[COMPMID-1331] Add support for RoIAlign operator in CL

Change-Id: Ie215daacd10477309dbf8af1bb2b05b7a0a8f203
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/150773
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

5 files changed, 462 insertions, 1 deletions

diff --git a/tests/datasets/ROIPoolingLayerDataset.h b/tests/datasets/ROIPoolingLayerDataset.h
index a1879d3b54..eb1d165202 100644
--- a/tests/datasets/ROIPoolingLayerDataset.h
+++ b/tests/datasets/ROIPoolingLayerDataset.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -112,6 +112,8 @@ class SmallROIPoolingLayerDataset final : public ROIPoolingLayerDataset
 public:
     SmallROIPoolingLayerDataset()
     {
+        add_config(TensorShape(50U, 47U, 1U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), 1U);
+        add_config(TensorShape(50U, 47U, 3U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), 1U);
         add_config(TensorShape(50U, 47U, 3U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), 40U);
         add_config(TensorShape(50U, 47U, 10U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), 80U);
         add_config(TensorShape(50U, 47U, 80U), ROIPoolingLayerInfo(7U, 7U, 1.f / 8.f), 80U);
diff --git a/tests/validation/CL/ROIAlignLayer.cpp b/tests/validation/CL/ROIAlignLayer.cpp
new file mode 100644
index 0000000000..8be16b4ad1
--- /dev/null
+++ b/tests/validation/CL/ROIAlignLayer.cpp
@@ -0,0 +1,104 @@
+/*
+ * Copyright (c) 2018 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 "arm_compute/runtime/CL/CLScheduler.h"
+#include "arm_compute/runtime/CL/functions/CLROIAlignLayer.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/CL/CLArrayAccessor.h"
+#include "tests/Globals.h"
+#include "tests/datasets/ROIPoolingLayerDataset.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/ROIAlignLayerFixture.h"
+#include "utils/TypePrinter.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RelativeTolerance<float> relative_tolerance_f32(0.01f);
+RelativeTolerance<float> absolute_tolerance_f32(0.001f);
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(RoiAlign)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+               framework::dataset::make("InputInfo", { TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/output
+                                                       TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching depth size input/output
+                                                       TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching number of rois and output batch size
+                                                       TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching height and width input/output
+
+                                                     }),
+               framework::dataset::make("NumRois", { 3U, 3U, 4U, 10U, 4U})),
+               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(7U, 7U, 3U, 3U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 3U), 1, DataType::F16),
+                                                       TensorInfo(TensorShape(7U, 7U, 4U, 3U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 2U, 3U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(5U, 5U, 2U, 4U), 1, DataType::F32),
+                                                     })),
+               framework::dataset::make("PoolInfo", { ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      })),
+               framework::dataset::make("Expected", { true, false, false, false, false })),
+               input_info, num_rois, output_info, pool_info, expected)
+{
+    ARM_COMPUTE_EXPECT(bool(CLROIAlignLayer::validate(&input_info.clone()->set_is_resizable(true), num_rois, &output_info.clone()->set_is_resizable(true), pool_info)) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using CLROIAlignLayerFixture = ROIAlignLayerFixture<CLTensor, CLAccessor, CLROIAlignLayer, CLArray<ROI>, CLArrayAccessor<ROI>, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(SmallROIAlignLayer, CLROIAlignLayerFixture<float>, framework::DatasetMode::ALL,
+                       framework::dataset::combine(framework::dataset::combine(datasets::SmallROIPoolingLayerDataset(),
+                                                                               framework::dataset::make("DataType", { DataType::F32 })),
+                                                   framework::dataset::make("Batches", { 1, 4, 8 })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, relative_tolerance_f32, 0.f, absolute_tolerance_f32);
+}
+TEST_SUITE_END() // FP32
+
+TEST_SUITE_END() // Float
+
+TEST_SUITE_END() // RoiAlign
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/ROIAlignLayerFixture.h b/tests/validation/fixtures/ROIAlignLayerFixture.h
new file mode 100644
index 0000000000..d327b0914e
--- /dev/null
+++ b/tests/validation/fixtures/ROIAlignLayerFixture.h
@@ -0,0 +1,124 @@
+/*
+ * Copyright (c) 2018 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 ARM_COMPUTE_TEST_ROIALIGNLAYER_FIXTURE
+#define ARM_COMPUTE_TEST_ROIALIGNLAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/functions/CLROIAlignLayer.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/ROIAlignLayer.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename Array_T, typename ArrayAccessor, typename T>
+class ROIAlignLayerFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, unsigned int num_rois, DataType data_type, int batches)
+    {
+        input_shape.set(2, batches);
+        std::vector<ROI> rois = generate_random_rois(input_shape, pool_info, num_rois, 0U);
+
+        _target    = compute_target(input_shape, data_type, rois, pool_info);
+        _reference = compute_reference(input_shape, data_type, rois, pool_info);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape         &input_shape,
+                              DataType                   data_type,
+                              std::vector<ROI> const    &rois,
+                              const ROIPoolingLayerInfo &pool_info)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(input_shape, data_type);
+        TensorType dst;
+
+        size_t num_rois = rois.size();
+
+        // Create roi arrays
+        std::unique_ptr<Array_T> rois_array = arm_compute::support::cpp14::make_unique<Array_T>(num_rois);
+        fill_array(ArrayAccessor(*rois_array), rois);
+
+        // Create and configure function
+        FunctionType roi_align_layer;
+        roi_align_layer.configure(&src, rois_array.get(), &dst, pool_info);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        roi_align_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape         &input_shape,
+                                      DataType                   data_type,
+                                      std::vector<ROI> const    &rois,
+                                      const ROIPoolingLayerInfo &pool_info)
+    {
+        // Create reference tensor
+        SimpleTensor<T> src{ input_shape, data_type };
+
+        // Fill reference tensor
+        fill(src);
+
+        return reference::roi_align_layer(src, rois, pool_info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_ROIALIGNLAYER_FIXTURE */
diff --git a/tests/validation/reference/ROIAlignLayer.cpp b/tests/validation/reference/ROIAlignLayer.cpp
new file mode 100644
index 0000000000..68a465d18f
--- /dev/null
+++ b/tests/validation/reference/ROIAlignLayer.cpp
@@ -0,0 +1,186 @@
+/*
+ * Copyright (c) 2018 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 "ROIAlignLayer.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "tests/validation/Helpers.h"
+
+#include <algorithm>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+namespace
+{
+/** Average pooling over an aligned window */
+template <typename T>
+inline T roi_align_1x1(const T *input, TensorShape input_shape,
+                       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);
+    }
+    else
+    {
+        float avg = 0;
+        // 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;
+
+                const size_t idx1  = coord2index(input_shape, Coordinates(x_low, y_low, pz));
+                T            data1 = input[idx1];
+
+                const size_t idx2  = coord2index(input_shape, Coordinates(x_high, y_low, pz));
+                T            data2 = input[idx2];
+
+                const size_t idx3  = coord2index(input_shape, Coordinates(x_low, y_high, pz));
+                T            data3 = input[idx3];
+
+                const size_t idx4  = coord2index(input_shape, Coordinates(x_high, y_high, pz));
+                T            data4 = input[idx4];
+
+                avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
+            }
+        }
+
+        avg /= grid_size_x * grid_size_y;
+
+        return T(avg);
+    }
+}
+
+/** Clamp the value between lower and upper */
+template <typename T>
+T clamp(T value, T lower, T upper)
+{
+    return std::max(lower, std::min(value, upper));
+}
+} // namespace
+template <typename T>
+SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info)
+{
+    const size_t num_rois      = rois.size();
+    DataType     dst_data_type = src.data_type();
+
+    TensorShape     input_shape = src.shape();
+    TensorShape     output_shape(pool_info.pooled_width(), pool_info.pooled_height(), src.shape()[2], num_rois);
+    SimpleTensor<T> dst(output_shape, dst_data_type);
+
+    // Iterate over every pixel of the input image
+    for(size_t px = 0; px < pool_info.pooled_width(); px++)
+    {
+        for(size_t py = 0; py < pool_info.pooled_height(); py++)
+        {
+            for(size_t pw = 0; pw < num_rois; pw++)
+            {
+                ROI       roi       = rois[pw];
+                const int roi_batch = roi.batch_idx;
+
+                const float roi_anchor_x = roi.rect.x * pool_info.spatial_scale();
+                const float roi_anchor_y = roi.rect.y * pool_info.spatial_scale();
+                const float roi_dims_x   = std::max(roi.rect.width * pool_info.spatial_scale(), 1.0f);
+                const float roi_dims_y   = std::max(roi.rect.height * pool_info.spatial_scale(), 1.0f);
+                ;
+
+                float bin_size_x     = roi_dims_x / pool_info.pooled_width();
+                float bin_size_y     = roi_dims_y / pool_info.pooled_height();
+                float region_start_x = px * bin_size_x + roi_anchor_x;
+                float region_start_y = py * bin_size_y + roi_anchor_y;
+                float region_end_x   = (px + 1) * bin_size_x + roi_anchor_x;
+                float region_end_y   = (py + 1) * bin_size_y + roi_anchor_y;
+
+                region_start_x = clamp(region_start_x, 0.0f, float(input_shape[0]));
+                region_start_y = clamp(region_start_y, 0.0f, float(input_shape[1]));
+                region_end_x   = clamp(region_end_x, 0.0f, float(input_shape[0]));
+                region_end_y   = clamp(region_end_y, 0.0f, float(input_shape[1]));
+
+                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));
+
+                // Move input and output pointer across the fourth dimension
+                const size_t input_stride_w  = input_shape[0] * input_shape[1] * input_shape[2];
+                const size_t output_stride_w = output_shape[0] * output_shape[1] * output_shape[2];
+                const T     *input_ptr       = src.data() + roi_batch * input_stride_w;
+                T           *output_ptr      = dst.data() + px + py * output_shape[0] + pw * output_stride_w;
+
+                for(int pz = 0; pz < int(input_shape[2]); ++pz)
+                {
+                    // For every pixel pool over an aligned region
+                    *(output_ptr + pz * output_shape[0] * output_shape[1]) = roi_align_1x1(input_ptr, input_shape,
+                                                                                           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, pz);
+                }
+            }
+        }
+    }
+    return dst;
+}
+template SimpleTensor<float> roi_align_layer(const SimpleTensor<float> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
+template SimpleTensor<half> roi_align_layer(const SimpleTensor<half> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/reference/ROIAlignLayer.h b/tests/validation/reference/ROIAlignLayer.h
new file mode 100644
index 0000000000..818f9b147c
--- /dev/null
+++ b/tests/validation/reference/ROIAlignLayer.h
@@ -0,0 +1,45 @@
+/*
+ * Copyright (c) 2018 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 __ARM_COMPUTE_TEST_ROIALIGNLAYER_H__
+#define __ARM_COMPUTE_TEST_ROIALIGNLAYER_H__
+
+#include "arm_compute/core/Types.h"
+#include "tests/SimpleTensor.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T>
+SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_ROIALIGNLAYER_H__ */