diff options
Diffstat (limited to 'tests/validation/fixtures/ROIAlignLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/ROIAlignLayerFixture.h | 93 |
1 files changed, 70 insertions, 23 deletions
diff --git a/tests/validation/fixtures/ROIAlignLayerFixture.h b/tests/validation/fixtures/ROIAlignLayerFixture.h index dfbb478a41..b9b85d3073 100644 --- a/tests/validation/fixtures/ROIAlignLayerFixture.h +++ b/tests/validation/fixtures/ROIAlignLayerFixture.h @@ -26,7 +26,7 @@ #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" -#include "arm_compute/runtime/CL/functions/CLROIAlignLayer.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "tests/AssetsLibrary.h" #include "tests/Globals.h" #include "tests/IAccessor.h" @@ -42,14 +42,17 @@ namespace test namespace validation { template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class ROIAlignLayerFixture : public framework::Fixture +class ROIAlignLayerGenericFixture : public framework::Fixture { public: + using TRois = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, uint16_t, T>::type; + template <typename...> - void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout) + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout, QuantizationInfo qinfo, QuantizationInfo output_qinfo) { - _target = compute_target(input_shape, data_type, data_layout, pool_info, rois_shape); - _reference = compute_reference(input_shape, data_type, pool_info, rois_shape); + _rois_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::QASYMM16 : data_type; + _target = compute_target(input_shape, data_type, data_layout, pool_info, rois_shape, qinfo, output_qinfo); + _reference = compute_reference(input_shape, data_type, pool_info, rois_shape, qinfo, output_qinfo); } protected: @@ -66,17 +69,17 @@ protected: const size_t num_rois = rois_shape.y(); std::mt19937 gen(library->seed()); - T *rois_ptr = static_cast<T *>(rois.data()); + TRois *rois_ptr = static_cast<TRois *>(rois.data()); const float pool_width = pool_info.pooled_width(); const float pool_height = pool_info.pooled_height(); const float roi_scale = pool_info.spatial_scale(); // Calculate distribution bounds - const auto scaled_width = static_cast<T>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH)] / roi_scale) / pool_width); - const auto scaled_height = static_cast<T>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT)] / roi_scale) / pool_height); - const auto min_width = static_cast<T>(pool_width / roi_scale); - const auto min_height = static_cast<T>(pool_height / roi_scale); + const auto scaled_width = static_cast<float>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH)] / roi_scale) / pool_width); + const auto scaled_height = static_cast<float>((shape[get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT)] / roi_scale) / pool_height); + const auto min_width = static_cast<float>(pool_width / roi_scale); + const auto min_height = static_cast<float>(pool_height / roi_scale); // Create distributions std::uniform_int_distribution<int> dist_batch(0, shape[3] - 1); @@ -93,11 +96,21 @@ protected: const auto x2 = x1 + dist_w(gen); const auto y2 = y1 + dist_h(gen); - rois_ptr[values_per_roi * pw] = batch_idx; - rois_ptr[values_per_roi * pw + 1] = x1; - rois_ptr[values_per_roi * pw + 2] = y1; - rois_ptr[values_per_roi * pw + 3] = x2; - rois_ptr[values_per_roi * pw + 4] = y2; + rois_ptr[values_per_roi * pw] = batch_idx; + if(rois.data_type() == DataType::QASYMM16) + { + rois_ptr[values_per_roi * pw + 1] = quantize_qasymm16(static_cast<float>(x1), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 2] = quantize_qasymm16(static_cast<float>(y1), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 3] = quantize_qasymm16(static_cast<float>(x2), rois.quantization_info()); + rois_ptr[values_per_roi * pw + 4] = quantize_qasymm16(static_cast<float>(y2), rois.quantization_info()); + } + else + { + rois_ptr[values_per_roi * pw + 1] = static_cast<TRois>(x1); + rois_ptr[values_per_roi * pw + 2] = static_cast<TRois>(y1); + rois_ptr[values_per_roi * pw + 3] = static_cast<TRois>(x2); + rois_ptr[values_per_roi * pw + 4] = static_cast<TRois>(y2); + } } } @@ -105,17 +118,23 @@ protected: DataType data_type, DataLayout data_layout, const ROIPoolingLayerInfo &pool_info, - const TensorShape rois_shape) + const TensorShape rois_shape, + const QuantizationInfo &qinfo, + const QuantizationInfo &output_qinfo) { if(data_layout == DataLayout::NHWC) { permute(input_shape, PermutationVector(2U, 0U, 1U)); } + const QuantizationInfo rois_qinfo = is_data_type_quantized(data_type) ? QuantizationInfo(0.125f, 0) : QuantizationInfo(); + // Create tensors - TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout); - TensorType rois_tensor = create_tensor<TensorType>(rois_shape, data_type); - TensorType dst; + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, qinfo, data_layout); + TensorType rois_tensor = create_tensor<TensorType>(rois_shape, _rois_data_type, 1, rois_qinfo); + + const TensorShape dst_shape = misc::shape_calculator::compute_roi_align_shape(*(src.info()), *(rois_tensor.info()), pool_info); + TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, output_qinfo, data_layout); // Create and configure function FunctionType roi_align_layer; @@ -147,23 +166,51 @@ protected: SimpleTensor<T> compute_reference(const TensorShape &input_shape, DataType data_type, const ROIPoolingLayerInfo &pool_info, - const TensorShape rois_shape) + const TensorShape rois_shape, + const QuantizationInfo &qinfo, + const QuantizationInfo &output_qinfo) { // Create reference tensor - SimpleTensor<T> src{ input_shape, data_type }; - SimpleTensor<T> rois_tensor{ rois_shape, data_type }; + SimpleTensor<T> src{ input_shape, data_type, 1, qinfo }; + const QuantizationInfo rois_qinfo = is_data_type_quantized(data_type) ? QuantizationInfo(0.125f, 0) : QuantizationInfo(); + SimpleTensor<TRois> rois_tensor{ rois_shape, _rois_data_type, 1, rois_qinfo }; // Fill reference tensor fill(src); generate_rois(rois_tensor, input_shape, pool_info, rois_shape); - return reference::roi_align_layer(src, rois_tensor, pool_info); + return reference::roi_align_layer(src, rois_tensor, pool_info, output_qinfo); } TensorType _target{}; SimpleTensor<T> _reference{}; + DataType _rois_data_type{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ROIAlignLayerFixture : public ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, DataLayout data_layout) + { + ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_info, rois_shape, data_type, data_layout, + QuantizationInfo(), QuantizationInfo()); + } }; +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ROIAlignLayerQuantizedFixture : public ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, + DataLayout data_layout, QuantizationInfo qinfo, QuantizationInfo output_qinfo) + { + ROIAlignLayerGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_info, rois_shape, + data_type, data_layout, qinfo, output_qinfo); + } +}; } // namespace validation } // namespace test } // namespace arm_compute |