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/*
* Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "helpers_asymm.h"
#if defined(CONV_STRIDE_X)
#if CONV_STRIDE_X == 1
#define convolution1x3 convolution1x3_stride_1
#elif CONV_STRIDE_X == 2
#define convolution1x3 convolution1x3_stride_2
#elif CONV_STRIDE_X == 3
#define convolution1x3 convolution1x3_stride_3
#else /* CONV_STRIDE_X */
#error "Stride not supported"
#endif /* CONV_STRIDE_X */
/** Compute a 1D horizontal convolution of size 3 and stride 1 for uchar type.
*
* @param[in] left_pixel Pointer to the left pixel.
* @param[in] left_coeff Weight of the left pixel
* @param[in] middle_coeff Weight of the middle pixel
* @param[in] right_coeff Weight of the right pixel
* @param[in] input_offset Quantized offset of zero point of the input tensor data range
* @param[in] weight_offset Quantized offset of zero point of the weights tensor data range
*
* @return a int8 containing 8 convoluted values.
*/
inline int8 convolution1x3_stride_1(__global const uchar *left_pixel,
const int left_coeff,
const int middle_coeff,
const int right_coeff,
const int input_offset,
const int weight_offset)
{
int8 temp0 = CONVERT(vload8(0, left_pixel), int8);
int2 temp1 = CONVERT(vload2(0, (left_pixel + 8 * sizeof(uchar))), int2);
int8 left = CONVERT(temp0.s01234567, int8);
int8 middle = CONVERT((int8)(temp0.s1234, temp0.s567, temp1.s0), int8);
int8 right = CONVERT((int8)(temp0.s2345, temp0.s67, temp1.s01), int8);
return (left + input_offset) * (int8)(left_coeff + weight_offset) + (middle + input_offset) * (int8)(middle_coeff + weight_offset) + (right + input_offset) * (int8)(right_coeff + weight_offset);
}
/** Compute a 1D horizontal convolution of size 3 and stride 2 for uchar type.
*
* @param[in] left_pixel Pointer to the left pixel.
* @param[in] left_coeff Weight of the left pixel
* @param[in] middle_coeff Weight of the middle pixel
* @param[in] right_coeff Weight of the right pixel
* @param[in] input_offset Quantized offset of zero point of the input tensor data range
* @param[in] weight_offset Quantized offset of zero point of the weights tensor data range
*
* @return a int8 containing 8 convoluted values.
*/
inline int8 convolution1x3_stride_2(__global const uchar *left_pixel,
const int left_coeff,
const int middle_coeff,
const int right_coeff,
const int input_offset,
const int weight_offset)
{
int16 temp0 = CONVERT(vload16(0, left_pixel), int16);
int temp1 = CONVERT(*(left_pixel + 16 * sizeof(uchar)), int);
int8 left = CONVERT(temp0.s02468ace, int8);
int8 middle = CONVERT(temp0.s13579bdf, int8);
int8 right = CONVERT((int8)(temp0.s2468, temp0.sace, temp1), int8);
return (left + input_offset) * (int8)(left_coeff + weight_offset) + (middle + input_offset) * (int8)(middle_coeff + weight_offset) + (right + input_offset) * (int8)(right_coeff + weight_offset);
}
/** Compute a 1D horizontal convolution of size 3 and stride 3 for uchar type.
*
* @param[in] left_pixel Pointer to the left pixel.
* @param[in] left_coeff Weight of the left pixel
* @param[in] middle_coeff Weight of the middle pixel
* @param[in] right_coeff Weight of the right pixel
* @param[in] input_offset Quantized offset of zero point of the input tensor data range
* @param[in] weight_offset Quantized offset of zero point of the weights tensor data range
*
* @return a int8 containing 8 convoluted values.
*/
inline int8 convolution1x3_stride_3(__global const uchar *left_pixel,
const int left_coeff,
const int middle_coeff,
const int right_coeff,
const int input_offset,
const int weight_offset)
{
int16 temp0 = CONVERT(vload16(0, left_pixel), int16);
int8 temp1 = CONVERT(vload8(0, (left_pixel + 16 * sizeof(uchar))), int8);
int8 left = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8);
int8 middle = CONVERT((int8)(temp0.s147a, temp0.sd, temp1.s036), int8);
int8 right = CONVERT((int8)(temp0.s258b, temp0.se, temp1.s147), int8);
return (left + input_offset) * (int8)(left_coeff + weight_offset) + (middle + input_offset) * (int8)(middle_coeff + weight_offset) + (right + input_offset) * (int8)(right_coeff + weight_offset);
}
/** Apply a 3x3 convolution matrix to a single channel QASYMM8 input image and return the result.
*
* Convolution matrix layout:
*
* [ mat0, mat1, mat2 ]\n
* [ mat3, mat4, mat5 ]\n
* [ mat6, mat7, mat8 ]\n
*
* @param[in] src A pointer to source Image structure
* @param[in] mat0 Coefficient from the convolution matrix
* @param[in] mat1 Coefficient from the convolution matrix
* @param[in] mat2 Coefficient from the convolution matrix
* @param[in] mat3 Coefficient from the convolution matrix
* @param[in] mat4 Coefficient from the convolution matrix
* @param[in] mat5 Coefficient from the convolution matrix
* @param[in] mat6 Coefficient from the convolution matrix
* @param[in] mat7 Coefficient from the convolution matrix
* @param[in] mat8 Coefficient from the convolution matrix
* @param[in] input_offset Quantized offset of zero point of the input tensor data range
* @param[in] weight_offset Quantized offset of zero point of the weights tensor data range
* @param[in] output_offset Quantized offset of zero point of the output tensor data range
* @param[in] output_multiplier Output scale multiplier
* @param[in] output_shift Output scale divisor exponent
* @param[in] bias (Optional) Bias value
*
* @return a uchar8 containing 8 convoluted values.
*/
inline uchar8 convolution3x3(
Image *src,
const uchar mat0, const uchar mat1, const uchar mat2,
const uchar mat3, const uchar mat4, const uchar mat5,
const uchar mat6, const uchar mat7, const uchar mat8,
const int input_offset, const int weight_offset, const int output_offset,
const int output_multiplier, const int output_shift
#if defined(HAS_BIAS)
,
const int bias
#endif //defined(HAS_BIAS)
)
{
int8 pixels;
pixels = convolution1x3(offset(src, 0, 0), mat0, mat1, mat2, input_offset, weight_offset);
pixels += convolution1x3(offset(src, 0, 1), mat3, mat4, mat5, input_offset, weight_offset);
pixels += convolution1x3(offset(src, 0, 2), mat6, mat7, mat8, input_offset, weight_offset);
#if defined(HAS_BIAS)
pixels += (int8)(bias);
#endif //defined(HAS_BIAS)
pixels = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(pixels, output_multiplier, output_shift, 8);
pixels = pixels + output_offset;
return CONVERT_SAT(pixels, uchar8);
}
/** This function computes the horizontal integral of the image.
*
* @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8
* @param[in] src_stride_x Stride of the source image in X dimension (in bytes)
* @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] src_stride_y Stride of the source image in Y dimension (in bytes)
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image
* @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8
* @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
* @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
* @param[in] weights_ptr Pointer to the weights tensor. Supported data types: QASYMM8
* @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes)
* @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes)
* @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes)
* @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: QASYMM8
* @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes)
* @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector
* @param[in] input_offset Quantized offset of zero point of the input tensor data range
* @param[in] weight_offset Quantized offset of zero point of the weights tensor data range
* @param[in] output_offset Quantized offset of zero point of the output tensor data range
* @param[in] output_multiplier Output scale multiplier
* @param[in] output_shift Output scale divisor exponent
*/
__kernel void depthwise_convolution_3x3_quantized(
TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
TENSOR3D_DECLARATION(weights),
#if defined(HAS_BIAS)
VECTOR_DECLARATION(biases),
#endif //defined(HAS_BIAS)
int input_offset,
int weight_offset,
int output_offset,
int output_multiplier,
int output_shift)
{
Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src);
Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst);
Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT(weights);
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
#endif //defined(HAS_BIAS)
uchar3 offset = (uchar3)(0, 1, 2) * (uchar3)weights_stride_y;
uchar3 weights_values0 = vload3(0, weights.ptr + offset.s0);
uchar3 weights_values1 = vload3(0, weights.ptr + offset.s1);
uchar3 weights_values2 = vload3(0, weights.ptr + offset.s2);
#if defined(HAS_BIAS)
int bias_value = *((__global int *)(vector_offset(&biases, get_global_id(2))));
#endif //defined(HAS_BIAS)
uchar8 pixels = convolution3x3(&src, weights_values0.s0, weights_values0.s1, weights_values0.s2,
weights_values1.s0, weights_values1.s1, weights_values1.s2,
weights_values2.s0, weights_values2.s1, weights_values2.s2,
input_offset, weight_offset, output_offset,
output_multiplier, output_shift
#if defined(HAS_BIAS)
,
bias_value
#endif //defined(HAS_BIAS)
);
vstore8(pixels, 0, dst.ptr);
}
#endif //defined(CONV_STRIDE_X)