From 9104cd559222b98f2b21f14d4fd561ed4a4e9bc2 Mon Sep 17 00:00:00 2001 From: Adnan AlSinan Date: Wed, 6 Apr 2022 16:19:31 +0100 Subject: Add support for int8 CpuPool3d - Add implementation for the CPU pooling 3d layer. - NDHWC data layout support. - Support QASYMM8/QASYMM8_SIGNED. - Add Pooling helper file for Pool3d/2d common functions. Resolves COMPMID-4668 Change-Id: Iadf042036b076099c2353d6e2fe9fc623bc263d8 Signed-off-by: Adnan AlSinan Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7387 Reviewed-by: Gunes Bayir Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- Android.bp | 2 + .../runtime/NEON/functions/NEPooling3dLayer.h | 6 +- docs/user_guide/operator_list.dox | 2 + filelist.json | 8 +- src/core/helpers/PoolingHelpers.h | 202 +++++++++++ src/cpu/kernels/CpuPool3dKernel.cpp | 17 +- src/cpu/kernels/CpuPool3dKernel.h | 4 +- src/cpu/kernels/pool2d/neon/fp16.cpp | 10 +- src/cpu/kernels/pool2d/neon/fp32.cpp | 10 +- src/cpu/kernels/pool2d/neon/nchw/all.cpp | 14 +- src/cpu/kernels/pool2d/neon/quantized.h | 161 +-------- src/cpu/kernels/pool3d/list.h | 2 + src/cpu/kernels/pool3d/neon/impl.cpp | 62 ++-- src/cpu/kernels/pool3d/neon/impl.h | 2 + src/cpu/kernels/pool3d/neon/qasymm8.cpp | 34 ++ src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp | 34 ++ src/cpu/kernels/pool3d/neon/quantized.h | 390 +++++++++++++++++++++ src/cpu/operators/CpuPool3d.h | 2 +- tests/validation/NEON/Pooling3dLayer.cpp | 78 ++++- tests/validation/fixtures/Pooling3dLayerFixture.h | 37 +- 20 files changed, 855 insertions(+), 222 deletions(-) create mode 100644 src/core/helpers/PoolingHelpers.h create mode 100644 src/cpu/kernels/pool3d/neon/qasymm8.cpp create mode 100644 src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp create mode 100644 src/cpu/kernels/pool3d/neon/quantized.h diff --git a/Android.bp b/Android.bp index a440e79ffd..691e46e5ac 100644 --- a/Android.bp +++ b/Android.bp @@ -512,6 +512,8 @@ cc_library_static { "src/cpu/kernels/pool3d/neon/fp16.cpp", "src/cpu/kernels/pool3d/neon/fp32.cpp", "src/cpu/kernels/pool3d/neon/impl.cpp", + "src/cpu/kernels/pool3d/neon/qasymm8.cpp", + "src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp", "src/cpu/kernels/range/generic/neon/fp16.cpp", "src/cpu/kernels/range/generic/neon/fp32.cpp", "src/cpu/kernels/range/generic/neon/impl.cpp", diff --git a/arm_compute/runtime/NEON/functions/NEPooling3dLayer.h b/arm_compute/runtime/NEON/functions/NEPooling3dLayer.h index 7b31f916f6..4c5eb58e05 100644 --- a/arm_compute/runtime/NEON/functions/NEPooling3dLayer.h +++ b/arm_compute/runtime/NEON/functions/NEPooling3dLayer.h @@ -64,10 +64,12 @@ public: * |:--------------|:--------------| * |F16 |F16 | * |F32 |F32 | + * |QASYMM8 |QASYMM8 | + * |QASYMM8_SIGNED |QASYMM8_SIGNED | * * @note Source tensor is padded with -inf for MAX pooling and 0 otherwise * - * @param[in] input Source tensor. Data types supported: F16/F32. + * @param[in] input Source tensor. Data types supported: F16/F32/QASYMM8/QASYMM8_SIGNED. * @param[out] output Destination tensor. * @param[in] pool_info Contains pooling operation information described in @ref Pooling3dLayerInfo. */ @@ -75,7 +77,7 @@ public: /** Static function to check if given info will lead to a valid configuration of @ref NEPooling3dLayer * * - * @param[in] input Source tensor info. Data types supported: F16/F32. + * @param[in] input Source tensor info. Data types supported: F16/F32/QASYMM8/QASYMM8_SIGNED. * @param[in] output Destination tensor info. * @param[in] pool_info Contains pooling operation information described in @ref Pooling3dLayerInfo. * diff --git a/docs/user_guide/operator_list.dox b/docs/user_guide/operator_list.dox index ee337d46ea..c0888f1775 100644 --- a/docs/user_guide/operator_list.dox +++ b/docs/user_guide/operator_list.dox @@ -2316,6 +2316,8 @@ where N = batches, C = channels, H = height, W = width, D = depth srcdst F16F16 F32F32 + QASYMM8QASYMM8 + QASYMM8_SIGNEDQASYMM8_SIGNED CLPooling3dLayer diff --git a/filelist.json b/filelist.json index 44e71c7e69..d02a6fc0c1 100644 --- a/filelist.json +++ b/filelist.json @@ -1803,9 +1803,11 @@ "src/runtime/NEON/functions/NEPooling3dLayer.cpp" ], "neon": { - "common":[ "src/cpu/kernels/pool3d/neon/impl.cpp" ], - "fp16": [ "src/cpu/kernels/pool3d/neon/fp16.cpp" ], - "fp32": [ "src/cpu/kernels/pool3d/neon/fp32.cpp" ] + "common": [ "src/cpu/kernels/pool3d/neon/impl.cpp" ], + "fp16": [ "src/cpu/kernels/pool3d/neon/fp16.cpp" ], + "fp32": [ "src/cpu/kernels/pool3d/neon/fp32.cpp" ], + "qasymm8": [ "src/cpu/kernels/pool3d/neon/qasymm8.cpp" ], + "qasymm8_signed": [ "src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp" ] } } }, diff --git a/src/core/helpers/PoolingHelpers.h b/src/core/helpers/PoolingHelpers.h new file mode 100644 index 0000000000..079629ee6a --- /dev/null +++ b/src/core/helpers/PoolingHelpers.h @@ -0,0 +1,202 @@ +/* +* Copyright (c) 2022 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. + */ +#ifndef SRC_CORE_HELPERS_POOLINGHELPERS_H +#define SRC_CORE_HELPERS_POOLINGHELPERS_H + +#include "src/core/NEON/NEAsymm.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace +{ + +inline float calculate_avg_scale_pool3d(bool exclude_padding, const Coordinates &id, const int pool_size_x, const int pool_size_y, const int pool_size_z, const int upper_bound_w, + const int upper_bound_h, const int upper_bound_d, const int pad_x, const int pad_y, const int pad_z, const int stride_x, const int stride_y, const int stride_z) +{ + // Based on NDHWC + int start_x = id[1] * stride_x - pad_x; + int start_y = id[2] * stride_y - pad_y; + int start_z = id[3] * stride_z - pad_z; + + const int end_x = std::min(start_x + pool_size_x, upper_bound_w); + const int end_y = std::min(start_y + pool_size_y, upper_bound_h); + const int end_z = std::min(start_z + pool_size_z, upper_bound_d); + if(exclude_padding) + { + start_x = std::max(0, start_x); + start_y = std::max(0, start_y); + start_z = std::max(0, start_z); + } + return 1.f / ((end_y - start_y) * (end_x - start_x) * (end_z - start_z)); +} + +inline float calculate_avg_scale_pool2d(bool exclude_padding, DataLayout data_layout, const Coordinates &id, const int pool_size_x, const int pool_size_y, const int upper_bound_w, const int upper_bound_h, + const int pad_x, const int pad_y, const int stride_x, const int stride_y) +{ + const unsigned int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const unsigned int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + + int start_x = id[idx_width] * stride_x - pad_x; + int start_y = id[idx_height] * stride_y - pad_y; + + const int end_x = std::min(start_x + pool_size_x, upper_bound_w); + const int end_y = std::min(start_y + pool_size_y, upper_bound_h); + if(exclude_padding) + { + start_x = std::max(0, start_x); + start_y = std::max(0, start_y); + } + return 1.f / ((end_y - start_y) * (end_x - start_x)); +} + +template +inline typename std::enable_if::value, int8_t>::type +quantize(float val, const UniformQuantizationInfo &info) +{ + return quantize_qasymm8_signed(val, info); +} + +template +inline typename std::enable_if::value, uint8_t>::type +quantize(float val, const UniformQuantizationInfo &info) +{ + return quantize_qasymm8(val, info); +} + +template +inline T vcvtq_q32_f32(float32x4_t values); + +template <> +inline uint32x4_t vcvtq_q32_f32(float32x4_t values) +{ + return vcvtq_u32_f32(values); +} + +template <> +inline int32x4_t vcvtq_q32_f32(float32x4_t values) +{ + return vcvtq_s32_f32(values); +} + +template +inline float32x4_t vcvtq_f32_q32(T values); + +template <> +inline float32x4_t vcvtq_f32_q32(uint32x4_t values) +{ + return vcvtq_f32_u32(values); +} + +template <> +inline float32x4_t vcvtq_f32_q32(int32x4_t values) +{ + return vcvtq_f32_s32(values); +} + +template +inline Tout vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset); + +template <> +inline uint8x16_t vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset) +{ + const float new_scale = quant_rescale / scale_pooling; + return vquantize(acc, UniformQuantizationInfo(new_scale, new_offset)); +} + +template <> +inline int8x16_t vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset) +{ + const float new_scale = quant_rescale / scale_pooling; + return vquantize_signed(acc, UniformQuantizationInfo(new_scale, new_offset)); +} + +template +inline Tout vrequantize_pooling(Tin vec1, Tin vec2, const UniformQuantizationInfo &requant_qinfo); + +template <> +inline uint8x16_t vrequantize_pooling(uint8x8_t vec1, uint8x8_t vec2, const UniformQuantizationInfo &requant_qinfo) +{ + const float32x4x4_t acc = + { + { + vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec1))))), + vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec1))))), + vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec2))))), + vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec2))))), + } + }; + return vquantize(acc, requant_qinfo); +} + +template <> +inline int8x16_t vrequantize_pooling(int8x8_t vec1, int8x8_t vec2, const UniformQuantizationInfo &requant_qinfo) +{ + const float32x4x4_t acc = + { + { + vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec1))))), + vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec1))))), + vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec2))))), + vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec2))))), + } + }; + return vquantize_signed(acc, requant_qinfo); +} + +template +inline T vrequantize_pooling(T &vec, const UniformQuantizationInfo &requant_qinfo); + +template <> +inline uint8x8_t vrequantize_pooling(uint8x8_t &vec, const UniformQuantizationInfo &requant_qinfo) +{ + const float32x4x2_t acc = + { + { + vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec))))), + vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec))))), + } + }; + return vquantize(acc, requant_qinfo); +} + +template <> +inline int8x8_t vrequantize_pooling(int8x8_t &vec, const UniformQuantizationInfo &requant_qinfo) +{ + const float32x4x2_t acc = + { + { + vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec))))), + vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec))))), + } + }; + return vquantize_signed(acc, requant_qinfo); +} + +} // namespace +} // namespace cpu +} // namespace arm_compute +#endif /* SRC_CORE_HELPERS_POOLINGHELPERS_H */ + diff --git a/src/cpu/kernels/CpuPool3dKernel.cpp b/src/cpu/kernels/CpuPool3dKernel.cpp index 3321967d2f..1305f7c5e8 100644 --- a/src/cpu/kernels/CpuPool3dKernel.cpp +++ b/src/cpu/kernels/CpuPool3dKernel.cpp @@ -43,12 +43,21 @@ using namespace misc::shape_calculator; static const std::vector available_kernels = { + { + "neon_qu8_ndhwc_poolMxNxD", + [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8); }, + REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_q8_pool3d) + }, + { + "neon_qs8_ndhwc_poolMxNxD", + [](const DataTypeISASelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); }, + REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_q8_signed_pool3d) + }, { "neon_fp16_ndhwc_poolMxNxD", [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F16 && data.isa.fp16); }, REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_pool3d) }, - { "neon_fp32_ndhwc_poolMxNxD", [](const DataTypeISASelectorData & data) { return (data.dt == DataType::F32); }, @@ -61,7 +70,11 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); ARM_COMPUTE_RETURN_ERROR_ON_MSG(src->data_layout() != DataLayout::NDHWC, "Only NDHWC layout supported"); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG((!is_data_type_float(src->data_type())) && (!pool_info.exclude_padding + && (pool_info.pool_type == PoolingType::AVG)), + "Exclude padding is unsupported for non-float types for Avg op"); const auto data_layout = src->data_layout(); const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); diff --git a/src/cpu/kernels/CpuPool3dKernel.h b/src/cpu/kernels/CpuPool3dKernel.h index f762cfca9a..437f2af7e4 100644 --- a/src/cpu/kernels/CpuPool3dKernel.h +++ b/src/cpu/kernels/CpuPool3dKernel.h @@ -51,8 +51,10 @@ public: * |:--------------|:--------------| * |F16 |F16 | * |F32 |F32 | + * |QASYMM8 |QASYMM8 | + * |QASYMM8_SIGNED |QASYMM8_SIGNED | * - * @param[in] src Source tensor info. Data types supported: F16/F32. + * @param[in] src Source tensor info. Data types supported: F16/F32/QASYMM8/QASYMM8_SIGNED. * @param[out] dst Destination tensor info. Data types supported: Same as @p src. * @param[in] pool_info Contains pooling operation information described in @ref Pooling3dLayerInfo. */ diff --git a/src/cpu/kernels/pool2d/neon/fp16.cpp b/src/cpu/kernels/pool2d/neon/fp16.cpp index 72f63af3be..13e21b1e70 100644 --- a/src/cpu/kernels/pool2d/neon/fp16.cpp +++ b/src/cpu/kernels/pool2d/neon/fp16.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2021 Arm Limited. + * Copyright (c) 2021-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -199,8 +199,8 @@ void poolingMxN_fp16_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); const float16x8_t scale_v = vdupq_n_f16(scale); // Perform pooling @@ -260,8 +260,8 @@ void poolingMxN_fp16_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float16_t scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float16_t scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); for(int y = pool_start_y; y < pool_end_y; ++y) { diff --git a/src/cpu/kernels/pool2d/neon/fp32.cpp b/src/cpu/kernels/pool2d/neon/fp32.cpp index e4261f746d..1ed199be8d 100644 --- a/src/cpu/kernels/pool2d/neon/fp32.cpp +++ b/src/cpu/kernels/pool2d/neon/fp32.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2021 Arm Limited. + * Copyright (c) 2021-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -193,8 +193,8 @@ void poolingMxN_fp32_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); const float32x4_t scale_v = vdupq_n_f32(scale); // Perform pooling @@ -258,8 +258,8 @@ void poolingMxN_fp32_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); for(int y = pool_start_y; y < pool_end_y; ++y) { diff --git a/src/cpu/kernels/pool2d/neon/nchw/all.cpp b/src/cpu/kernels/pool2d/neon/nchw/all.cpp index 10cbfc56a1..77f63c6f77 100644 --- a/src/cpu/kernels/pool2d/neon/nchw/all.cpp +++ b/src/cpu/kernels/pool2d/neon/nchw/all.cpp @@ -124,7 +124,7 @@ void pooling3_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); const float16x4_t scale_v = vdup_n_f16(scale); // Perform pooling @@ -288,7 +288,7 @@ void pooling2_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P if(pool_info.pool_type != PoolingType::MAX) { - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); const float16x4_t scale_v = vdup_n_f16(scale); @@ -343,7 +343,7 @@ void poolingMxN_fp16_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float16_t scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + const float16_t scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); // Perform pooling @@ -430,7 +430,7 @@ void poolingMxN_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); // Perform pooling @@ -538,7 +538,7 @@ void pooling2_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); const float32x2_t scale_v = vdup_n_f32(scale); @@ -618,7 +618,7 @@ void pooling3_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); const float32x2_t scale_v = vdup_n_f32(scale); @@ -687,7 +687,7 @@ void pooling7_fp32_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *dst1, P if(pool_info.pool_type != PoolingType::MAX) { // Calculate scale - float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size, pool_size, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, pool_stride_y); const float32x2_t scale_v = vdup_n_f32(scale); diff --git a/src/cpu/kernels/pool2d/neon/quantized.h b/src/cpu/kernels/pool2d/neon/quantized.h index 386e043984..a2cd3991be 100644 --- a/src/cpu/kernels/pool2d/neon/quantized.h +++ b/src/cpu/kernels/pool2d/neon/quantized.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2021 Arm Limited. + * Copyright (c) 2021-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -30,154 +30,13 @@ #include "src/core/NEON/NEFixedPoint.h" #include "src/core/NEON/NEMath.h" #include "src/core/NEON/wrapper/wrapper.h" +#include "src/core/helpers/PoolingHelpers.h" #include namespace arm_compute { namespace cpu { -template -inline typename std::enable_if::value, int8_t>::type -quantize(float val, const UniformQuantizationInfo &info) -{ - return quantize_qasymm8_signed(val, info); -} - -template -inline typename std::enable_if::value, uint8_t>::type -quantize(float val, const UniformQuantizationInfo &info) -{ - return quantize_qasymm8(val, info); -} - -template -inline T vcvtq_q32_f32(float32x4_t values); - -template <> -inline uint32x4_t vcvtq_q32_f32(float32x4_t values) -{ - return vcvtq_u32_f32(values); -} - -template <> -inline int32x4_t vcvtq_q32_f32(float32x4_t values) -{ - return vcvtq_s32_f32(values); -} - -template -inline float32x4_t vcvtq_f32_q32(T values); - -template <> -inline float32x4_t vcvtq_f32_q32(uint32x4_t values) -{ - return vcvtq_f32_u32(values); -} - -template <> -inline float32x4_t vcvtq_f32_q32(int32x4_t values) -{ - return vcvtq_f32_s32(values); -} - -template -inline Tout vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset); - -template <> -inline uint8x16_t vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset) -{ - const float new_scale = quant_rescale / scale_pooling; - return vquantize(acc, UniformQuantizationInfo(new_scale, new_offset)); -} - -template <> -inline int8x16_t vrequantize_pooling_with_scale(const float32x4x4_t &acc, const float quant_rescale, const float scale_pooling, const int32_t new_offset) -{ - const float new_scale = quant_rescale / scale_pooling; - return vquantize_signed(acc, UniformQuantizationInfo(new_scale, new_offset)); -} - -template -inline Tout vrequantize_pooling(Tin vec1, Tin vec2, const UniformQuantizationInfo &requant_qinfo); - -template <> -inline uint8x16_t vrequantize_pooling(uint8x8_t vec1, uint8x8_t vec2, const UniformQuantizationInfo &requant_qinfo) -{ - const float32x4x4_t acc = - { - { - vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec1))))), - vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec1))))), - vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec2))))), - vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec2))))), - } - }; - return vquantize(acc, requant_qinfo); -} - -template <> -inline int8x16_t vrequantize_pooling(int8x8_t vec1, int8x8_t vec2, const UniformQuantizationInfo &requant_qinfo) -{ - const float32x4x4_t acc = - { - { - vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec1))))), - vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec1))))), - vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec2))))), - vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec2))))), - } - }; - return vquantize_signed(acc, requant_qinfo); -} - -template -inline T vrequantize_pooling(T &vec, const UniformQuantizationInfo &requant_qinfo); - -template <> -inline uint8x8_t vrequantize_pooling(uint8x8_t &vec, const UniformQuantizationInfo &requant_qinfo) -{ - const float32x4x2_t acc = - { - { - vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8((vec))))), - vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8((vec))))), - } - }; - return vquantize(acc, requant_qinfo); -} - -template <> -inline int8x8_t vrequantize_pooling(int8x8_t &vec, const UniformQuantizationInfo &requant_qinfo) -{ - const float32x4x2_t acc = - { - { - vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8((vec))))), - vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8((vec))))), - } - }; - return vquantize_signed(acc, requant_qinfo); -} - -inline float calculate_avg_scale(bool exclude_padding, DataLayout data_layout, const Coordinates &id, const int pool_size_x, const int pool_size_y, const int upper_bound_w, const int upper_bound_h, - const int pad_x, const int pad_y, const int stride_x, const int stride_y) -{ - const unsigned int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const unsigned int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - - int start_x = id[idx_width] * stride_x - pad_x; - int start_y = id[idx_height] * stride_y - pad_y; - - const int end_x = std::min(start_x + pool_size_x, upper_bound_w); - const int end_y = std::min(start_y + pool_size_y, upper_bound_h); - if(exclude_padding) - { - start_x = std::max(0, start_x); - start_y = std::max(0, start_y); - } - return 1.f / ((end_y - start_y) * (end_x - start_x)); -} - template void poolingMxN_q8_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, PoolingLayerInfo &pool_info, const Window &window_src, const Window &window) { @@ -250,8 +109,8 @@ void poolingMxN_q8_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, P q32x4_t vres4 = wrapper::vdup_n(static_cast(0.f), wrapper::traits::vector_128_tag{}); // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); // Perform pooling for(int y = pool_start_y; y < pool_end_y; ++y) @@ -352,8 +211,8 @@ void poolingMxN_q8_neon_nhwc(const ITensor *src, ITensor *dst0, ITensor *dst1, P q32_t res = static_cast(0.f); // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NHWC, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); // Perform pooling for(int y = pool_start_y; y < pool_end_y; ++y) @@ -531,8 +390,8 @@ void pooling2_quantized_neon_nchw(const ITensor *src, ITensor *dst0, ITensor *ds Iterator out(dst0, window); /** SIMD vector types */ - using q8x8_t = typename wrapper::traits::neon_vector::type; - using q8x16_t = typename wrapper::traits::neon_vector::type; + using q8x8_t = typename wrapper::traits::neon_vector::type; + using q8x16_t = typename wrapper::traits::neon_vector::type; using q16_t = typename wrapper::traits::promote_t; using q16x4_t = typename wrapper::traits::neon_vector::type; using q16x8_t = typename wrapper::traits::neon_vector::type; @@ -867,8 +726,8 @@ void poolingMxN_quantized_neon_nchw(const ITensor *src, ITensor *dst0, ITensor * q32_t sres = 0; // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, - pool_stride_y); + const float scale = calculate_avg_scale_pool2d(pool_info.exclude_padding, DataLayout::NCHW, id, pool_size_x, pool_size_y, upper_bound_w, upper_bound_h, pool_pad_left, pool_pad_top, pool_stride_x, + pool_stride_y); // Perform pooling for(int y = 0; y < pool_size_y; ++y) diff --git a/src/cpu/kernels/pool3d/list.h b/src/cpu/kernels/pool3d/list.h index ece780eb0b..3426360f93 100644 --- a/src/cpu/kernels/pool3d/list.h +++ b/src/cpu/kernels/pool3d/list.h @@ -31,6 +31,8 @@ namespace cpu #define DECLARE_POOLING_KERNEL(func_name) \ void func_name(const ITensor *src0, ITensor *dst0, Pooling3dLayerInfo &, const Window &window) +DECLARE_POOLING_KERNEL(neon_q8_pool3d); +DECLARE_POOLING_KERNEL(neon_q8_signed_pool3d); DECLARE_POOLING_KERNEL(neon_fp16_pool3d); DECLARE_POOLING_KERNEL(neon_fp32_pool3d); diff --git a/src/cpu/kernels/pool3d/neon/impl.cpp b/src/cpu/kernels/pool3d/neon/impl.cpp index bb3999b104..2b089f3079 100644 --- a/src/cpu/kernels/pool3d/neon/impl.cpp +++ b/src/cpu/kernels/pool3d/neon/impl.cpp @@ -22,11 +22,10 @@ * SOFTWARE. */ #include "arm_compute/core/Helpers.h" -#include "arm_compute/core/ITensor.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/utils/misc/Traits.h" #include "src/core/NEON/wrapper/intrinsics/intrinsics.h" +#include "src/core/helpers/PoolingHelpers.h" #include "src/core/helpers/WindowHelpers.h" +#include "src/cpu/kernels/pool3d/neon/quantized.h" #include "src/cpu/kernels/pool3d/neon/impl.h" @@ -36,27 +35,6 @@ namespace cpu { namespace { -inline float calculate_avg_scale(bool exclude_padding, const Coordinates &id, const int pool_size_x, const int pool_size_y, const int pool_size_z, const int upper_bound_w, - const int upper_bound_h, const int upper_bound_d, const int pad_x, const int pad_y, const int pad_z, const int stride_x, const int stride_y, const int stride_z) -{ - // Based on NDHWC - int start_x = id[1] * stride_x - pad_x; - int start_y = id[2] * stride_y - pad_y; - int start_z = id[3] * stride_z - pad_z; - - const int end_x = std::min(start_x + pool_size_x, upper_bound_w); - const int end_y = std::min(start_y + pool_size_y, upper_bound_h); - const int end_z = std::min(start_z + pool_size_z, upper_bound_d); - if(exclude_padding) - { - start_x = std::max(0, start_x); - start_y = std::max(0, start_y); - start_z = std::max(0, start_z); - } - return 1.f / ((end_y - start_y) * (end_x - start_x) * (end_z - start_z)); -} - - template void max_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window_out, const int window_start_x, const int window_end_x, const int window_step_x) @@ -227,9 +205,9 @@ void avg_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3d const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, - pool_pad_top, pool_pad_front, pool_stride_x, - pool_stride_y, pool_stride_z); + const float scale = calculate_avg_scale_pool3d(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, + pool_pad_top, pool_pad_front, pool_stride_x, + pool_stride_y, pool_stride_z); const vector_type scale_v = wrapper::vdup_n(static_cast(scale), tag_type()); int x_off = window_start_x; @@ -354,9 +332,9 @@ void l2_poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dL const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; // Calculate scale - const float scale = calculate_avg_scale(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, - pool_pad_top, pool_pad_front, pool_stride_x, - pool_stride_y, pool_stride_z); + const float scale = calculate_avg_scale_pool3d(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, + pool_pad_top, pool_pad_front, pool_stride_x, + pool_stride_y, pool_stride_z); int x_off = window_start_x; @@ -452,9 +430,33 @@ void poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLaye } } +template +void poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window) +{ + constexpr int window_step_x = 16; + Window window_out = window; + + // Needed to handle loop left-over + window_out.set(Window::DimX, Window::Dimension(0, 1, 1)); + + switch(pool_info.pool_type) + { + case PoolingType::MAX: + max_poolingMxNxD_q8_neon_ndhwc(src, dst0, pool_info, window_out, window_step_x); + break; + case PoolingType::AVG: + avg_poolingMxNxD_q8_neon_ndhwc(src, dst0, pool_info, window_out, window_step_x); + break; + default: + ARM_COMPUTE_ERROR("Pool operation not supported"); + } +} + template void poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) template void poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); #endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS) */ +template void poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); +template void poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); } // namespace cpu } // namespace arm_compute diff --git a/src/cpu/kernels/pool3d/neon/impl.h b/src/cpu/kernels/pool3d/neon/impl.h index 829a9bd192..7ad8c8eb05 100644 --- a/src/cpu/kernels/pool3d/neon/impl.h +++ b/src/cpu/kernels/pool3d/neon/impl.h @@ -37,6 +37,8 @@ namespace cpu template void poolingMxNxD_fp_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); +template +void poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window); } // namespace cpu } // namespace arm_compute #endif //define SRC_CORE_POOLING_3D_LAYER_IMPL_H diff --git a/src/cpu/kernels/pool3d/neon/qasymm8.cpp b/src/cpu/kernels/pool3d/neon/qasymm8.cpp new file mode 100644 index 0000000000..650a815e76 --- /dev/null +++ b/src/cpu/kernels/pool3d/neon/qasymm8.cpp @@ -0,0 +1,34 @@ +/* + * Copyright (c) 2022 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 "src/cpu/kernels/pool3d/neon/impl.h" +namespace arm_compute +{ +namespace cpu +{ +void neon_q8_pool3d(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window) +{ + return poolingMxNxD_q8_neon_ndhwc(src, dst0, pool_info, window); +} +} // namespace cpu +} // namespace arm_compute \ No newline at end of file diff --git a/src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp b/src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp new file mode 100644 index 0000000000..374b2435ea --- /dev/null +++ b/src/cpu/kernels/pool3d/neon/qasymm8_signed.cpp @@ -0,0 +1,34 @@ +/* + * Copyright (c) 2022 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 "src/cpu/kernels/pool3d/neon/impl.h" +namespace arm_compute +{ +namespace cpu +{ +void neon_q8_signed_pool3d(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window) +{ + return poolingMxNxD_q8_neon_ndhwc(src, dst0, pool_info, window); +} +} // namespace cpu +} // namespace arm_compute \ No newline at end of file diff --git a/src/cpu/kernels/pool3d/neon/quantized.h b/src/cpu/kernels/pool3d/neon/quantized.h new file mode 100644 index 0000000000..ac14f5eafa --- /dev/null +++ b/src/cpu/kernels/pool3d/neon/quantized.h @@ -0,0 +1,390 @@ +/* + * Copyright (c) 2022 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. + */ +#ifndef SRC_CORE_NEON_KERNELS_POOL3D_QUANTIZED_H +#define SRC_CORE_NEON_KERNELS_POOL3D_QUANTIZED_H + +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/Types.h" +#include "src/core/NEON/wrapper/wrapper.h" +#include "src/core/helpers/PoolingHelpers.h" +#include "src/core/helpers/WindowHelpers.h" + +namespace arm_compute +{ +namespace cpu +{ +template +void avg_poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window_out, + const int window_step_x) + +{ + using q8x8_t = typename wrapper::traits::neon_vector::type; + using q8x16_t = typename wrapper::traits::neon_vector::type; + using q16_t = typename wrapper::traits::promote_t; + using q16x8_t = typename wrapper::traits::neon_vector::type; + using q32_t = typename wrapper::traits::promote_t; + using q32x4_t = typename wrapper::traits::neon_vector::type; + + int pool_stride_x = static_cast(pool_info.stride.width); + int pool_stride_y = static_cast(pool_info.stride.height); + int pool_stride_z = static_cast(pool_info.stride.depth); + + const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.width; + const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().z() : pool_info.pool_size.height; + const int pool_size_z = pool_info.is_global_pooling ? src->info()->tensor_shape()[3] : pool_info.pool_size.depth; + + const int pool_pad_top = static_cast(pool_info.padding.top); + const int pool_pad_bottom = static_cast(pool_info.padding.bottom); + const int pool_pad_left = static_cast(pool_info.padding.left); + const int pool_pad_right = static_cast(pool_info.padding.right); + const int pool_pad_front = static_cast(pool_info.padding.front); + const int pool_pad_back = static_cast(pool_info.padding.back); + + const int upper_bound_w = src->info()->dimension(1) + (pool_info.exclude_padding ? 0 : pool_pad_right); + const int upper_bound_h = src->info()->dimension(2) + (pool_info.exclude_padding ? 0 : pool_pad_bottom); + const int upper_bound_d = src->info()->dimension(3) + (pool_info.exclude_padding ? 0 : pool_pad_back); + + const int input_dim_c = src->info()->dimension(0); + const int input_dim_w = src->info()->dimension(1); + const int input_dim_h = src->info()->dimension(2); + const int input_dim_d = src->info()->dimension(3); + + const int y_stride = static_cast(src->info()->strides_in_bytes().y()); + const int z_stride = static_cast(src->info()->strides_in_bytes().z()); + const int w_stride = static_cast(src->info()->strides_in_bytes()[3]); + const int n_stride = static_cast(src->info()->strides_in_bytes()[4]); + + const uint8_t *in_ptr_start = src->buffer() + src->info()->offset_first_element_in_bytes(); + + const int window_end_x = input_dim_c; + const int window_start_x = 0; + + Iterator out(dst0, window_out); + + const float32x4_t half_scale_v = vdupq_n_f32(0.5f); + const UniformQuantizationInfo src_qinfo = src->info()->quantization_info().uniform(); + const UniformQuantizationInfo dst_qinfo = dst0->info()->quantization_info().uniform(); + + const float quant_rescale = dst_qinfo.scale / src_qinfo.scale; + // "new_offset" doesn't have to consider the "half_scale_v" in its computation + // With a requantization performed in a single step there won't be uncertainties introduced + const int32_t new_offset = dst_qinfo.offset - static_cast(static_cast(src_qinfo.offset) / quant_rescale); + + execute_window_loop(window_out, [&](const Coordinates & id) + { + // Computing the theoretical input starting/ending points + const int in_idx_width = static_cast(id.y()) * pool_stride_x - pool_pad_left; + const int in_idx_height = static_cast(id.z()) * pool_stride_y - pool_pad_top; + const int in_idx_depth = static_cast(id[3]) * pool_stride_z - pool_pad_front; + + const int pool_start_x = std::max(0, -in_idx_width); + const int pool_end_x_t = std::min(input_dim_w + pool_pad_left - in_idx_width, pool_size_x); + const int pool_start_y = std::max(0, -in_idx_height); + const int pool_end_y_t = std::min(input_dim_h + pool_pad_top - in_idx_height, pool_size_y); + + const int pool_start_z = std::max(0, -in_idx_depth); + const int pool_end_z_t = std::min(input_dim_d + pool_pad_front - in_idx_depth, pool_size_z); + + // The end of width to consider in calculation should exclude PAD_X, PAD_Y and PAD_Z + const int pool_end_x = std::min(pool_end_x_t, input_dim_w - in_idx_width); + const int pool_end_y = std::min(pool_end_y_t, input_dim_h - in_idx_height); + const int pool_end_z = std::min(pool_end_z_t, input_dim_d - in_idx_depth); + + // Calculate scale + const float scale = calculate_avg_scale_pool3d(pool_info.exclude_padding, id, pool_size_x, pool_size_y, pool_size_z, upper_bound_w, upper_bound_h, upper_bound_d, pool_pad_left, + pool_pad_top, pool_pad_front, pool_stride_x, pool_stride_y, pool_stride_z); + + const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; + + int x_off = window_start_x; + + for(; x_off <= (window_end_x - window_step_x); x_off += window_step_x) // C + { + q32x4_t vres1 = wrapper::vdup_n(static_cast(0.f), wrapper::traits::vector_128_tag{}); + q32x4_t vres2 = wrapper::vdup_n(static_cast(0.f), wrapper::traits::vector_128_tag{}); + q32x4_t vres3 = wrapper::vdup_n(static_cast(0.f), wrapper::traits::vector_128_tag{}); + q32x4_t vres4 = wrapper::vdup_n(static_cast(0.f), wrapper::traits::vector_128_tag{}); + + // Perform pooling + for(int z = pool_start_z; z < pool_end_z; ++z) + { + const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; + for(int y = pool_start_y; y < pool_end_y; ++y) + { + const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; + for(int x = pool_start_x; x < pool_end_x; ++x) + { + const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; + const q8x16_t data = wrapper::vloadq(reinterpret_cast(in_ptr_x) + x_off); + + const q16x8_t data_q16 = wrapper::vmovl(wrapper::vgetlow(data)); + const q16x8_t data2_q16 = wrapper::vmovl(wrapper::vgethigh(data)); + vres1 = wrapper::vadd(vres1, wrapper::vmovl(wrapper::vgetlow(data_q16))); + vres2 = wrapper::vadd(vres2, wrapper::vmovl(wrapper::vgethigh(data_q16))); + vres3 = wrapper::vadd(vres3, wrapper::vmovl(wrapper::vgetlow(data2_q16))); + vres4 = wrapper::vadd(vres4, wrapper::vmovl(wrapper::vgethigh(data2_q16))); + } + } + } + + if(src_qinfo != dst_qinfo) + { + const float32x4x4_t vres = + { + { + vcvtq_f32_q32(vres1), + vcvtq_f32_q32(vres2), + vcvtq_f32_q32(vres3), + vcvtq_f32_q32(vres4), + } + }; + const auto requantized_dst = vrequantize_pooling_with_scale(vres, quant_rescale, scale, new_offset); + // Store result + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off, wrapper::vgetlow(requantized_dst)); + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off + 8, wrapper::vgethigh(requantized_dst)); + } + else + { + const float32x4_t scale_v = vdupq_n_f32(scale); + // Divide by scale and add 0.5f to round to nearest instead of rounding towards zero + vres1 = vcvtq_q32_f32(wrapper::vmla(half_scale_v, vcvtq_f32_q32(vres1), scale_v)); + vres2 = vcvtq_q32_f32(wrapper::vmla(half_scale_v, vcvtq_f32_q32(vres2), scale_v)); + vres3 = vcvtq_q32_f32(wrapper::vmla(half_scale_v, vcvtq_f32_q32(vres3), scale_v)); + vres4 = vcvtq_q32_f32(wrapper::vmla(half_scale_v, vcvtq_f32_q32(vres4), scale_v)); + + const q8x8_t res1 = wrapper::vmovn(wrapper::vcombine(wrapper::vmovn(vres1), wrapper::vmovn(vres2))); + const q8x8_t res2 = wrapper::vmovn(wrapper::vcombine(wrapper::vmovn(vres3), wrapper::vmovn(vres4))); + // Store result + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off, res1); + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off + 8, res2); + } + } + + // Left-overs loop + for(; x_off < window_end_x; ++x_off) + { + q32_t res = static_cast(0.f); + + // Perform pooling + for(int z = pool_start_z; z < pool_end_z; ++z) + { + const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; + for(int y = pool_start_y; y < pool_end_y; ++y) + { + const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; + for(int x = pool_start_x; x < pool_end_x; ++x) + { + const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; + const T data = *(reinterpret_cast(in_ptr_x) + x_off); + res += data; + } + } + } + + if(src_qinfo != dst_qinfo) + { + const float res_f = static_cast(res); + const float new_scale = quant_rescale / scale; + const auto requantized_dst = quantize(res_f, UniformQuantizationInfo(new_scale, new_offset)); + + // Store result + *(reinterpret_cast(out.ptr()) + x_off) = requantized_dst; + } + else + { + // Divide by scale and add 0.5f to round to nearest instead of rounding towards zero + res = static_cast(0.5f + static_cast(res) * scale); + + // Store result + *(reinterpret_cast(out.ptr()) + x_off) = res; + } + } + }, + out); +} + +template +void max_poolingMxNxD_q8_neon_ndhwc(const ITensor *src, ITensor *dst0, Pooling3dLayerInfo &pool_info, const Window &window_out, + const int window_step_x) + +{ + using q8x8_t = typename wrapper::traits::neon_vector::type; + using q8x16_t = typename wrapper::traits::neon_vector::type; + + const int window_half_step_x = window_step_x / 2; + + int pool_stride_x = static_cast(pool_info.stride.width); + int pool_stride_y = static_cast(pool_info.stride.height); + int pool_stride_z = static_cast(pool_info.stride.depth); + + const int pool_size_x = pool_info.is_global_pooling ? src->info()->tensor_shape().y() : pool_info.pool_size.width; + const int pool_size_y = pool_info.is_global_pooling ? src->info()->tensor_shape().z() : pool_info.pool_size.height; + const int pool_size_z = pool_info.is_global_pooling ? src->info()->tensor_shape()[3] : pool_info.pool_size.depth; + + const int pool_pad_top = static_cast(pool_info.padding.top); + const int pool_pad_left = static_cast(pool_info.padding.left); + const int pool_pad_front = static_cast(pool_info.padding.front); + + const int input_dim_c = src->info()->dimension(0); + const int input_dim_w = src->info()->dimension(1); + const int input_dim_h = src->info()->dimension(2); + const int input_dim_d = src->info()->dimension(3); + + const int y_stride = static_cast(src->info()->strides_in_bytes().y()); + const int z_stride = static_cast(src->info()->strides_in_bytes().z()); + const int w_stride = static_cast(src->info()->strides_in_bytes()[3]); + const int n_stride = static_cast(src->info()->strides_in_bytes()[4]); + + const uint8_t *in_ptr_start = src->buffer() + src->info()->offset_first_element_in_bytes(); + + const int window_end_x = input_dim_c; + const int window_start_x = 0; + + Iterator out(dst0, window_out); + + const UniformQuantizationInfo src_qinfo = src->info()->quantization_info().uniform(); + const UniformQuantizationInfo dst_qinfo = dst0->info()->quantization_info().uniform(); + + const float requant_scale = dst_qinfo.scale / src_qinfo.scale; + const int32_t requant_offset = dst_qinfo.offset - static_cast(static_cast(src_qinfo.offset) / requant_scale); + const UniformQuantizationInfo requant_qinfo = UniformQuantizationInfo(requant_scale, requant_offset); + + execute_window_loop(window_out, [&](const Coordinates & id) + { + // Computing the theoretical input starting/ending points + const int in_idx_width = static_cast(id.y()) * pool_stride_x - pool_pad_left; + const int in_idx_height = static_cast(id.z()) * pool_stride_y - pool_pad_top; + const int in_idx_depth = static_cast(id[3]) * pool_stride_z - pool_pad_front; + + const int pool_start_x = std::max(0, -in_idx_width); + const int pool_end_x_t = std::min(input_dim_w + pool_pad_left - in_idx_width, pool_size_x); + const int pool_start_y = std::max(0, -in_idx_height); + const int pool_end_y_t = std::min(input_dim_h + pool_pad_top - in_idx_height, pool_size_y); + + const int pool_start_z = std::max(0, -in_idx_depth); + const int pool_end_z_t = std::min(input_dim_d + pool_pad_front - in_idx_depth, pool_size_z); + + // The end of width to consider in calculation should exclude PAD_X, PAD_Y and PAD_Z + const int pool_end_x = std::min(pool_end_x_t, input_dim_w - in_idx_width); + const int pool_end_y = std::min(pool_end_y_t, input_dim_h - in_idx_height); + const int pool_end_z = std::min(pool_end_z_t, input_dim_d - in_idx_depth); + + const uint8_t *in_ptr_n = in_ptr_start + id[4] * n_stride; + + int x_off = window_start_x; + + for(; x_off <= (window_end_x - window_step_x); x_off += window_step_x) // C + { + q8x16_t vres = wrapper::vdup_n(std::numeric_limits::min(), wrapper::traits::vector_128_tag{}); + + // Perform pooling + for(int z = pool_start_z; z < pool_end_z; ++z) + { + const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; + for(int y = pool_start_y; y < pool_end_y; ++y) + { + const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; + for(int x = pool_start_x; x < pool_end_x; ++x) + { + const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; + const q8x16_t data = wrapper::vloadq(reinterpret_cast(in_ptr_x) + x_off); + + vres = wrapper::vmax(vres, data); + } + } + } + + // Store result + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off, (src_qinfo != dst_qinfo) ? vrequantize_pooling(wrapper::vgetlow(vres), wrapper::vgethigh(vres), + requant_qinfo) : + vres); + } + + // Leftovers using half the window step + for(; x_off <= (window_end_x - window_half_step_x); x_off += window_half_step_x) + { + q8x8_t vres = wrapper::vdup_n(std::numeric_limits::min(), wrapper::traits::vector_64_tag{}); + + // Perform pooling + for(int z = pool_start_z; z < pool_end_z; ++z) + { + const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; + for(int y = pool_start_y; y < pool_end_y; ++y) + { + const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; + for(int x = pool_start_x; x < pool_end_x; ++x) + { + const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; + const q8x8_t data = wrapper::vload(reinterpret_cast(in_ptr_x) + x_off); + + vres = wrapper::vmax(vres, data); + } + } + } + + // Store result + wrapper::vstore(reinterpret_cast(out.ptr()) + x_off, + (src_qinfo != dst_qinfo) ? vrequantize_pooling(vres, requant_qinfo) : vres); + } + + // Left-overs loop + for(; x_off < window_end_x; ++x_off) + { + T res = std::numeric_limits::min(); + + for(int z = pool_start_z; z < pool_end_z; ++z) + { + const uint8_t *in_ptr_z = in_ptr_n + (z + in_idx_depth) * w_stride; + for(int y = pool_start_y; y < pool_end_y; ++y) + { + const uint8_t *in_ptr_y = in_ptr_z + (y + in_idx_height) * z_stride; + for(int x = pool_start_x; x < pool_end_x; ++x) + { + const uint8_t *in_ptr_x = in_ptr_y + (x + in_idx_width) * y_stride; + const T data = *(reinterpret_cast(in_ptr_x) + x_off); + + res = std::max(res, data); + } + } + } + + // Store result + if(src_qinfo != dst_qinfo) + { + const float res_f = static_cast(res); + *(reinterpret_cast(out.ptr()) + x_off) = quantize(res_f, requant_qinfo); + } + else + { + *(reinterpret_cast(out.ptr()) + x_off) = res; + } + } + }, + out); +} + +} // namespace cpu +} // namespace arm_compute + +#endif // SRC_CORE_NEON_KERNELS_POOL3D_QUANTIZED_H \ No newline at end of file diff --git a/src/cpu/operators/CpuPool3d.h b/src/cpu/operators/CpuPool3d.h index fc73cf0e0e..8a73f8a0af 100644 --- a/src/cpu/operators/CpuPool3d.h +++ b/src/cpu/operators/CpuPool3d.h @@ -47,7 +47,7 @@ public: /** Set the src and dst tensors. * * - * @param[in] src Source tensor info. Data types supported: F16/F32. + * @param[in] src Source tensor info. Data types supported: F16/F32/QASYMM8/QASYMM8_SIGNED. * @param[out] dst Destination tensor info. Data types supported: same as @p src. * @param[in] pool_info Contains pooling operation information described in @ref Pooling3dLayerInfo. */ diff --git a/tests/validation/NEON/Pooling3dLayer.cpp b/tests/validation/NEON/Pooling3dLayer.cpp index ae5ca466b3..07054462f5 100644 --- a/tests/validation/NEON/Pooling3dLayer.cpp +++ b/tests/validation/NEON/Pooling3dLayer.cpp @@ -55,12 +55,43 @@ const auto Pooling3dLayerDatasetFPSmall = combine(combine(combine(combine(datase framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 1), Padding3D(1, 0, 0) })), framework::dataset::make("ExcludePadding", { true, false })); +const auto Pooling3dLayerDatasetQASYMM8Small = combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), + framework::dataset::make("PoolingSize", { Size3D(3, 3, 3) })), + framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 1, 1), Size3D(1, 2, 1), Size3D(2, 2, 1) })), + framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 1), Padding3D(1, 0, 0) })), + framework::dataset::make("ExcludePadding", { true })); + +const auto Pooling3dLayerDatasetQASYMM8Large = combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), + framework::dataset::make("PoolingSize", { Size3D(3, 3, 3) })), + framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 2, 1) })), + framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 0) })), + framework::dataset::make("ExcludePadding", { true })); + using ShapeDataset = framework::dataset::ContainerDataset>; constexpr AbsoluteTolerance tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */ #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -constexpr AbsoluteTolerance tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */ -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +constexpr AbsoluteTolerance tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */ +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +constexpr AbsoluteTolerance tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for unsigned 8-bit asymmetric type */ +constexpr AbsoluteTolerance tolerance_qasymm8_s(1); /**< Tolerance value for comparing reference's output against implementation's output for signed 8-bit asymmetric type */ + +const auto qasymm8_in_qinfo_dataset = framework::dataset::make("InputQuantInfo", { QuantizationInfo(.2f, 10) }); +const auto qasymm8_out_qinfo_dataset = framework::dataset::make("OutputQuantInfo", +{ + QuantizationInfo(.2f, 10), // Same qinfo + QuantizationInfo(.1f, 5), // Multiplier <= 1 + QuantizationInfo(2.f, 3) // Multiplier > 1 +}); + +const auto qasymm8_signed_in_qinfo_dataset = framework::dataset::make("InputQuantInfo", { QuantizationInfo(.2f, -10) }); +const auto qasymm8_signed_out_qinfo_dataset = framework::dataset::make("OutputQuantInfo", +{ + QuantizationInfo(.2f, -10), // Same qinfo + QuantizationInfo(.1f, -5), // Multiplier <= 1 + QuantizationInfo(2.f, -3) // Multiplier > 1 +}); + } //namespace TEST_SUITE(NEON) @@ -280,8 +311,49 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEPoolingLayer3dFixture, framework::Datas TEST_SUITE_END() // GlobalPooling TEST_SUITE_END() // FP16 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - TEST_SUITE_END() // Float +TEST_SUITE(Quantized) + +template +using NEPooling3dLayerQuantizedFixture = Pooling3dLayerValidationQuantizedFixture; + +TEST_SUITE(QASYMM8) +FIXTURE_DATA_TEST_CASE(RunSmall, NEPooling3dLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small5dShapes(), + combine(Pooling3dLayerDatasetQASYMM8Small, + framework::dataset::make("DataType", DataType::QASYMM8))), + qasymm8_in_qinfo_dataset), + qasymm8_out_qinfo_dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEPooling3dLayerQuantizedFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::Large5dShapes(), + combine(Pooling3dLayerDatasetQASYMM8Large, + framework::dataset::make("DataType", DataType::QASYMM8))), + qasymm8_in_qinfo_dataset), + qasymm8_out_qinfo_dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} + +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(QASYMM8_SIGNED) + +FIXTURE_DATA_TEST_CASE(RunSmall, NEPooling3dLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small5dShapes(), + combine(Pooling3dLayerDatasetQASYMM8Small, + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))), + qasymm8_signed_in_qinfo_dataset), + qasymm8_signed_out_qinfo_dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_s); +} + +TEST_SUITE_END() // QASYMM8_SIGNED +TEST_SUITE_END() // Quantized TEST_SUITE_END() // Pooling3dLayer TEST_SUITE_END() // NEON } // namespace validation diff --git a/tests/validation/fixtures/Pooling3dLayerFixture.h b/tests/validation/fixtures/Pooling3dLayerFixture.h index c1b3519e80..563f1dcced 100644 --- a/tests/validation/fixtures/Pooling3dLayerFixture.h +++ b/tests/validation/fixtures/Pooling3dLayerFixture.h @@ -46,10 +46,10 @@ class Pooling3dLayerValidationGenericFixture : public framework::Fixture { public: template - void setup(TensorShape shape, Pooling3dLayerInfo pool_info, DataType data_type) + void setup(TensorShape shape, Pooling3dLayerInfo pool_info, DataType data_type, QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo()) { - _target = compute_target(shape, pool_info, data_type); - _reference = compute_reference(shape, pool_info, data_type); + _target = compute_target(shape, pool_info, data_type, input_qinfo, output_qinfo); + _reference = compute_reference(shape, pool_info, data_type, input_qinfo, output_qinfo); } protected: @@ -68,17 +68,17 @@ protected: } else // data type is quantized_asymmetric { - ARM_COMPUTE_ERROR("Passed Type Not Supported"); + library->fill_tensor_uniform(tensor, 0); } } TensorType compute_target(TensorShape shape, Pooling3dLayerInfo info, - DataType data_type) + DataType data_type, QuantizationInfo input_qinfo, QuantizationInfo output_qinfo) { // Create tensors - TensorType src = create_tensor(shape, data_type, 1, QuantizationInfo(), DataLayout::NDHWC); + TensorType src = create_tensor(shape, data_type, 1, input_qinfo, DataLayout::NDHWC); const TensorShape dst_shape = misc::shape_calculator::compute_pool3d_shape((src.info()->tensor_shape()), info); - TensorType dst = create_tensor(dst_shape, data_type, 1, QuantizationInfo(), DataLayout::NDHWC); + TensorType dst = create_tensor(dst_shape, data_type, 1, output_qinfo, DataLayout::NDHWC); // Create and configure function FunctionType pool_layer; @@ -103,17 +103,17 @@ protected: return dst; } - SimpleTensor compute_reference(TensorShape shape, Pooling3dLayerInfo info, DataType data_type) + SimpleTensor compute_reference(TensorShape shape, Pooling3dLayerInfo info, DataType data_type, QuantizationInfo input_qinfo, QuantizationInfo output_qinfo) { // Create reference - SimpleTensor src(shape, data_type, 1, QuantizationInfo(), DataLayout::NDHWC); + SimpleTensor src(shape, data_type, 1, input_qinfo, DataLayout::NDHWC); // Fill reference fill(src); - return reference::pooling_3d_layer(src, info); + return reference::pooling_3d_layer(src, info, output_qinfo); } - TensorType _target{}; - SimpleTensor _reference{}; + TensorType _target{}; + SimpleTensor _reference{}; }; template @@ -128,6 +128,19 @@ public: } }; +template +class Pooling3dLayerValidationQuantizedFixture : public Pooling3dLayerValidationGenericFixture +{ +public: + template + void setup(TensorShape shape, PoolingType pool_type, Size3D pool_size, Size3D stride, Padding3D padding, bool exclude_padding, DataType data_type, + QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo()) + { + Pooling3dLayerValidationGenericFixture::setup(shape, Pooling3dLayerInfo(pool_type, pool_size, stride, padding, exclude_padding), + data_type, input_qinfo, output_qinfo); + } +}; + template class Pooling3dLayerGlobalValidationFixture : public Pooling3dLayerValidationGenericFixture { -- cgit v1.2.1