COMPMID-2247: Extend support of CLBoundingBoxTransform for QUANT16_ASYMM
Change-Id: I8af7a382c0bccf55cf7f4a64f46ce9e6cd965afe
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1833
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/fixtures/BoundingBoxTransformFixture.h b/tests/validation/fixtures/BoundingBoxTransformFixture.h
index b71da8e..5e4c598 100644
--- a/tests/validation/fixtures/BoundingBoxTransformFixture.h
+++ b/tests/validation/fixtures/BoundingBoxTransformFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,28 +40,117 @@
{
namespace validation
{
+namespace
+{
+std::vector<float> generate_deltas(std::vector<float> &boxes, const TensorShape &image_shape, size_t num_boxes, size_t num_classes, std::mt19937 &gen)
+{
+ std::vector<float> deltas(num_boxes * 4 * num_classes);
+
+ std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1);
+ std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1);
+ std::uniform_int_distribution<> dist_w(1, image_shape[0]);
+ std::uniform_int_distribution<> dist_h(1, image_shape[1]);
+
+ for(size_t i = 0; i < num_boxes; ++i)
+ {
+ const float ex_width = boxes[4 * i + 2] - boxes[4 * i] + 1.f;
+ const float ex_height = boxes[4 * i + 3] - boxes[4 * i + 1] + 1.f;
+ const float ex_ctr_x = boxes[4 * i] + 0.5f * ex_width;
+ const float ex_ctr_y = boxes[4 * i + 1] + 0.5f * ex_height;
+
+ for(size_t j = 0; j < num_classes; ++j)
+ {
+ const float x1 = dist_x1(gen);
+ const float y1 = dist_y1(gen);
+ const float width = dist_w(gen);
+ const float height = dist_h(gen);
+ const float ctr_x = x1 + 0.5f * width;
+ const float ctr_y = y1 + 0.5f * height;
+
+ deltas[4 * num_classes * i + 4 * j] = (ctr_x - ex_ctr_x) / ex_width;
+ deltas[4 * num_classes * i + 4 * j + 1] = (ctr_y - ex_ctr_y) / ex_height;
+ deltas[4 * num_classes * i + 4 * j + 2] = log(width / ex_width);
+ deltas[4 * num_classes * i + 4 * j + 3] = log(height / ex_height);
+ }
+ }
+ return deltas;
+}
+
+std::vector<float> generate_boxes(const TensorShape &image_shape, size_t num_boxes, std::mt19937 &gen)
+{
+ std::vector<float> boxes(num_boxes * 4);
+
+ std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1);
+ std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1);
+ std::uniform_int_distribution<> dist_w(1, image_shape[0]);
+ std::uniform_int_distribution<> dist_h(1, image_shape[1]);
+
+ for(size_t i = 0; i < num_boxes; ++i)
+ {
+ boxes[4 * i] = dist_x1(gen);
+ boxes[4 * i + 1] = dist_y1(gen);
+ boxes[4 * i + 2] = boxes[4 * i] + dist_w(gen) - 1;
+ boxes[4 * i + 3] = boxes[4 * i + 1] + dist_h(gen) - 1;
+ }
+ return boxes;
+}
+} // namespace
+
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class BoundingBoxTransformFixture : public framework::Fixture
+class BoundingBoxTransformGenericFixture : public framework::Fixture
{
public:
+ using TDeltas = typename std::conditional<std::is_same<typename std::decay<T>::type, uint16_t>::value, uint8_t, T>::type;
+
template <typename...>
- void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type)
+ void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type, QuantizationInfo deltas_qinfo)
{
+ const bool is_qasymm16 = data_type == DataType::QASYMM16;
+ _data_type_deltas = (is_qasymm16) ? DataType::QASYMM8 : data_type;
+ _boxes_qinfo = (is_qasymm16) ? QuantizationInfo(.125f, 0) : QuantizationInfo();
+
std::mt19937 gen_target(library->seed());
- _target = compute_target(deltas_shape, data_type, info, gen_target);
+ _target = compute_target(deltas_shape, data_type, info, gen_target, deltas_qinfo);
std::mt19937 gen_reference(library->seed());
- _reference = compute_reference(deltas_shape, data_type, info, gen_reference);
+ _reference = compute_reference(deltas_shape, data_type, info, gen_reference, deltas_qinfo);
}
protected:
+ template <typename data_type, typename U>
+ void fill(U &&tensor, std::vector<float> values)
+ {
+ data_type *data_ptr = reinterpret_cast<data_type *>(tensor.data());
+ switch(tensor.data_type())
+ {
+ case DataType::QASYMM8:
+ for(size_t i = 0; i < values.size(); ++i)
+ {
+ data_ptr[i] = quantize_qasymm8(values[i], tensor.quantization_info());
+ }
+ break;
+ case DataType::QASYMM16:
+ for(size_t i = 0; i < values.size(); ++i)
+ {
+ data_ptr[i] = quantize_qasymm16(values[i], tensor.quantization_info());
+ }
+ break;
+ default:
+ for(size_t i = 0; i < values.size(); ++i)
+ {
+ data_ptr[i] = static_cast<data_type>(values[i]);
+ }
+ }
+ }
+
TensorType compute_target(const TensorShape &deltas_shape, DataType data_type,
- const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen)
+ const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen,
+ QuantizationInfo deltas_qinfo)
{
// Create tensors
TensorShape boxes_shape(4, deltas_shape[1]);
- TensorType deltas = create_tensor<TensorType>(deltas_shape, data_type);
- TensorType boxes = create_tensor<TensorType>(boxes_shape, data_type);
+ TensorType deltas = create_tensor<TensorType>(deltas_shape, _data_type_deltas, 1, deltas_qinfo);
+ TensorType boxes = create_tensor<TensorType>(boxes_shape, data_type, 1, _boxes_qinfo);
TensorType pred_boxes;
// Create and configure function
@@ -81,9 +170,11 @@
ARM_COMPUTE_EXPECT(!boxes.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
- TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height());
- generate_boxes(AccessorType(boxes), img_shape, boxes_shape[1], gen);
- generate_deltas(AccessorType(deltas), AccessorType(boxes), img_shape, deltas_shape[1], deltas_shape[0] / 4, gen);
+ TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height());
+ std::vector<float> boxes_vec = generate_boxes(img_shape, boxes_shape[1], gen);
+ std::vector<float> deltas_vec = generate_deltas(boxes_vec, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen);
+ fill<T>(AccessorType(boxes), boxes_vec);
+ fill<TDeltas>(AccessorType(deltas), deltas_vec);
// Compute function
bbox_transform.run();
@@ -93,80 +184,56 @@
SimpleTensor<T> compute_reference(const TensorShape &deltas_shape,
DataType data_type,
- const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen)
+ const BoundingBoxTransformInfo &bbox_info,
+ std::mt19937 &gen,
+ QuantizationInfo deltas_qinfo)
{
// Create reference tensor
- TensorShape boxes_shape(4, deltas_shape[1]);
- SimpleTensor<T> boxes{ boxes_shape, data_type };
- SimpleTensor<T> deltas{ deltas_shape, data_type };
+ TensorShape boxes_shape(4, deltas_shape[1]);
+ SimpleTensor<T> boxes{ boxes_shape, data_type, 1, _boxes_qinfo };
+ SimpleTensor<TDeltas> deltas{ deltas_shape, _data_type_deltas, 1, deltas_qinfo };
// Fill reference tensor
- TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height());
- generate_boxes(boxes, img_shape, boxes_shape[1], gen);
- generate_deltas(deltas, boxes, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen);
+ TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height());
+ std::vector<float> boxes_vec = generate_boxes(img_shape, boxes_shape[1], gen);
+ std::vector<float> deltas_vec = generate_deltas(boxes_vec, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen);
+ fill<T>(boxes, boxes_vec);
+ fill<TDeltas>(deltas, deltas_vec);
return reference::bounding_box_transform(boxes, deltas, bbox_info);
}
- TensorType _target{};
- SimpleTensor<T> _reference{};
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ DataType _data_type_deltas{};
+ QuantizationInfo _boxes_qinfo{};
private:
- template <typename U>
- void generate_deltas(U &&deltas, U &&boxes, const TensorShape &image_shape, size_t num_boxes, size_t num_classes, std::mt19937 &gen)
- {
- T *deltas_ptr = static_cast<T *>(deltas.data());
- T *boxes_ptr = static_cast<T *>(boxes.data());
-
- std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1);
- std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1);
- std::uniform_int_distribution<> dist_w(1, image_shape[0]);
- std::uniform_int_distribution<> dist_h(1, image_shape[1]);
-
- for(size_t i = 0; i < num_boxes; ++i)
- {
- const T ex_width = boxes_ptr[4 * i + 2] - boxes_ptr[4 * i] + T(1);
- const T ex_height = boxes_ptr[4 * i + 3] - boxes_ptr[4 * i + 1] + T(1);
- const T ex_ctr_x = boxes_ptr[4 * i] + T(0.5) * ex_width;
- const T ex_ctr_y = boxes_ptr[4 * i + 1] + T(0.5) * ex_height;
-
- for(size_t j = 0; j < num_classes; ++j)
- {
- const T x1 = T(dist_x1(gen));
- const T y1 = T(dist_y1(gen));
- const T width = T(dist_w(gen));
- const T height = T(dist_h(gen));
- const T ctr_x = x1 + T(0.5) * width;
- const T ctr_y = y1 + T(0.5) * height;
-
- deltas_ptr[4 * num_classes * i + 4 * j] = (ctr_x - ex_ctr_x) / ex_width;
- deltas_ptr[4 * num_classes * i + 4 * j + 1] = (ctr_y - ex_ctr_y) / ex_height;
- deltas_ptr[4 * num_classes * i + 4 * j + 2] = log(width / ex_width);
- deltas_ptr[4 * num_classes * i + 4 * j + 3] = log(height / ex_height);
- }
- }
- }
-
- template <typename U>
- void generate_boxes(U &&boxes, const TensorShape &image_shape, size_t num_boxes, std::mt19937 &gen)
- {
- T *boxes_ptr = (T *)boxes.data();
-
- std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1);
- std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1);
- std::uniform_int_distribution<> dist_w(1, image_shape[0]);
- std::uniform_int_distribution<> dist_h(1, image_shape[1]);
-
- for(size_t i = 0; i < num_boxes; ++i)
- {
- boxes_ptr[4 * i] = dist_x1(gen);
- boxes_ptr[4 * i + 1] = dist_y1(gen);
- boxes_ptr[4 * i + 2] = boxes_ptr[4 * i] + dist_w(gen) - 1;
- boxes_ptr[4 * i + 3] = boxes_ptr[4 * i + 1] + dist_h(gen) - 1;
- }
- }
};
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BoundingBoxTransformFixture : public BoundingBoxTransformGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type)
+ {
+ BoundingBoxTransformGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(deltas_shape, info, data_type, QuantizationInfo());
+ }
+
+private:
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BoundingBoxTransformQuantizedFixture : public BoundingBoxTransformGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type, QuantizationInfo deltas_qinfo)
+ {
+ BoundingBoxTransformGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(deltas_shape, info, data_type, deltas_qinfo);
+ }
+};
} // namespace validation
} // namespace test
} // namespace arm_compute