dimention
* @param[in] ch_im_in number of input tensor channels
* @param[in] dim_kernel filter kernel size
* @param[in] padding padding sizes
* @param[in] stride convolution stride
* @param[in] dim_im_out output tensor dimension
* @param[in,out] bufferA pointer to buffer space for input
* @param[in,out] Im_out pointer to output tensor
* @return none.
*/

void arm_avepool_q7_HWC_1d(const q7_t * Im_in, // input image
const uint16_t dim_im_in, // input image dimension
const uint16_t ch_im_in, // number of input image channels
const uint16_t dim_kernel, // window kernel size
const uint16_t padding, // padding sizes
const uint16_t stride, // stride
const uint16_t dim_im_out, // output image dimension
q7_t * bufferA, // a buffer for local storage
q7_t * Im_out);


/**
* @defgroup Softmax Softmax Functions
*
Expand Down
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