diff options
Diffstat (limited to 'src/core/CL/cl_kernels/roi_pooling_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/roi_pooling_layer.cl | 56 |
1 files changed, 41 insertions, 15 deletions
diff --git a/src/core/CL/cl_kernels/roi_pooling_layer.cl b/src/core/CL/cl_kernels/roi_pooling_layer.cl index ac193e8fb6..6899b952e0 100644 --- a/src/core/CL/cl_kernels/roi_pooling_layer.cl +++ b/src/core/CL/cl_kernels/roi_pooling_layer.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 Arm Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -22,6 +22,7 @@ * SOFTWARE. */ #include "helpers.h" +#include "helpers_asymm.h" #if DATA_SIZE == 32 #define VEC_SIZE 4 @@ -29,24 +30,41 @@ #elif DATA_SIZE == 16 #define VEC_SIZE 8 #define VEC_MAX vec8_max -#else /* DATA_SIZE not equals 32 or 16 */ +#elif DATA_SIZE == 8 +#define VEC_SIZE 16 +#define VEC_MAX vec16_max +#else /* DATA_SIZE not equals 8, 16, 32 */ #error "Unsupported data size" #endif /* DATA_SIZE == 32 */ +// Define whether to use max (Quantized datatype) or fmax (Float) functions +#if defined(OFFSET_OUT) && defined(SCALE_OUT) +#define MAX(x, y) max(x, y) +#else // !(defined(OFFSET_OUT) && defined(SCALE_OUT) +#define MAX(x, y) fmax(x, y) +#endif // defined(OFFSET_OUT) && defined(SCALE_OUT) + inline DATA_TYPE vec4_max(VEC_DATA_TYPE(DATA_TYPE, 4) vec) { VEC_DATA_TYPE(DATA_TYPE, 2) - temp = fmax(vec.lo, vec.hi); - return fmax(temp.x, temp.y); + temp = MAX(vec.lo, vec.hi); + return MAX(temp.x, temp.y); } inline DATA_TYPE vec8_max(VEC_DATA_TYPE(DATA_TYPE, 8) vec) { VEC_DATA_TYPE(DATA_TYPE, 4) - temp = fmax(vec.lo, vec.hi); + temp = MAX(vec.lo, vec.hi); return vec4_max(temp); } +inline DATA_TYPE vec16_max(VEC_DATA_TYPE(DATA_TYPE, 16) vec) +{ + VEC_DATA_TYPE(DATA_TYPE, 8) + temp = MAX(vec.lo, vec.hi); + return vec8_max(temp); +} + /** Performs a roi pooling on a single output pixel. * * @param[in] input Pointer to input Tensor3D struct. @@ -69,7 +87,8 @@ inline DATA_TYPE roi_pool_1x1(const Tensor3D *input, int region_start_x, int reg { int num_iter = (int)((region_end_x - region_start_x) / VEC_SIZE); VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - curr_max = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))(-FLT_MAX); + curr_max = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))(MIN_VALUE); + for(int j = region_start_y; j < region_end_y; ++j) { int i = region_start_x; @@ -77,27 +96,34 @@ inline DATA_TYPE roi_pool_1x1(const Tensor3D *input, int region_start_x, int reg { VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) val = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(input, i, j, pz)); - curr_max = fmax(val, curr_max); + curr_max = MAX(val, curr_max); } for(; i < region_end_x; ++i) { DATA_TYPE val = *(__global DATA_TYPE *)tensor3D_offset(input, i, j, pz); - curr_max = fmax(curr_max, val); + curr_max = MAX(curr_max, val); } } - return (DATA_TYPE)VEC_MAX(curr_max); + + const DATA_TYPE temp = (DATA_TYPE)VEC_MAX(curr_max); + +#if defined(OFFSET_OUT) && defined(SCALE_OUT) + return QUANTIZE(temp, OFFSET_OUT, SCALE_OUT, DATA_TYPE, 1); +#endif /* if quantized, requantize and return */ + + return temp; } } /** Performs a roi pooling function. * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32; + * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32, QASYMM8; * @note Datasize must be passed using -DDATA_SIZE e.g. -DDATA_SIZE=32; * @note Input dimensions must be passed using -DMAX_DIM_X, -DMAX_DIM_Y and -DMAX_DIM_Z; * @note Pooled region dimensions must be passed using -DPOOLED_DIM_X and -DPOOLED_DIM_Y; * @note Spatial scale must be passed using -DSPATIAL_SCALE; * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32 + * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32, QASYMM8 * @param[in] input_stride_x Stride of the source image in X dimension (in bytes) * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes) @@ -111,7 +137,7 @@ inline DATA_TYPE roi_pool_1x1(const Tensor3D *input, int region_start_x, int reg * @param[in] rois_stride_y Stride of the ROIs tensor in Y dimension (in bytes) * @param[in] rois_step_y Step of the ROIs tensor in Y dimension (in bytes) * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the ROIs tensor - * @param[out] output_ptr Pointer to the destination image. Supported data types: F16, F32 + * @param[out] output_ptr Pointer to the destination image. Supported data types: same as input * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes) * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes) @@ -139,9 +165,9 @@ __kernel void roi_pooling_layer( // Load roi parameters // roi is laid out as follows { batch_index, x1, y1, x2, y2 } - const ushort roi_batch = (ushort) * ((__global DATA_TYPE *)offset(&rois, 0, pw)); - const VEC_DATA_TYPE(DATA_TYPE, 4) - roi = vload4(0, (__global DATA_TYPE *)offset(&rois, 1, pw)); + const ushort roi_batch = (ushort) * ((__global ushort *)offset(&rois, 0, pw)); + const VEC_DATA_TYPE(ushort, 4) + roi = vload4(0, (__global ushort *)offset(&rois, 1, pw)); const int2 roi_anchor = convert_int2_sat(round(convert_float2(roi.s01) * (float)SPATIAL_SCALE)); const int2 roi_dims = convert_int2_sat(fmax(round(convert_float2(roi.s23 - roi.s01) * (float)SPATIAL_SCALE), 1.f)); |