From ebe2e8ccc6f9504fdad95884a794be1e9f58803e Mon Sep 17 00:00:00 2001 From: Pablo Tello Date: Fri, 23 Aug 2019 16:26:26 +0100 Subject: COMPMID-2318: Implement NEROIAlignLayer Added support for QASYMM8 Change-Id: I884ee8b44f38ed6e2eb5600e4ffff25e19f52eb8 Signed-off-by: Pablo Tello Reviewed-on: https://review.mlplatform.org/c/1831 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- .../core/NEON/kernels/NEROIAlignLayerKernel.h | 12 +- .../runtime/NEON/functions/NEROIAlignLayer.h | 12 +- src/core/NEON/kernels/NEROIAlignLayerKernel.cpp | 207 ++++++++++++++++----- tests/validation/NEON/ROIAlignLayer.cpp | 19 ++ 4 files changed, 195 insertions(+), 55 deletions(-) diff --git a/arm_compute/core/NEON/kernels/NEROIAlignLayerKernel.h b/arm_compute/core/NEON/kernels/NEROIAlignLayerKernel.h index 00c6f07cb5..4fc339bd14 100644 --- a/arm_compute/core/NEON/kernels/NEROIAlignLayerKernel.h +++ b/arm_compute/core/NEON/kernels/NEROIAlignLayerKernel.h @@ -55,9 +55,10 @@ public: /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. * @param[in] rois ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner - * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: same as @p input + * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. + * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, otherwise same as @p input * @param[out] output Destination tensor. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * @@ -69,8 +70,9 @@ public: void configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info); /** Static function to check if given info will lead to a valid configuration of @ref NEROIAlignLayerKernel * - * @param[in] input Source tensor info. Data types supported: F16/F32. - * @param[in] rois ROIs tensor info. Data types supported: same as @p input + * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] rois ROIs tensor info. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, + * otherwise same as @p input * @param[in] output Destination tensor info. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * @@ -87,7 +89,7 @@ public: void run(const Window &window, const ThreadInfo &info) override; private: - template + template void internal_run(const Window &window, const ThreadInfo &info); const ITensor *_input; diff --git a/arm_compute/runtime/NEON/functions/NEROIAlignLayer.h b/arm_compute/runtime/NEON/functions/NEROIAlignLayer.h index f28fb6b2be..e8171d3817 100644 --- a/arm_compute/runtime/NEON/functions/NEROIAlignLayer.h +++ b/arm_compute/runtime/NEON/functions/NEROIAlignLayer.h @@ -42,9 +42,10 @@ class NEROIAlignLayer : public INESimpleFunction public: /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. * @param[in] rois ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner - * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: same as @p input + * as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. + * Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, otherwise same as @p input * @param[out] output Destination tensor. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * @@ -54,10 +55,11 @@ public: * @note The fourth dimension of @p output tensor must be the same as the number of elements in @p rois array. */ void configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info); - /** Static function to check if given info will lead to a valid configuration of @ref NEROIAlignLayer + /** Static function to check if given info will lead to a valid configuration of @ref NEROIAlignLayerKernel * - * @param[in] input Source tensor info. Data types supported: F16/F32. - * @param[in] rois ROIs tensor info. Data types supported: same as @p input + * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] rois ROIs tensor info. Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8, + * otherwise same as @p input * @param[in] output Destination tensor info. Data types supported: Same as @p input. * @param[in] pool_info Contains pooling operation information described in @ref ROIPoolingLayerInfo. * diff --git a/src/core/NEON/kernels/NEROIAlignLayerKernel.cpp b/src/core/NEON/kernels/NEROIAlignLayerKernel.cpp index dd21094832..3b944ab8d0 100644 --- a/src/core/NEON/kernels/NEROIAlignLayerKernel.cpp +++ b/src/core/NEON/kernels/NEROIAlignLayerKernel.cpp @@ -43,10 +43,9 @@ namespace Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, ITensorInfo *output, const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, rois, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, rois); ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(0) != 5); ARM_COMPUTE_RETURN_ERROR_ON(rois->num_dimensions() > 2); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F32, DataType::F16); ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC, DataLayout::NCHW); ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); @@ -57,6 +56,20 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, ITe ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(compute_roi_align_shape(*input, *rois, pool_info), output->tensor_shape()); } + + if(input->data_type() == DataType::QASYMM8) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rois, 1, DataType::QASYMM16); + + const UniformQuantizationInfo rois_qinfo = rois->quantization_info().uniform(); + ARM_COMPUTE_RETURN_ERROR_ON(rois_qinfo.scale != 0.125f); + ARM_COMPUTE_RETURN_ERROR_ON(rois_qinfo.offset != 0); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, rois); + } + return Status{}; } @@ -118,21 +131,22 @@ Status NEROIAlignLayerKernel::validate(const ITensorInfo *input, const ITensorIn } /** Average pooling over an aligned window */ -template -inline T roi_align_1x1(const ITensor *input, unsigned int roi_batch, - float region_start_x, - float bin_size_x, - int grid_size_x, - float region_end_x, - float region_start_y, - float bin_size_y, - int grid_size_y, - float region_end_y, - int pz) +template +inline input_data_type roi_align_1x1(const ITensor *input, + unsigned int roi_batch, + float region_start_x, + float bin_size_x, + int grid_size_x, + float region_end_x, + float region_start_y, + float bin_size_y, + int grid_size_y, + float region_end_y, + int pz) { if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) { - return T(0); + return input_data_type(0); } else { @@ -163,18 +177,90 @@ inline T roi_align_1x1(const ITensor *input, unsigned int roi_batch, const float w4 = ly * lx; if(data_layout == DataLayout::NCHW) { - const auto data1 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))); - const auto data2 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))); - const auto data3 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))); - const auto data4 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))); + const auto data1 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))); + const auto data2 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))); + const auto data3 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))); + const auto data4 = *reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + else + { + const auto data1 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))); + const auto data2 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))); + const auto data3 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))); + const auto data4 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + } + } + + avg /= grid_size_x * grid_size_y; + return input_data_type(avg); + } +} + +/** Average pooling over an aligned window */ +template +inline input_data_type roi_align_1x1_qasymm8(const ITensor *input, + unsigned int roi_batch, + float region_start_x, + float bin_size_x, + int grid_size_x, + float region_end_x, + float region_start_y, + float bin_size_y, + int grid_size_y, + float region_end_y, + int pz, + const QuantizationInfo &out_qinfo) +{ + if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + { + return input_data_type(out_qinfo.uniform().offset); + } + else + { + float avg = 0; + const UniformQuantizationInfo input_qinfo = input->info()->quantization_info().uniform(); + // Iterate through the aligned pooling region + for(int iy = 0; iy < grid_size_y; ++iy) + { + for(int ix = 0; ix < grid_size_x; ++ix) + { + // Align the window in the middle of every bin + float y = region_start_y + (iy + 0.5) * bin_size_y / float(grid_size_y); + float x = region_start_x + (ix + 0.5) * bin_size_x / float(grid_size_x); + + // Interpolation in the [0,0] [0,1] [1,0] [1,1] square + const int y_low = y; + const int x_low = x; + const int y_high = y_low + 1; + const int x_high = x_low + 1; + + const float ly = y - y_low; + const float lx = x - x_low; + const float hy = 1. - ly; + const float hx = 1. - lx; + + const float w1 = hy * hx; + const float w2 = hy * lx; + const float w3 = ly * hx; + const float w4 = ly * lx; + + if(data_layout == DataLayout::NCHW) + { + float data1 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))), input_qinfo); + float data2 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))), input_qinfo); + float data3 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))), input_qinfo); + float data4 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))), input_qinfo); avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; } else { - const auto data1 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))); - const auto data2 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))); - const auto data3 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))); - const auto data4 = *reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))); + const auto data1 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))), input_qinfo); + const auto data2 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))), input_qinfo); + const auto data3 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))), input_qinfo); + const auto data4 = dequantize_qasymm8(*reinterpret_cast(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))), input_qinfo); avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; } } @@ -182,7 +268,7 @@ inline T roi_align_1x1(const ITensor *input, unsigned int roi_batch, avg /= grid_size_x * grid_size_y; - return T(avg); + return quantize_qasymm8(avg, out_qinfo); } } @@ -198,6 +284,11 @@ void NEROIAlignLayerKernel::run(const Window &window, const ThreadInfo &info) { switch(_input->info()->data_type()) { + case DataType::QASYMM8: + { + NEROIAlignLayerKernel::internal_run(window, info); + break; + } case DataType::F32: { NEROIAlignLayerKernel::internal_run(window, info); @@ -221,6 +312,11 @@ void NEROIAlignLayerKernel::run(const Window &window, const ThreadInfo &info) { switch(_input->info()->data_type()) { + case DataType::QASYMM8: + { + NEROIAlignLayerKernel::internal_run(window, info); + break; + } case DataType::F32: { NEROIAlignLayerKernel::internal_run(window, info); @@ -246,7 +342,7 @@ void NEROIAlignLayerKernel::run(const Window &window, const ThreadInfo &info) } } -template +template void NEROIAlignLayerKernel::internal_run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); @@ -268,16 +364,30 @@ void NEROIAlignLayerKernel::internal_run(const Window &window, const ThreadInfo const int pooled_w = _pool_info.pooled_width(); const int pooled_h = _pool_info.pooled_height(); - const auto *rois_ptr = reinterpret_cast(_rois->buffer()); + const DataType data_type = _input->info()->data_type(); + const bool is_qasymm = is_data_type_quantized_asymmetric(data_type); + const auto *rois_ptr = reinterpret_cast(_rois->buffer()); + const QuantizationInfo &rois_qinfo = _rois->info()->quantization_info(); for(int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) { const unsigned int roi_batch = rois_ptr[values_per_roi * roi_indx]; - const auto x1 = rois_ptr[values_per_roi * roi_indx + 1]; - const auto y1 = rois_ptr[values_per_roi * roi_indx + 2]; - const auto x2 = rois_ptr[values_per_roi * roi_indx + 3]; - const auto y2 = rois_ptr[values_per_roi * roi_indx + 4]; + roi_data_type qx1 = rois_ptr[values_per_roi * roi_indx + 1]; + roi_data_type qy1 = rois_ptr[values_per_roi * roi_indx + 2]; + roi_data_type qx2 = rois_ptr[values_per_roi * roi_indx + 3]; + roi_data_type qy2 = rois_ptr[values_per_roi * roi_indx + 4]; + float x1(qx1); + float x2(qx2); + float y1(qy1); + float y2(qy2); + if(is_qasymm) + { + x1 = dequantize_qasymm16(qx1, rois_qinfo); + x2 = dequantize_qasymm16(qx2, rois_qinfo); + y1 = dequantize_qasymm16(qy1, rois_qinfo); + y2 = dequantize_qasymm16(qy2, rois_qinfo); + } const float roi_anchor_x = x1 * _pool_info.spatial_scale(); const float roi_anchor_y = y1 * _pool_info.spatial_scale(); const float roi_dims_x = std::max((x2 - x1) * _pool_info.spatial_scale(), 1.0f); @@ -293,29 +403,36 @@ void NEROIAlignLayerKernel::internal_run(const Window &window, const ThreadInfo { for(int px = 0; px < pooled_w; ++px) { - const float region_start_x = compute_region_coordinate(px, bin_size_x, roi_anchor_x, input_width); - const float region_start_y = compute_region_coordinate(py, bin_size_y, roi_anchor_y, input_height); - const float region_end_x = compute_region_coordinate(px + 1, bin_size_x, roi_anchor_x, input_width); - const float region_end_y = compute_region_coordinate(py + 1, bin_size_y, roi_anchor_y, input_height); - const int roi_bin_grid_x = (_pool_info.sampling_ratio() > 0) ? _pool_info.sampling_ratio() : int(ceil(bin_size_x)); - const int roi_bin_grid_y = (_pool_info.sampling_ratio() > 0) ? _pool_info.sampling_ratio() : int(ceil(bin_size_y)); - - const float out_val = roi_align_1x1(_input, roi_batch, region_start_x, bin_size_x, - roi_bin_grid_x, - region_end_x, - region_start_y, - bin_size_y, - roi_bin_grid_y, - region_end_y, ch); + const float region_start_x = compute_region_coordinate(px, bin_size_x, roi_anchor_x, input_width); + const float region_start_y = compute_region_coordinate(py, bin_size_y, roi_anchor_y, input_height); + const float region_end_x = compute_region_coordinate(px + 1, bin_size_x, roi_anchor_x, input_width); + const float region_end_y = compute_region_coordinate(py + 1, bin_size_y, roi_anchor_y, input_height); + const int roi_bin_grid_x = (_pool_info.sampling_ratio() > 0) ? _pool_info.sampling_ratio() : int(ceil(bin_size_x)); + const int roi_bin_grid_y = (_pool_info.sampling_ratio() > 0) ? _pool_info.sampling_ratio() : int(ceil(bin_size_y)); + input_data_type out_val(0); + if(is_qasymm) + { + out_val = roi_align_1x1_qasymm8( + _input, roi_batch, region_start_x, bin_size_x, + roi_bin_grid_x, region_end_x, region_start_y, bin_size_y, + roi_bin_grid_y, region_end_y, ch, _output->info()->quantization_info()); + } + else + { + out_val = roi_align_1x1( + _input, roi_batch, region_start_x, bin_size_x, + roi_bin_grid_x, region_end_x, region_start_y, bin_size_y, + roi_bin_grid_y, region_end_y, ch); + } if(data_layout == DataLayout::NCHW) { - auto out_ptr = reinterpret_cast(_output->ptr_to_element(Coordinates(px, py, ch, roi_indx))); + auto out_ptr = reinterpret_cast(_output->ptr_to_element(Coordinates(px, py, ch, roi_indx))); *out_ptr = out_val; } else { - auto out_ptr = reinterpret_cast(_output->ptr_to_element(Coordinates(ch, px, py, roi_indx))); + auto out_ptr = reinterpret_cast(_output->ptr_to_element(Coordinates(ch, px, py, roi_indx))); *out_ptr = out_val; } } diff --git a/tests/validation/NEON/ROIAlignLayer.cpp b/tests/validation/NEON/ROIAlignLayer.cpp index 853ef6558d..9433c21ac9 100644 --- a/tests/validation/NEON/ROIAlignLayer.cpp +++ b/tests/validation/NEON/ROIAlignLayer.cpp @@ -52,6 +52,7 @@ RelativeTolerance relative_tolerance_f16(0.01f); AbsoluteTolerance absolute_tolerance_f16(0.001f); #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +constexpr AbsoluteTolerance tolerance_qasymm8(1); } // namespace TEST_SUITE(NEON) @@ -127,6 +128,24 @@ FIXTURE_DATA_TEST_CASE(SmallROIAlignLayerHalf, NEROIAlignLayerFixture, fra TEST_SUITE_END() // Float +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +template +using NEROIAlignLayerQuantizedFixture = ROIAlignLayerQuantizedFixture; + +FIXTURE_DATA_TEST_CASE(Small, NEROIAlignLayerQuantizedFixture, framework::DatasetMode::ALL, + combine(combine(combine(combine(datasets::SmallROIDataset(), + framework::dataset::make("DataType", { DataType::QASYMM8 })), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 127) })), + framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(2.f / 255.f, 120) }))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} +TEST_SUITE_END() // QASYMM8 +TEST_SUITE_END() // Quantized + TEST_SUITE_END() // RoiAlign TEST_SUITE_END() // NEON } // namespace validation -- cgit v1.2.1