Gitiles
Code Review Sign In
review.mlplatform.org / ml / ComputeLibrary / 7d18e9cc9cf687ac97eae7c5d17591b11bc1bb65 / . / src / core / CL / cl_kernels / depthwise_convolution_quantized.cl
blob: 95cd44eb78d1fc7ac216ae3395e9260c83b1ae67 [file] [log] [blame]
/*
* Copyright (c) 2017-2020 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"
#ifndef VEC_SIZE
#if defined(N0)
#define VEC_SIZE N0
#else /* defined(N0) */
#define VEC_SIZE 8
#endif /* defined(N0) */
#endif /* VEC_SIZE */
#if defined(ACTIVATION_TYPE) && defined(CONST_0)
#include "activation_layer_quant.cl"
#define ACTIVATION_FUNC(x) PERFORM_ACTIVATION_QUANT(ACTIVATION_TYPE, x)
#else /* defined(ACTIVATION_TYPE) && defined(CONST_0) */
#define ACTIVATION_FUNC(x) (x)
#endif /* defined(ACTIVATION_TYPE) && defined(CONST_0) */
#define VEC_INT VEC_DATA_TYPE(int, VEC_SIZE)
#define VEC_FLOAT VEC_DATA_TYPE(float, VEC_SIZE)
#define VEC_SHORT VEC_DATA_TYPE(short, VEC_SIZE)
#if defined(DATA_TYPE) && defined(WEIGHTS_TYPE)
#define VEC_TYPE(size) VEC_DATA_TYPE(DATA_TYPE, size)
#if defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && ((defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT)) || defined(REAL_MULTIPLIER))
#if defined(WEIGHTS_PROMOTED_TYPE)
#define VEC_WEIGHTS_PROMOTED_TYPE(size) VEC_DATA_TYPE(WEIGHTS_PROMOTED_TYPE, size)
#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
#if defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
#define ARM_DOT(x, y, val) val = arm_dot_acc((x), (y), val);
#else // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
#define ARM_DOT(x, y, val) val += arm_dot((x), (y));
#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
#if defined(CONV_STRIDE_Y) && defined(CONV_STRIDE_X) && defined(DEPTH_MULTIPLIER) && defined(DST_CHANNELS)
#if CONV_STRIDE_X > 3
#error "Stride X not supported"
#endif /* CONV_STRIDE_X > 3 */
#if !defined(IS_DOT8)
#if DILATION_X == 1
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
int8 temp0 = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value)), int8); \
int2 temp1 = CONVERT(vload2(0, (__global DATA_TYPE *)(first_value + 8 * sizeof(DATA_TYPE))), int2); \
\
left = CONVERT(temp0.s01234567, int8); \
middle = CONVERT((int8)(temp0.s1234, temp0.s567, temp1.s0), int8); \
right = CONVERT((int8)(temp0.s2345, temp0.s67, temp1.s01), int8); \
})
#elif CONV_STRIDE_X == 2
#define GET_VALUES(first_value, left, middle, right) \
({ \
int16 temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value)), int16); \
int temp1 = CONVERT(*((__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE))), int); \
\
left = CONVERT(temp0.s02468ace, int8); \
middle = CONVERT(temp0.s13579bdf, int8); \
right = CONVERT((int8)(temp0.s2468, temp0.sace, temp1), int8); \
})
#else /* CONV_STRIDE_X */
#define GET_VALUES(first_value, left, middle, right) \
({ \
int16 temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value)), int16); \
int8 temp1 = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE))), int8); \
\
left = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
middle = CONVERT((int8)(temp0.s147a, temp0.sd, temp1.s036), int8); \
right = CONVERT((int8)(temp0.s258b, temp0.se, temp1.s147), int8); \
})
#endif /* CONV_STRIDE_X */
#else /* DILATION_X == 1 */
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
left = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value)), int8); \
middle = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))), int8); \
right = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))), int8); \
})
#elif CONV_STRIDE_X == 2
#define GET_VALUES(first_value, left, middle, right) \
({ \
int16 temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value)), int16); \
left = CONVERT(temp0.s02468ace, int8); \
\
temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))), int16); \
middle = CONVERT(temp0.s02468ace, int8); \
\
temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))), int16); \
right = CONVERT(temp0.s02468ace, int8); \
})
#else /* CONV_STRIDE_X */
#define GET_VALUES(first_value, left, middle, right) \
({ \
int16 temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value)), int16); \
int8 temp1 = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE))), int8); \
left = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
\
temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))), int16); \
temp1 = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + (16 + DILATION_X) * sizeof(DATA_TYPE))), int8); \
middle = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
\
temp0 = CONVERT(vload16(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))), int16); \
temp1 = CONVERT(vload8(0, (__global DATA_TYPE *)(first_value + (16 + 2 * DILATION_X) * sizeof(DATA_TYPE))), int8); \
right = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
})
#endif /* CONV_STRIDE_X */
#endif /* DILATION_X==1 */
/** This function computes the depthwise convolution quantized.
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_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] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
* @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] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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
*/
__kernel void dwc_3x3_native_quantized8_nchw(
TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
TENSOR3D_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts)
#if defined(HAS_BIAS)
,
VECTOR_DECLARATION(biases)
#endif //defined(HAS_BIAS)
)
{
Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src);
Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst);
Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
Vector output_multipliers = CONVERT_TO_VECTOR_STRUCT_NO_STEP(output_multipliers);
Vector output_shifts = CONVERT_TO_VECTOR_STRUCT_NO_STEP(output_shifts);
// Extract channel and linearized batch indices
const int channel = get_global_id(2) % DST_CHANNELS;
const int batch = get_global_id(2) / DST_CHANNELS;
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
int bias_value = *((__global int *)(vector_offset(&biases, channel)));
#endif //defined(HAS_BIAS)
// Load relevant input and weights data (Accounts depth multiplier when indexing input, OFM = IFM * DEPTH_MULTIPLIER)
src.ptr -= batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z + (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
VEC_DATA_TYPE(WEIGHTS_TYPE, 3)
w0 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 0 * weights_stride_y));
VEC_DATA_TYPE(WEIGHTS_TYPE, 3)
w1 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 1 * weights_stride_y));
VEC_DATA_TYPE(WEIGHTS_TYPE, 3)
w2 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 2 * weights_stride_y));
#if defined(PER_CHANNEL_QUANTIZATION)
const int output_multiplier = *((__global int *)vector_offset(&output_multipliers, channel));
const int output_shift = *((__global int *)vector_offset(&output_shifts, channel));
#endif // defined(PER_CHANNEL_QUANTIZATION)
int8 values0 = 0;
int8 sum0 = 0;
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
int8 values1 = 0;
int8 sum1 = 0;
#endif /* CONV_STRIDE_Y &&DILATION_Y==1 */
// Row0
int8 left, middle, right;
GET_VALUES(src.ptr + 0 * src_stride_y, left, middle, right);
values0 += left * (int8)(w0.s0);
values0 += middle * (int8)(w0.s1);
values0 += right * (int8)(w0.s2);
#if WEIGHTS_OFFSET != 0
sum0 += left + middle + right;
#endif /* WEIGHTS_OFFSET != 0 */
// Row1
GET_VALUES(src.ptr + DILATION_Y * src_stride_y, left, middle, right);
values0 += left * (int8)(w1.s0);
values0 += middle * (int8)(w1.s1);
values0 += right * (int8)(w1.s2);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += left * (int8)(w0.s0);
values1 += middle * (int8)(w0.s1);
values1 += right * (int8)(w0.s2);
#endif /* CONV_STRIDE_Y && DILATION_Y== 1 */
#if WEIGHTS_OFFSET != 0
int8 tmp = left + middle + right;
sum0 += tmp;
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
sum1 += tmp;
#endif /* CONV_STRIDE_Y &&DILATION_Y== 1 */
#endif /* WEIGHTS_OFFSET != 0 */
// Row2
GET_VALUES(src.ptr + 2 * DILATION_Y * src_stride_y, left, middle, right);
values0 += left * (int8)(w2.s0);
values0 += middle * (int8)(w2.s1);
values0 += right * (int8)(w2.s2);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += left * (int8)(w1.s0);
values1 += middle * (int8)(w1.s1);
values1 += right * (int8)(w1.s2);
#endif /* CONV_STRIDE_Y &&DILATION_Y == 1 */
#if WEIGHTS_OFFSET != 0
tmp = left + middle + right;
sum0 += tmp;
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
sum1 += tmp;
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
// Row3
GET_VALUES(src.ptr + 3 * src_stride_y, left, middle, right);
values1 += left * (int8)(w2.s0);
values1 += middle * (int8)(w2.s1);
values1 += right * (int8)(w2.s2);
#if WEIGHTS_OFFSET != 0
sum1 += left + middle + right;
#endif /* WEIGHTS_OFFSET != 0 */
#endif /* CONV_STRIDE_Y && DILATION_Y == 1 */
#if defined(HAS_BIAS)
values0 += (int8)(bias_value);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(bias_value);
#endif /* CONV_STRIDE_Y & &DILATION_Y == 1 */
#endif //defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
values0 += sum0 * (int8)(WEIGHTS_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum1 * (int8)(WEIGHTS_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
VEC_WEIGHTS_PROMOTED_TYPE(3)
tmp_we = CONVERT(w0, VEC_WEIGHTS_PROMOTED_TYPE(3)) + CONVERT(w1, VEC_WEIGHTS_PROMOTED_TYPE(3)) + CONVERT(w2, VEC_WEIGHTS_PROMOTED_TYPE(3));
WEIGHTS_PROMOTED_TYPE sum_weights = tmp_we.s0 + tmp_we.s1 + tmp_we.s2;
values0 += sum_weights * (int8)(INPUT_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum_weights * (int8)(INPUT_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
values0 += (int8)(K_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(K_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
values0 = CONVERT(round(CONVERT(values0, float8) * (float8)REAL_MULTIPLIER), int8);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
int8 res0_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, output_multiplier, output_shift, 8);
int8 res0_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, output_multiplier, output_shift, 8);
values0 = select(res0_shift_lt0, res0_shift_gt0, (int8)(output_shift) >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#else // OUTPUT_SHIFT < 0
values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#endif // OUTPUT_OFFSET < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
values0 += (int8)OUTPUT_OFFSET;
VEC_TYPE(8)
res0 = CONVERT_SAT(values0, VEC_TYPE(8));
vstore8(ACTIVATION_FUNC(res0), 0, dst.ptr);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
#if defined(REAL_MULTIPLIER)
values1 = CONVERT(round(CONVERT(values1, float8) * (float8)REAL_MULTIPLIER), int8);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
int8 res1_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values1, output_multiplier, output_shift, 8);
int8 res1_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values1, output_multiplier, output_shift, 8);
values1 = select(res1_shift_lt0, res1_shift_gt0, (int8)(output_shift) >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
values1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#else // OUTPUT_SHIFT < 0
values1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#endif // OUTPUT_OFFSET < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
values1 += (int8)OUTPUT_OFFSET;
VEC_TYPE(8)
res1 = CONVERT_SAT(values1, VEC_TYPE(8));
vstore8(ACTIVATION_FUNC(res1), 0, dst.ptr + dst_stride_y);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
}
#else // !defined(IS_DOT8)
#if DILATION_X == 1
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
VEC_TYPE(8) \
temp0 = vload8(0, (__global DATA_TYPE *)(first_value)); \
VEC_TYPE(2) \
temp1 = vload2(0, (__global DATA_TYPE *)(first_value + 8 * sizeof(DATA_TYPE))); \
\
left = temp0.s01234567; \
middle = (VEC_TYPE(8))(temp0.s1234, temp0.s567, temp1.s0); \
right = (VEC_TYPE(8))(temp0.s2345, temp0.s67, temp1.s01); \
})
#elif CONV_STRIDE_X == 2
#define GET_VALUES(first_value, left, middle, right) \
({ \
VEC_TYPE(16) \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value)); \
DATA_TYPE temp1 = *((__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE))); \
\
left = temp0.s02468ace; \
middle = temp0.s13579bdf; \
right = (VEC_TYPE(8))(temp0.s2468, temp0.sace, temp1); \
})
#else /* CONV_STRIDE_X */
#define GET_VALUES(first_value, left, middle, right) \
({ \
VEC_TYPE(16) \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value)); \
VEC_TYPE(8) \
temp1 = vload8(0, (__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE))); \
\
left = (VEC_TYPE(8))(temp0.s0369, temp0.scf, temp1.s25); \
middle = (VEC_TYPE(8))(temp0.s147a, temp0.sd, temp1.s036); \
right = (VEC_TYPE(8))(temp0.s258b, temp0.se, temp1.s147); \
})
#endif /* CONV_STRIDE_X */
#else /*DILATION_X==1*/
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
left = vload8(0, (__global DATA_TYPE *)(first_value)); \
middle = vload8(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))); \
right = vload8(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))); \
})
#elif CONV_STRIDE_X == 2
#define GET_VALUES(first_value, left, middle, right) \
({ \
VEC_TYPE(16) \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value)); \
left = temp0.s02468ace; \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))); \
middle = temp0.s02468ace; \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))); \
right = temp0.s02468ace; \
})
#else /* CONV_STRIDE_X */
#define GET_VALUES(first_value, left, middle, right) \
({ \
VEC_TYPE(16) \
temp0 = vload16(0, (__global DATA_TYPE *)(first_value)); \
VEC_TYPE(8) \
temp1 = vload8(0, (__global DATA_TYPE *)(first_value + 16 * sizeof(DATA_TYPE)))); \
left = (VEC_TYPE(8))(temp0.s0369, temp0.scf, temp1.s25); \
\
temp0 = vload16(0, (__global DATA_TYPE *)(first_value + DILATION_X * sizeof(DATA_TYPE))); \
temp1 = vload8(0, (__global DATA_TYPE *)(first_value + (16 + DILATION_X) * sizeof(DATA_TYPE))); \
middle = (VEC_TYPE(8))(temp0.s0369, temp0.scf, temp1.s25); \
\
temp0 = vload16(0, (__global DATA_TYPE *)(first_value + 2 * DILATION_X * sizeof(DATA_TYPE))); \
temp1 = vload8(0, (__global DATA_TYPE *)(first_value + (16 + 2 * DILATION_X) * sizeof(DATA_TYPE))); \
right = (VEC_TYPE(8))(temp0.s0369, temp0.scf, temp1.s25); \
})
#endif /* CONV_STRIDE_X */
#endif /*DILATION_X==1*/
/** This function computes the depthwise convolution quantized using dot product when the data layout is NCHW.
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_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] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
* @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] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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
*/
__kernel void dwc_3x3_native_quantized8_dot8_nchw(
TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
TENSOR3D_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts)
#if defined(HAS_BIAS)
,
VECTOR_DECLARATION(biases)
#endif //defined(HAS_BIAS)
)
{
Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src);
Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst);
Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
Vector output_multipliers = CONVERT_TO_VECTOR_STRUCT_NO_STEP(output_multipliers);
Vector output_shifts = CONVERT_TO_VECTOR_STRUCT_NO_STEP(output_shifts);
// Extract channel and linearized batch indices
const int channel = get_global_id(2) % DST_CHANNELS;
const int batch = get_global_id(2) / DST_CHANNELS;
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
const int bias_value = *((__global int *)(vector_offset(&biases, channel)));
#endif //defined(HAS_BIAS)
// Load relevant input and weights data (Accounts depth multiplier when indexing input, OFM = IFM * DEPTH_MULTIPLIER)
src.ptr -= batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z + (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
VEC_TYPE(3)
w0 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 0 * weights_stride_y));
VEC_TYPE(3)
w1 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 1 * weights_stride_y));
VEC_TYPE(3)
w2 = vload3(0, (__global WEIGHTS_TYPE *)(weights_addr + 2 * weights_stride_y));
const int output_multiplier = *((__global int *)vector_offset(&output_multipliers, 0));
const int output_shift = *((__global int *)vector_offset(&output_shifts, 0));
VEC_TYPE(8)
left0, middle0, right0;
VEC_TYPE(8)
left1, middle1, right1;
VEC_TYPE(8)
left2, middle2, right2;
int8 values0 = 0;
int8 sum0 = 0;
GET_VALUES(src.ptr + 0 * src_stride_y, left0, middle0, right0);
GET_VALUES(src.ptr + DILATION_Y * src_stride_y, left1, middle1, right1);
GET_VALUES(src.ptr + 2 * DILATION_Y * src_stride_y, left2, middle2, right2);
#if WEIGHTS_OFFSET != 0
sum0 += convert_int8(left0) + convert_int8(middle0) + convert_int8(right0);
sum0 += convert_int8(left1) + convert_int8(middle1) + convert_int8(right1);
sum0 += convert_int8(left2) + convert_int8(middle2) + convert_int8(right2);
#endif /* WEIGHTS_OFFSET != 0 */
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
// If conv_stride_y is equals to 1, we compute two output rows
VEC_TYPE(8)
left3, middle3, right3;
int8 values1 = 0;
int8 sum1 = 0;
GET_VALUES(src.ptr + 3 * src_stride_y, left3, middle3, right3);
#if WEIGHTS_OFFSET != 0
sum1 += convert_int8(left1) + convert_int8(middle1) + convert_int8(right1);
sum1 += convert_int8(left2) + convert_int8(middle2) + convert_int8(right2);
sum1 += convert_int8(left3) + convert_int8(middle3) + convert_int8(right3);
#endif /* WEIGHTS_OFFSET != 0 */
#endif // CONV_STRIDE_Y == 1 && DILATION_Y==1
ARM_DOT((VEC_TYPE(4))(left0.s0, middle0.s0, right0.s0, left1.s0), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s0);
ARM_DOT((VEC_TYPE(4))(middle1.s0, right1.s0, left2.s0, middle2.s0), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s0);
values0.s0 += right2.s0 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s1, middle0.s1, right0.s1, left1.s1), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s1);
ARM_DOT((VEC_TYPE(4))(middle1.s1, right1.s1, left2.s1, middle2.s1), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s1);
values0.s1 += right2.s1 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s2, middle0.s2, right0.s2, left1.s2), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s2);
ARM_DOT((VEC_TYPE(4))(middle1.s2, right1.s2, left2.s2, middle2.s2), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s2);
values0.s2 += right2.s2 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s3, middle0.s3, right0.s3, left1.s3), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s3);
ARM_DOT((VEC_TYPE(4))(middle1.s3, right1.s3, left2.s3, middle2.s3), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s3);
values0.s3 += right2.s3 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s4, middle0.s4, right0.s4, left1.s4), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s4);
ARM_DOT((VEC_TYPE(4))(middle1.s4, right1.s4, left2.s4, middle2.s4), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s4);
values0.s4 += right2.s4 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s5, middle0.s5, right0.s5, left1.s5), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s5);
ARM_DOT((VEC_TYPE(4))(middle1.s5, right1.s5, left2.s5, middle2.s5), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s5);
values0.s5 += right2.s5 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s6, middle0.s6, right0.s6, left1.s6), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s6);
ARM_DOT((VEC_TYPE(4))(middle1.s6, right1.s6, left2.s6, middle2.s6), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s6);
values0.s6 += right2.s6 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left0.s7, middle0.s7, right0.s7, left1.s7), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values0.s7);
ARM_DOT((VEC_TYPE(4))(middle1.s7, right1.s7, left2.s7, middle2.s7), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values0.s7);
values0.s7 += right2.s7 * w2.s2;
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
ARM_DOT((VEC_TYPE(4))(left1.s0, middle1.s0, right1.s0, left2.s0), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s0);
ARM_DOT((VEC_TYPE(4))(middle2.s0, right2.s0, left3.s0, middle3.s0), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s0);
values1.s0 += right3.s0 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s1, middle1.s1, right1.s1, left2.s1), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s1);
ARM_DOT((VEC_TYPE(4))(middle2.s1, right2.s1, left3.s1, middle3.s1), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s1);
values1.s1 += right3.s1 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s2, middle1.s2, right1.s2, left2.s2), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s2);
ARM_DOT((VEC_TYPE(4))(middle2.s2, right2.s2, left3.s2, middle3.s2), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s2);
values1.s2 += right3.s2 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s3, middle1.s3, right1.s3, left2.s3), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s3);
ARM_DOT((VEC_TYPE(4))(middle2.s3, right2.s3, left3.s3, middle3.s3), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s3);
values1.s3 += right3.s3 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s4, middle1.s4, right1.s4, left2.s4), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s4);
ARM_DOT((VEC_TYPE(4))(middle2.s4, right2.s4, left3.s4, middle3.s4), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s4);
values1.s4 += right3.s4 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s5, middle1.s5, right1.s5, left2.s5), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s5);
ARM_DOT((VEC_TYPE(4))(middle2.s5, right2.s5, left3.s5, middle3.s5), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s5);
values1.s5 += right3.s5 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s6, middle1.s6, right1.s6, left2.s6), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s6);
ARM_DOT((VEC_TYPE(4))(middle2.s6, right2.s6, left3.s6, middle3.s6), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s6);
values1.s6 += right3.s6 * w2.s2;
ARM_DOT((VEC_TYPE(4))(left1.s7, middle1.s7, right1.s7, left2.s7), (VEC_TYPE(4))(w0.s0, w0.s1, w0.s2, w1.s0), values1.s7);
ARM_DOT((VEC_TYPE(4))(middle2.s7, right2.s7, left3.s7, middle3.s7), (VEC_TYPE(4))(w1.s1, w1.s2, w2.s0, w2.s1), values1.s7);
values1.s7 += right3.s7 * w2.s2;
#endif // CONV_STRIDE_Y == 1 && DILATION_Y==1
#if defined(HAS_BIAS)
values0 += (int8)(bias_value);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(bias_value);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif //defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
values0 += sum0 * (int8)(WEIGHTS_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum1 * (int8)(WEIGHTS_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
WEIGHTS_PROMOTED_TYPE sum_weights = 0;
VEC_WEIGHTS_PROMOTED_TYPE(3)
tmp_we = CONVERT(w0, VEC_WEIGHTS_PROMOTED_TYPE(3)) + CONVERT(w1, VEC_WEIGHTS_PROMOTED_TYPE(3)) + CONVERT(w2, VEC_WEIGHTS_PROMOTED_TYPE(3));
sum_weights += tmp_we.s0 + tmp_we.s1 + tmp_we.s2;
values0 += sum_weights * (int8)(INPUT_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum_weights * (int8)(INPUT_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
values0 += (int8)(K_OFFSET);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(K_OFFSET);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
values0 = CONVERT(round(CONVERT(values0, float8) * (float8)REAL_MULTIPLIER), int8);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
int8 res0_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, output_multiplier, output_shift, 8);
int8 res0_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, output_multiplier, output_shift, 8);
values0 = select(res0_shift_lt0, res0_shift_gt0, (int8)(output_shift) >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#else // OUTPUT_SHIFT < 0
values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#endif // OUTPUT_OFFSET < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
values0 += (int8)OUTPUT_OFFSET;
VEC_TYPE(8)
res0 = CONVERT_SAT(values0, VEC_TYPE(8));
vstore8(ACTIVATION_FUNC(res0), 0, dst.ptr);
#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
#if defined(REAL_MULTIPLIER)
values1 = CONVERT(round(CONVERT(values1, float8) * (float8)REAL_MULTIPLIER), int8);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
int8 res1_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values1, output_multiplier, output_shift, 8);
int8 res1_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values1, output_multiplier, output_shift, 8);
values1 = select(res1_shift_lt0, res1_shift_gt0, (int8)(output_shift) >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
values1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#else // OUTPUT_SHIFT < 0
values1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#endif // OUTPUT_OFFSET < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
values1 += (int8)OUTPUT_OFFSET;
VEC_TYPE(8)
res1 = CONVERT_SAT(values1, VEC_TYPE(8));
vstore8(ACTIVATION_FUNC(res1), 0, dst.ptr + dst_stride_y);
#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
}
#endif // !defined(IS_DOT8)
#endif /* defined(CONV_STRIDE_Y) && defined(CONV_STRIDE_X) && defined(DEPTH_MULTIPLIER) && defined(DST_CHANNELS) */
#if defined(VEC_SIZE) && defined(SRC_DIM_1) && defined(SRC_DIM_2) && defined(CONV_PAD_TOP) && defined(CONV_PAD_LEFT)
#define asymm_mult_by_quant_multiplier_less_than_one(x, y, z) ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(x, y, z, VEC_SIZE)
#define MULTIPLY_ADD(x, y, acc) acc += CONVERT(CONVERT(x, VEC_WEIGHTS_PROMOTED_TYPE(VEC_SIZE)) * CONVERT(y, VEC_WEIGHTS_PROMOTED_TYPE(VEC_SIZE)), VEC_INT)
#if WEIGHTS_OFFSET != 0
#define MULTIPLY_ADD_ACCUMULATE(x, y, acc, sum) \
({ \
sum += CONVERT(x, VEC_INT); \
MULTIPLY_ADD(x, y, acc); \
})
#else /* WEIGHTS_OFFSET != 0 */
#define MULTIPLY_ADD_ACCUMULATE(x, y, acc, sum) MULTIPLY_ADD(x, y, acc)
#endif /* WEIGHTS_OFFSET != 0 */
#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
#define DOT_PRODUCT(acc, val0, val1, val2, val3, val4, val5, val6, val7, val8, w0, w1) \
({ \
ARM_DOT((VEC_TYPE(4))(val0, val1, val2, val3), w0.s0123, acc); \
ARM_DOT((VEC_TYPE(4))(val4, val5, val6, val7), w0.s4567, acc); \
acc += val8 * w1; \
})
#define DOT_PRODUCT_REDUCTION(sum, val0, val1, val2, val3, val4, val5, val6, val7, val8) \
({ \
sum = val0; \
ARM_DOT((VEC_TYPE(4))(val1, val2, val3, val4), (VEC_TYPE(4))1, sum); \
ARM_DOT((VEC_TYPE(4))(val5, val6, val7, val8), (VEC_TYPE(4))1, sum); \
})
#define DOT_PRODUCT_REDUCTION_WEIGHTS(sum, w0, w1) \
({ \
sum = w1; \
ARM_DOT(w0.s0123, (VEC_TYPE(4))1, sum); \
ARM_DOT(w0.s4567, (VEC_TYPE(4))1, sum); \
})
#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
#if defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && VEC_SIZE == 4
/** This function computes the depthwise convolution quantized for NHWC data layout when the stride along the width or height is not 1.
*
* @note This kernel assumes VEC_SIZE is 4.
* @note The weights tensor is expected to be reshaped using @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel.
* @note The number of elements read per thread must be passed at compile time using -DVEC_SIZE (e.g. -DVEC_SIZE=2)
* @note Dimension two of the input tensor (height for NHWC data layout) must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM_2=112)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1)
* @note The convolution stride along the width must be passed at compile time using -DCONV_STRIDE_X (e.g. -DCONV_STRIDE_Y=X)
* @note The convolution stride along the height must be passed at compile time using -DCONV_STRIDE_Y (e.g. -DCONV_STRIDE_Y=1)
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_y * number of elements along Z processed per workitem(in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_step_w dst_stride_w * number of elements along W 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 reshaped. Supported data types: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
* @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_offset_first_element_in_bytes The offset of the first element in the weights tensor
* @param[in] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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] max_offset Max offset for the input tensor
*/
__kernel void dwc_3x3_reshaped_quantized8_nhwc(
TENSOR4D_DECLARATION(src),
TENSOR4D_DECLARATION(dst),
IMAGE_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts),
#if defined(HAS_BIAS)
VECTOR_DECLARATION(biases),
#endif /* defined(HAS_BIAS) */
int max_offset)
{
const int x = get_global_id(0); // channels
const int y = get_global_id(1); // spatial coordinate x
#if defined(DST_DEPTH)
int z = get_global_id(2) % (int)DST_DEPTH; // spatial coordinate y
int b = get_global_id(2) / (int)DST_DEPTH; // batch
#else // defined(DST_DEPTH)
int z = get_global_id(2); // spatial coordinate y
#endif // defined(DST_DEPTH)
__global uchar *weights_addr = weights_ptr + weights_offset_first_element_in_bytes + x * weights_stride_y;
#if defined(DST_DEPTH)
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE + b * src_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE;
#endif /* defined(DST_DEPTH) */
int z_coord = 0;
int4 offset = 0;
int4 y_coord = ((int4)(y * CONV_STRIDE_X) + (int4)(0, DILATION_X * 1, DILATION_X * 2, DILATION_X * 3)) - (int)CONV_PAD_LEFT;
// Only for y = 0 we can have a negative coordinate. If so, we convert it to SRC_DIM_1
y_coord.s0 = min((uint)y_coord.s0, (uint)SRC_DIM_1);
y_coord.s1 = min((uint)y_coord.s1, (uint)SRC_DIM_1);
y_coord.s2 = min((uint)y_coord.s2, (uint)SRC_DIM_1);
y_coord.s3 = min((uint)y_coord.s3, (uint)SRC_DIM_1);
int4 y_offset = convert_int4(y_coord * (int)src_stride_y);
// We compute VEC_SIZEx1x1 [C,W,H] elements
VEC_INT acc = 0, sum = 0;
// Load weights
VEC_DATA_TYPE(WEIGHTS_TYPE, 16)
w0_tmp = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr));
VEC_DATA_TYPE(WEIGHTS_TYPE, 16)
w1_tmp = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr + 16));
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w8 = VLOAD(4)(0, (__global WEIGHTS_TYPE *)(weights_addr + 2 * 16));
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w0 = w0_tmp.s0123;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w1 = w0_tmp.s4567;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w2 = w0_tmp.s89AB;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w3 = w0_tmp.sCDEF;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w4 = w1_tmp.s0123;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w5 = w1_tmp.s4567;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w6 = w1_tmp.s89AB;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w7 = w1_tmp.sCDEF;
#if INPUT_OFFSET != 0
VEC_INT sum_we = CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT)
+ CONVERT(w3, VEC_INT) + CONVERT(w4, VEC_INT) + CONVERT(w5, VEC_INT)
+ CONVERT(w6, VEC_INT) + CONVERT(w7, VEC_INT) + CONVERT(w8, VEC_INT);
#endif /* INPUT_OFFSET != 0 */
// Load input values
// z == 0
// Clamp z_coord as for z = 0, it can be negative
// z_coord is casted to unsigned int in order to use just a min() operation
// A "-1" 32 bit signed variable converted to unsigned gives 4294967295
z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP;
z_coord = min((uint)z_coord, (uint)SRC_DIM_2);
offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values0 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values1 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values2 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
// z == 1
// z_coord can be only negative for z = 0 so we do not need to clamp it
// Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset
z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y;
offset = y_offset + (int4)(z_coord * src_stride_z);
VEC_TYPE(VEC_SIZE)
values3 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values4 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values5 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
// z == 2
// Offset can be out-of-bound so we need to check if it is greater than max_offset
z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y * 2;
offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values6 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values7 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values8 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
MULTIPLY_ADD_ACCUMULATE(values0, w0, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values1, w1, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values2, w2, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values3, w3, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values4, w4, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values5, w5, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values6, w6, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values7, w7, acc, sum);
MULTIPLY_ADD_ACCUMULATE(values8, w8, acc, sum);
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT(biases);
VEC_INT bias_values = VLOAD(VEC_SIZE)(0, (__global int *)biases.ptr);
acc += bias_values;
#endif // defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
acc += WEIGHTS_OFFSET * sum;
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
acc += INPUT_OFFSET * sum_we;
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
acc += (VEC_INT)K_OFFSET;
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
acc = CONVERT(round(CONVERT(acc, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
Vector output_multipliers = CONVERT_TO_VECTOR_STRUCT(output_multipliers);
Vector output_shifts = CONVERT_TO_VECTOR_STRUCT(output_shifts);
VEC_INT output_multiplier = VLOAD(VEC_SIZE)(0, (__global int *)output_multipliers.ptr);
VEC_INT output_shift = VLOAD(VEC_SIZE)(0, (__global int *)output_shifts.ptr);
VEC_INT res_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc, output_multiplier, output_shift, VEC_SIZE);
VEC_INT res_shift_gt0 = asymm_mult_by_quant_multiplier_less_than_one(acc, output_multiplier, output_shift);
acc = select(res_shift_lt0, res_shift_gt0, output_shift >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
acc = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
#else // OUTPUT_SHIFT < 0
acc = asymm_mult_by_quant_multiplier_less_than_one(acc, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
#endif // OUTPUT_SHIFT < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
acc += (VEC_INT)OUTPUT_OFFSET;
VEC_TYPE(VEC_SIZE)
res = CONVERT_SAT(acc, VEC_TYPE(VEC_SIZE));
#if defined(DST_DEPTH)
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + z * dst_step_z + b * dst_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + z * dst_step_z;
#endif /* defined(DST_DEPTH) */
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res), 0, (__global DATA_TYPE *)(dst_addr));
}
#endif // defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y)
#if defined(NUM_ROWS_PROCESSED) && defined(NUM_PLANES_PROCESSED) && VEC_SIZE == 4
/** This function computes the depthwise convolution quantized for NHWC data layout when the stride along the width and height is 1.
*
* @note This kernel assumes VEC_SIZE is 4.
* @note The weights tensor is expected to be reshaped using @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel.
* @note The number of elements read per thread must be passed at compile time using -DVEC_SIZE (e.g. -DVEC_SIZE=2)
* @note Dimension two of the input tensor (height for NHWC data layout) must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM_2=112)
* @note The number of rows processed per thread must be passed at compile time using -DNUM_ROWS_PROCESSED (i.e. -DNUM_ROWS_PROCESSED=2)
* @note The number of planes processed per thread must be passed at compile time using -DNUM_PLANES_PROCESSED (i.e. -DNUM_PLANES_PROCESSED=2)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1).
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_y * number of elements along Z processed per workitem(in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_step_w dst_stride_w * number of elements along W 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/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
* @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_offset_first_element_in_bytes The offset of the first element in the weights tensor
* @param[in] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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] max_offset Max offset for the input tensor
*/
__kernel void dwc_3x3_reshaped_quantized8_stride1_nhwc(
TENSOR4D_DECLARATION(src),
TENSOR4D_DECLARATION(dst),
IMAGE_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts),
#if defined(HAS_BIAS)
VECTOR_DECLARATION(biases),
#endif /* defined(HAS_BIAS) */
int max_offset)
{
int x = get_global_id(0);
int y = get_global_id(1);
#if defined(DST_DEPTH)
int z = get_global_id(2) % (int)DST_DEPTH; // spatial coordinate y
int b = get_global_id(2) / (int)DST_DEPTH; // batch
#else // defined(DST_DEPTH)
int z = get_global_id(2); // spatial coordinate y
#endif // defined(DST_DEPTH)
__global uchar *weights_addr = weights_ptr + weights_offset_first_element_in_bytes + x * weights_stride_y;
#if defined(DST_DEPTH)
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE + b * src_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE;
#endif /* defined(DST_DEPTH) */
int z_coord = 0;
int4 offset = 0;
int4 y_coord = ((int4)(y * NUM_ROWS_PROCESSED) + (int4)(0, 1, 2, 3)) - (int)CONV_PAD_LEFT;
// Only for y = 0 we can have a negative coordinate. If so, we convert it to SRC_DIM_1
y_coord.s0 = min((uint)y_coord.s0, (uint)SRC_DIM_1);
y_coord.s1 = min((uint)y_coord.s1, (uint)SRC_DIM_1);
y_coord.s2 = min((uint)y_coord.s2, (uint)SRC_DIM_1);
y_coord.s3 = min((uint)y_coord.s3, (uint)SRC_DIM_1);
int4 y_offset = convert_int4(y_coord * (int)src_stride_y);
// We compute 4x2x2 [C,W,H] elements
VEC_INT acc0 = 0, sum0 = 0;
VEC_INT acc1 = 0, sum1 = 0;
VEC_INT acc2 = 0, sum2 = 0;
VEC_INT acc3 = 0, sum3 = 0;
// Load weights
VEC_DATA_TYPE(WEIGHTS_TYPE, 16)
w0_tmp = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr));
VEC_DATA_TYPE(WEIGHTS_TYPE, 16)
w1_tmp = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr + 16));
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w8 = VLOAD(4)(0, (__global WEIGHTS_TYPE *)(weights_addr + 2 * 16));
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w0 = w0_tmp.s0123;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w1 = w0_tmp.s4567;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w2 = w0_tmp.s89AB;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w3 = w0_tmp.sCDEF;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w4 = w1_tmp.s0123;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w5 = w1_tmp.s4567;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w6 = w1_tmp.s89AB;
VEC_DATA_TYPE(WEIGHTS_TYPE, 4)
w7 = w1_tmp.sCDEF;
#if INPUT_OFFSET != 0
VEC_INT sum_we = CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT)
+ CONVERT(w3, VEC_INT) + CONVERT(w4, VEC_INT) + CONVERT(w5, VEC_INT)
+ CONVERT(w6, VEC_INT) + CONVERT(w7, VEC_INT) + CONVERT(w8, VEC_INT);
#endif /* INPUT_OFFSET != 0 */
// Load input values
// z == 0
// Clamp z_coord as for z = 0, it can be negative
// z_coord is casted to unsigned int in order to use just a min() operation
// A "-1" 32 bit signed variable converted to unsigned gives 4294967295
z_coord = z * (int)NUM_PLANES_PROCESSED - (int)CONV_PAD_TOP;
z_coord = min((uint)z_coord, (uint)SRC_DIM_2);
offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values0 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values1 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values2 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values3 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
// z == 1
// z_coord can be only negative for z = 0 so we do not need to clamp it
// Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset
z_coord = z * (int)NUM_PLANES_PROCESSED - (int)CONV_PAD_TOP + 1;
offset = y_offset + (int4)(z_coord * src_stride_z);
VEC_TYPE(VEC_SIZE)
values4 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values5 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values6 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values7 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
// z == 2
// After z = 1 we can simply add src_stride_z to offset without updating z_coord
// However offset can be out-of-bound so we need to check if it is greater than max_offset
offset += (int4)src_stride_z;
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values8 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values9 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values10 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values11 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
// z == 3
// After z = 1 we can simply add src_stride_z to offset without updating z_coord
// However offset can be out-of-bound so we need to check if it is greater than max_offset
offset += (int4)(src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values12 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values13 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values14 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values15 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
MULTIPLY_ADD_ACCUMULATE(values0, w0, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values1, w1, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values2, w2, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values1, w0, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values2, w1, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values3, w2, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values4, w3, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values5, w4, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values6, w5, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values5, w3, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values6, w4, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values7, w5, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values8, w6, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values9, w7, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values10, w8, acc0, sum0);
MULTIPLY_ADD_ACCUMULATE(values9, w6, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values10, w7, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values11, w8, acc1, sum1);
MULTIPLY_ADD_ACCUMULATE(values4, w0, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values5, w1, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values6, w2, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values5, w0, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values6, w1, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values7, w2, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values8, w3, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values9, w4, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values10, w5, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values9, w3, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values10, w4, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values11, w5, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values12, w6, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values13, w7, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values14, w8, acc2, sum2);
MULTIPLY_ADD_ACCUMULATE(values13, w6, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values14, w7, acc3, sum3);
MULTIPLY_ADD_ACCUMULATE(values15, w8, acc3, sum3);
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT(biases);
VEC_INT bias_values = VLOAD(VEC_SIZE)(0, (__global int *)biases.ptr);
acc0 += bias_values;
acc1 += bias_values;
acc2 += bias_values;
acc3 += bias_values;
#endif /* defined(HAS_BIAS) */
#if WEIGHTS_OFFSET != 0
acc0 += WEIGHTS_OFFSET * sum0;
acc1 += WEIGHTS_OFFSET * sum1;
acc2 += WEIGHTS_OFFSET * sum2;
acc3 += WEIGHTS_OFFSET * sum3;
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
VEC_INT offs = INPUT_OFFSET * sum_we;
acc0 += offs;
acc1 += offs;
acc2 += offs;
acc3 += offs;
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
acc0 += (VEC_INT)K_OFFSET;
acc1 += (VEC_INT)K_OFFSET;
acc2 += (VEC_INT)K_OFFSET;
acc3 += (VEC_INT)K_OFFSET;
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
acc0 = CONVERT(round(CONVERT(acc0, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
acc1 = CONVERT(round(CONVERT(acc1, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
acc2 = CONVERT(round(CONVERT(acc2, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
acc3 = CONVERT(round(CONVERT(acc3, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
#else // defined(REAL_MULTIPLIER)
#if defined(PER_CHANNEL_QUANTIZATION)
Vector output_multipliers = CONVERT_TO_VECTOR_STRUCT(output_multipliers);
Vector output_shifts = CONVERT_TO_VECTOR_STRUCT(output_shifts);
VEC_INT output_multiplier = VLOAD(VEC_SIZE)(0, (__global int *)output_multipliers.ptr);
VEC_INT output_shift = VLOAD(VEC_SIZE)(0, (__global int *)output_shifts.ptr);
VEC_INT res0_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc0, output_multiplier, output_shift, VEC_SIZE);
VEC_INT res1_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc1, output_multiplier, output_shift, VEC_SIZE);
VEC_INT res2_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc2, output_multiplier, output_shift, VEC_SIZE);
VEC_INT res3_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc3, output_multiplier, output_shift, VEC_SIZE);
VEC_INT res0_shift_gt0 = asymm_mult_by_quant_multiplier_less_than_one(acc0, output_multiplier, output_shift);
VEC_INT res1_shift_gt0 = asymm_mult_by_quant_multiplier_less_than_one(acc1, output_multiplier, output_shift);
VEC_INT res2_shift_gt0 = asymm_mult_by_quant_multiplier_less_than_one(acc2, output_multiplier, output_shift);
VEC_INT res3_shift_gt0 = asymm_mult_by_quant_multiplier_less_than_one(acc3, output_multiplier, output_shift);
acc0 = select(res0_shift_lt0, res0_shift_gt0, output_shift >= 0);
acc1 = select(res1_shift_lt0, res1_shift_gt0, output_shift >= 0);
acc2 = select(res2_shift_lt0, res2_shift_gt0, output_shift >= 0);
acc3 = select(res3_shift_lt0, res3_shift_gt0, output_shift >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
acc0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
acc1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
acc2 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc2, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
acc3 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc3, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
#else // OUTPUT_SHIFT < 0
acc0 = asymm_mult_by_quant_multiplier_less_than_one(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
acc1 = asymm_mult_by_quant_multiplier_less_than_one(acc1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
acc2 = asymm_mult_by_quant_multiplier_less_than_one(acc2, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
acc3 = asymm_mult_by_quant_multiplier_less_than_one(acc3, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
#endif // OUTPUT_SHIFT < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
#endif // defined(REAL_MULTIPLIER)
acc0 += (VEC_INT)OUTPUT_OFFSET;
acc1 += (VEC_INT)OUTPUT_OFFSET;
acc2 += (VEC_INT)OUTPUT_OFFSET;
acc3 += (VEC_INT)OUTPUT_OFFSET;
VEC_TYPE(VEC_SIZE)
res0 = CONVERT_SAT(acc0, VEC_TYPE(VEC_SIZE));
VEC_TYPE(VEC_SIZE)
res1 = CONVERT_SAT(acc1, VEC_TYPE(VEC_SIZE));
VEC_TYPE(VEC_SIZE)
res2 = CONVERT_SAT(acc2, VEC_TYPE(VEC_SIZE));
VEC_TYPE(VEC_SIZE)
res3 = CONVERT_SAT(acc3, VEC_TYPE(VEC_SIZE));
#if defined(DST_DEPTH)
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + (z * NUM_PLANES_PROCESSED) * dst_step_z + b * dst_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + (z * NUM_PLANES_PROCESSED) * dst_step_z;
#endif /* defined(DST_DEPTH) */
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res0), 0, dst_addr + 0 * dst_stride_y);
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res1), 0, dst_addr + 1 * dst_stride_y);
#if((DST_DIM_2 % NUM_PLANES_PROCESSED) != 0)
if((z * NUM_PLANES_PROCESSED + 1) < DST_DIM_2)
#endif // ((DST_DIM_2 % NUM_PLANES_PROCESSED) != 0)
{
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res2), 0, (__global DATA_TYPE *)(dst_addr + 0 * dst_stride_y + 1 * dst_stride_z));
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res3), 0, (__global DATA_TYPE *)(dst_addr + 1 * dst_stride_y + 1 * dst_stride_z));
}
}
#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) && VEC_SIZE == 4
/** This function computes the depthwise convolution quantized for NHWC data layout when the stride along the width and height is 1 using dot product.
*
* @note Per-channel quantization is not supported by this kernel.
* @note This kernel assumes VEC_SIZE is 4.
* @note The weights tensor is expected to be reshaped using @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel.
* @note The number of elements read per thread must be passed at compile time using -DVEC_SIZE (e.g. -DVEC_SIZE=2)
* @note Dimension two of the input tensor (height for NHWC data layout) must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM_2=112)
* @note The number of rows processed per thread must be passed at compile time using -DNUM_ROWS_PROCESSED (i.e. -DNUM_ROWS_PROCESSED=2)
* @note The number of planes processed per thread must be passed at compile time using -DNUM_PLANES_PROCESSED (i.e. -DNUM_PLANES_PROCESSED=2)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1).
* @note If REAL_MULTIPLIER is passed at compile time (i.e. -DREAL_MULTIPLIER=1.355f), the final quantization is performed using a floating point multiplication.
* If not, the quantization will be performed using a fixed point multiplication
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_y * number of elements along Z processed per workitem(in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_step_w dst_stride_w * number of elements along W 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: same as @p src_ptr
* @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_offset_first_element_in_bytes The offset of the first element in the weights tensor
* @param[in] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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] max_offset The maximum allowed offset for the input tensor
*/
__kernel void dwc_3x3_reshaped_quantized8_dot8_stride1_nhwc(
TENSOR4D_DECLARATION(src),
TENSOR4D_DECLARATION(dst),
IMAGE_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts),
#if defined(HAS_BIAS)
VECTOR_DECLARATION(biases),
#endif // defined(HAS_BIAS)
int max_offset)
{
int x = get_global_id(0);
int y = get_global_id(1);
#if defined(DST_DEPTH)
int z = get_global_id(2) % (int)DST_DEPTH; // spatial coordinate y
int b = get_global_id(2) / (int)DST_DEPTH; // batch
#else // defined(DST_DEPTH)
int z = get_global_id(2); // spatial coordinate y
#endif // defined(DST_DEPTH)
__global uchar *weights_addr = weights_ptr + weights_offset_first_element_in_bytes + x * weights_stride_y;
#if defined(DST_DEPTH)
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE + b * src_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * VEC_SIZE;
#endif /* defined(DST_DEPTH) */
int z_coord = 0;
int4 offset = 0;
int4 y_coord = ((int4)(y * NUM_ROWS_PROCESSED) + (int4)(0, 1, 2, 3)) - (int)CONV_PAD_LEFT;
// Only for y = 0 we can have a negative coordinate. If so, we convert it to SRC_DIM_1
y_coord.s0 = min((uint)y_coord.s0, (uint)SRC_DIM_1);
y_coord.s1 = min((uint)y_coord.s1, (uint)SRC_DIM_1);
y_coord.s2 = min((uint)y_coord.s2, (uint)SRC_DIM_1);
y_coord.s3 = min((uint)y_coord.s3, (uint)SRC_DIM_1);
int4 y_offset = convert_int4(y_coord * (int)src_stride_y);
// We compute 4x2x1 [C,W,H] elements
VEC_INT acc0 = 0;
VEC_INT acc1 = 0;
VEC_INT sum0 = 0;
VEC_INT sum1 = 0;
// Load weights
VEC_TYPE(16)
w0 = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr));
VEC_TYPE(16)
w1 = VLOAD(16)(0, (__global WEIGHTS_TYPE *)(weights_addr + 16));
VEC_TYPE(4)
w2 = VLOAD(4)(0, (__global WEIGHTS_TYPE *)(weights_addr + 32));
#if INPUT_OFFSET != 0
// Initilize the final result with the weights reduction multiplied by INPUT_OFFSET
DOT_PRODUCT_REDUCTION_WEIGHTS(acc0.s0, w0.s01234567, w0.s8);
DOT_PRODUCT_REDUCTION_WEIGHTS(acc0.s1, (VEC_TYPE(8))((w0.s9ABC), (w0.sDEF), w1.s0), w1.s1);
DOT_PRODUCT_REDUCTION_WEIGHTS(acc0.s2, w1.s23456789, w1.sA);
DOT_PRODUCT_REDUCTION_WEIGHTS(acc0.s3, (VEC_TYPE(8))((w1.sBCD), (w1.sEF), (w2.s012)), w2.s3);
// Multiply the weights reduction with INPUT_OFFSET
acc0 = INPUT_OFFSET * acc0;
acc1 = acc0;
#endif // INPUT_OFFSET != 0
// Load input values
// z == 0
// Clamp z_coord as for z = 0, it can be negative
// z_coord is casted to unsigned int in order to use just a min() operation
// A "-1" 32 bit signed variable converted to unsigned gives 4294967295
z_coord = z - (int)CONV_PAD_TOP;
z_coord = min((uint)z_coord, (uint)SRC_DIM_2);
offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values0 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values1 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values2 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values3 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
// z == 1
// z_coord can be only negative for z = 0 so we do not need to clamp it
// Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset
z_coord = z - (int)CONV_PAD_TOP + 1;
offset = y_offset + (int4)(z_coord * src_stride_z);
VEC_TYPE(VEC_SIZE)
values4 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values5 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values6 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values7 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
// z == 2
// After z = 1 we can simply add src_stride_z to offset without updating z_coord
// However offset can be out-of-bound so we need to check if it is greater than max_offset
offset += (int4)src_stride_z;
offset = min(offset, (int4)max_offset);
VEC_TYPE(VEC_SIZE)
values8 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_TYPE(VEC_SIZE)
values9 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_TYPE(VEC_SIZE)
values10 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
VEC_TYPE(VEC_SIZE)
values11 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s3));
DOT_PRODUCT_REDUCTION(sum0.s0, values0.s0, values1.s0, values2.s0, values4.s0, values5.s0, values6.s0, values8.s0, values9.s0, values10.s0);
DOT_PRODUCT_REDUCTION(sum1.s0, values1.s0, values2.s0, values3.s0, values5.s0, values6.s0, values7.s0, values9.s0, values10.s0, values11.s0);
DOT_PRODUCT(acc0.s0, values0.s0, values1.s0, values2.s0, values4.s0, values5.s0, values6.s0, values8.s0, values9.s0, values10.s0, w0.s01234567, w0.s8);
DOT_PRODUCT(acc1.s0, values1.s0, values2.s0, values3.s0, values5.s0, values6.s0, values7.s0, values9.s0, values10.s0, values11.s0, w0.s01234567, w0.s8);
DOT_PRODUCT_REDUCTION(sum0.s1, values0.s1, values1.s1, values2.s1, values4.s1, values5.s1, values6.s1, values8.s1, values9.s1, values10.s1);
DOT_PRODUCT_REDUCTION(sum1.s1, values1.s1, values2.s1, values3.s1, values5.s1, values6.s1, values7.s1, values9.s1, values10.s1, values11.s1);
DOT_PRODUCT(acc0.s1, values0.s1, values1.s1, values2.s1, values4.s1, values5.s1, values6.s1, values8.s1, values9.s1, values10.s1, (VEC_TYPE(8))((w0.s9ABC), (w0.sDEF), w1.s0), w1.s1);
DOT_PRODUCT(acc1.s1, values1.s1, values2.s1, values3.s1, values5.s1, values6.s1, values7.s1, values9.s1, values10.s1, values11.s1, (VEC_TYPE(8))((w0.s9ABC), (w0.sDEF), w1.s0), w1.s1);
DOT_PRODUCT_REDUCTION(sum0.s2, values0.s2, values1.s2, values2.s2, values4.s2, values5.s2, values6.s2, values8.s2, values9.s2, values10.s2);
DOT_PRODUCT_REDUCTION(sum1.s2, values1.s2, values2.s2, values3.s2, values5.s2, values6.s2, values7.s2, values9.s2, values10.s2, values11.s2);
DOT_PRODUCT(acc0.s2, values0.s2, values1.s2, values2.s2, values4.s2, values5.s2, values6.s2, values8.s2, values9.s2, values10.s2, w1.s23456789, w1.sA);
DOT_PRODUCT(acc1.s2, values1.s2, values2.s2, values3.s2, values5.s2, values6.s2, values7.s2, values9.s2, values10.s2, values11.s2, w1.s23456789, w1.sA);
DOT_PRODUCT_REDUCTION(sum0.s3, values0.s3, values1.s3, values2.s3, values4.s3, values5.s3, values6.s3, values8.s3, values9.s3, values10.s3);
DOT_PRODUCT_REDUCTION(sum1.s3, values1.s3, values2.s3, values3.s3, values5.s3, values6.s3, values7.s3, values9.s3, values10.s3, values11.s3);
DOT_PRODUCT(acc0.s3, values0.s3, values1.s3, values2.s3, values4.s3, values5.s3, values6.s3, values8.s3, values9.s3, values10.s3, (VEC_TYPE(8))((w1.sBCD), (w1.sEF), (w2.s012)), w2.s3);
DOT_PRODUCT(acc1.s3, values1.s3, values2.s3, values3.s3, values5.s3, values6.s3, values7.s3, values9.s3, values10.s3, values11.s3, (VEC_TYPE(8))((w1.sBCD), (w1.sEF), (w2.s012)), w2.s3);
#if defined(HAS_BIAS)
Vector biases = CONVERT_TO_VECTOR_STRUCT(biases);
VEC_INT bias_values = VLOAD(VEC_SIZE)(0, (__global int *)biases.ptr);
acc0 += bias_values;
acc1 += bias_values;
#endif // defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
acc0 += WEIGHTS_OFFSET * sum0;
acc1 += WEIGHTS_OFFSET * sum1;
#endif // WEIGHTS_OFFSET != 0
#if K_OFFSET != 0
acc0 += (VEC_INT)K_OFFSET;
acc1 += (VEC_INT)K_OFFSET;
#endif // K_OFFSET != 0
#if defined(REAL_MULTIPLIER)
acc0 = CONVERT(round(CONVERT(acc0, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
acc1 = CONVERT(round(CONVERT(acc1, VEC_FLOAT) * (VEC_FLOAT)REAL_MULTIPLIER), VEC_INT);
#else // defined(REAL_MULTIPLIER)
#if OUTPUT_SHIFT < 0
acc0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
acc1 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(acc1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, VEC_SIZE);
#else // OUTPUT_SHIFT < 0
acc0 = asymm_mult_by_quant_multiplier_less_than_one(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
acc1 = asymm_mult_by_quant_multiplier_less_than_one(acc1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT);
#endif // OUTPUT_SHIFT < 0
#endif // defined(REAL_MULTIPLIER)
acc0 += (VEC_INT)OUTPUT_OFFSET;
acc1 += (VEC_INT)OUTPUT_OFFSET;
VEC_TYPE(VEC_SIZE)
res0 = CONVERT_SAT(acc0, VEC_TYPE(VEC_SIZE));
VEC_TYPE(VEC_SIZE)
res1 = CONVERT_SAT(acc1, VEC_TYPE(VEC_SIZE));
#if defined(DST_DEPTH)
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + z * dst_step_z + b * dst_stride_w;
#else /* defined(DST_DEPTH) */
__global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + z * dst_step_z;
#endif /* defined(DST_DEPTH) */
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res0), 0, (__global DATA_TYPE *)(dst_addr + 0 * dst_stride_y));
VSTORE(VEC_SIZE)
(ACTIVATION_FUNC(res1), 0, (__global DATA_TYPE *)(dst_addr + 1 * dst_stride_y));
}
#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) && VEC_SIZE==4
#endif // defined(NUM_ROWS_PROCESSED) && defined(NUM_PLANES_PROCESSED)
#endif // defined(VEC_SIZE) && defined(SRC_DIM_1) && defined(SRC_DIM_2) && defined(CONV_PAD_TOP) && defined(CONV_PAD_LEFT)
#endif // defined(WEIGHTS_PROMOTED_TYPE)
#endif // defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && ((defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT)) || defined(REAL_MULTIPLIER))
#if defined(SRC_DIM1) && defined(SRC_DIM2) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(N0) && defined(DILATION_X) && defined(DILATION_Y) && defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(CONV_PAD_LEFT) && defined(CONV_PAD_TOP) && defined(INPUT_OFFSET) && defined(WEIGHTS_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_SHIFT) && defined(OUTPUT_MULTIPLIER) && defined(VEC_SIZE_LEFTOVER)
/** This function computes the depthwise convolution for NHWC data layout. This kernel assumes that the weights tensor is NOT reshaped
*
* @note The number of elements processed must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note The depth multiplier must be passed at compile time using -DDEPTH_MULTIPLIER (e.g. -DDEPTH_MULTIPLIER=1)
* @note The first dimension of the input tensor must be passed at compile time using -DSRC_DIM1 (e.g. -DSRC_DIM1=112)
* @note The second dimension of the input tensor must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM2=80)
* @note The kernel width must be passed at compile time using -DKERNEL_WIDTH (e.g. -DKERNEL_WIDTH=5)
* @note The kernel height must be passed at compile time using -DKERNEL_HEIGHT (e.g. -DKERNEL_HEIGHT=5)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1)
* @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1)
* @note The convolution stride along the width must be passed at compile time using -DCONV_STRIDE_X (e.g. -DCONV_STRIDE_Y=X)
* @note The convolution stride along the height must be passed at compile time using -DCONV_STRIDE_Y (e.g. -DCONV_STRIDE_Y=1)
* @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE=3. It is defined as the remainder between the input's first dimension and VEC_SIZE
* @note It is possible to select the activation function to apply using -DACTIVATION_TYPE e.g. -DACTIVATION_TYPE=relu
* @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
* @param[in] src_stride_x Stride of the source tensor 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 tensor 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_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_y * number of elements along Z processed per workitem(in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @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_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_step_w dst_stride_w * number of elements along W 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/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
* @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] output_multipliers_ptr Pointer to the output multipliers vector. Supported data types: S32
* @param[in] output_multipliers_stride_x Stride of the output multipliers vector in X dimension (in bytes)
* @param[in] output_multipliers_step_x output_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_multipliers_offset_first_element_in_bytes The offset of the first element in the output multipliers vector
* @param[in] output_shifts_ptr Pointer to the output shifts vector. Supported data types: S32
* @param[in] output_shifts_stride_x Stride of the output shifts vector in X dimension (in bytes)
* @param[in] output_shifts_step_x output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_shifts_offset_first_element_in_bytes The offset of the first element in the output shifts vector
* @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: S32
* @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
*/
__kernel void dwc_MxN_native_quantized8_nhwc(
TENSOR4D_DECLARATION(src),
TENSOR4D_DECLARATION(dst),
TENSOR3D_DECLARATION(weights),
VECTOR_DECLARATION(output_multipliers),
VECTOR_DECLARATION(output_shifts)
#if defined(HAS_BIAS)
,
VECTOR_DECLARATION(biases)
#endif // defined(HAS_BIAS)
)
{
int x_offs = max((int)(get_global_id(0) * N0 - (N0 - VEC_SIZE_LEFTOVER) % N0), 0);
int y = get_global_id(1); // spatial coordinate x
#if defined(DST_DEPTH)
int z = get_global_id(2) % (int)DST_DEPTH; // spatial coordinate y
int b = get_global_id(2) / (int)DST_DEPTH; // batch
#else // defined(DST_DEPTH)
int z = get_global_id(2); // spatial coordinate y
#endif // defined(DST_DEPTH)
__global uchar *s_addr = src_ptr + src_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE);
__global uchar *d_addr = dst_ptr + dst_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) * (int)DEPTH_MULTIPLIER + y * dst_stride_y + z * dst_stride_z;
__global uchar *w_addr = weights_ptr + weights_offset_first_element_in_bytes + x_offs * sizeof(WEIGHTS_TYPE) * (int)DEPTH_MULTIPLIER;
#if defined(HAS_BIAS)
__global uchar *b_addr = biases_ptr + biases_offset_first_element_in_bytes + x_offs * sizeof(int) * (int)DEPTH_MULTIPLIER;
#endif // defined(HAS_BIAS)
#if defined(PER_CHANNEL_QUANTIZATION)
__global uchar *out_mul_addr = output_multipliers_ptr + output_multipliers_offset_first_element_in_bytes + x_offs * sizeof(int) * (int)DEPTH_MULTIPLIER;
__global uchar *out_shift_addr = output_shifts_ptr + output_shifts_offset_first_element_in_bytes + x_offs * sizeof(int) * (int)DEPTH_MULTIPLIER;
#endif // defined(PER_CHANNEL_QUANTIZATION)
#if defined(DST_DEPTH)
s_addr += b * src_stride_w;
d_addr += b * dst_stride_w;
#endif // defined(DST_DEPTH)
#if DEPTH_MULTIPLIER > 1
for(int d = 0; d < (int)DEPTH_MULTIPLIER; ++d)
{
#endif // DEPTH_MULTIPLIER > 1
// Each work-item computes N0x1x1 elements
VEC_INT res = 0;
int x_coord = y * CONV_STRIDE_X - (int)CONV_PAD_LEFT;
int y_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP;
for(int yk = 0; yk < KERNEL_HEIGHT; ++yk)
{
if(y_coord >= 0 && y_coord < SRC_DIM2)
{
int x_coord_tmp = x_coord;
for(int xk = 0; xk < KERNEL_WIDTH; ++xk)
{
if(x_coord_tmp >= 0 && x_coord_tmp < SRC_DIM1)
{
int s_offset = x_coord_tmp * (int)src_stride_y + y_coord * (int)src_stride_z;
int w_offset = xk * weights_stride_y + yk * weights_stride_z;
// Load input and weights values
VEC_INT i = CONVERT(VLOAD(N0)(0, (__global DATA_TYPE *)(s_addr + s_offset)), VEC_INT);
VEC_INT w = CONVERT(VLOAD(N0)(0, (__global WEIGHTS_TYPE *)(w_addr + w_offset)), VEC_INT);
res += (i + (VEC_INT)INPUT_OFFSET) * (w + (VEC_INT)WEIGHTS_OFFSET);
}
x_coord_tmp += DILATION_X;
}
}
y_coord += DILATION_Y;
}
#if defined(HAS_BIAS)
VEC_INT bias = VLOAD(N0)(0, (__global int *)(b_addr));
res += bias;
#endif // defined(HAS_BIAS)
#if defined(PER_CHANNEL_QUANTIZATION)
VEC_INT output_multiplier = VLOAD(N0)(0, (__global int *)(out_mul_addr));
VEC_INT output_shift = VLOAD(N0)(0, (__global int *)(out_shift_addr));
VEC_INT res_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(res, output_multiplier, output_shift, N0);
VEC_INT res_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(res, output_multiplier, output_shift, N0);
res = select(res_shift_lt0, res_shift_gt0, (VEC_INT)(output_shift) >= 0);
#else // defined(PER_CHANNEL_QUANTIZATION)
#if OUTPUT_SHIFT < 0
res = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(res, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, N0);
#else // OUTPUT_SHIFT < 0
res = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(res, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, N0);
#endif // OUTPUT_OFFSET < 0
#endif // defined(PER_CHANNEL_QUANTIZATION)
res += (VEC_INT)OUTPUT_OFFSET;
VEC_TYPE(VEC_SIZE)
res0 = CONVERT_SAT(res, VEC_TYPE(VEC_SIZE));
res0 = ACTIVATION_FUNC(res0);
STORE_VECTOR_SELECT(res, DATA_TYPE, d_addr, N0, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0)
#if DEPTH_MULTIPLIER > 1
w_addr += sizeof(WEIGHTS_TYPE);
d_addr += sizeof(DATA_TYPE);
#if defined(PER_CHANNEL_QUANTIZATION)
out_mul_addr += sizeof(int);
out_shift_addr += sizeof(int);
#endif // defined(PER_CHANNEL_QUANTIZATION)
#if defined(HAS_BIAS)
b_addr += sizeof(int);
#endif // defined(HAS_BIAS)
}
#endif // DEPTH_MULTIPLIER > 1
}
#endif // defined(SRC_DIM1) && defined(SRC_DIM2) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defiend(N0) && defined(DILATION_X) && defined(DILATION_Y) && defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(CONV_PAD_LEFT) && defined(CONV_PAD_TOP) && defined(INPUT_OFFSET) && defined(WEIGHTS_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_SHIFT) && defined(OUTPUT_MULTIPLIER) && defined(VEC_SIZE_LEFTOVER)
#endif // defined(DATA_TYPE) && defined(WEIGHTS_TYPE)