COMPMID-2318: Implement NEROIAlignLayer

Change-Id: I2665c98b5d6523a9ddaef0b7c220aecd22559ce6
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1826
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>

1 files changed, 134 insertions, 0 deletions

diff --git a/tests/validation/NEON/ROIAlignLayer.cpp b/tests/validation/NEON/ROIAlignLayer.cpp
new file mode 100644
index 0000000000..853ef6558d
--- /dev/null
+++ b/tests/validation/NEON/ROIAlignLayer.cpp
@@ -0,0 +1,134 @@
+/*
+ * Copyright (c) 2019 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/core/Types.h"
+
+#include "arm_compute/runtime/NEON/functions/NEROIAlignLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/Globals.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/datasets/ROIDataset.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);
+AbsoluteTolerance<float> absolute_tolerance_f32(0.001f);
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+RelativeTolerance<float> relative_tolerance_f16(0.01f);
+AbsoluteTolerance<float> absolute_tolerance_f16(0.001f);
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+} // namespace
+
+TEST_SUITE(NEON)
+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/rois
+                                                       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, 3U), 1, DataType::F32), // Mismatching number of rois and output batch size
+                                                       TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Invalid number of values per ROIS
+                                                       TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching height and width input/output
+
+                                                     }),
+               framework::dataset::make("RoisInfo", { TensorInfo(TensorShape(5, 4U), 1, DataType::F32),
+                                                      TensorInfo(TensorShape(5, 4U), 1, DataType::F16),
+                                                      TensorInfo(TensorShape(5, 4U), 1, DataType::F32),
+                                                      TensorInfo(TensorShape(5, 4U), 1, DataType::F32),
+                                                      TensorInfo(TensorShape(5, 10U), 1, DataType::F32),
+                                                      TensorInfo(TensorShape(4, 4U), 1, DataType::F32),
+                                                      TensorInfo(TensorShape(5, 4U), 1, DataType::F32),
+                                                    })),
+               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F16),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(5U, 5U, 3U, 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),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      ROIPoolingLayerInfo(7U, 7U, 1./8),
+                                                      })),
+               framework::dataset::make("Expected", { true, false, false, false, false, false, false })),
+               input_info, rois_info, output_info, pool_info, expected)
+{
+    ARM_COMPUTE_EXPECT(bool(NEROIAlignLayer::validate(&input_info.clone()->set_is_resizable(true), &rois_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), pool_info)) == expected, framework::LogLevel::ERRORS);
+}
+
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using NEROIAlignLayerFixture = ROIAlignLayerFixture<Tensor, Accessor, NEROIAlignLayer, T>;
+
+TEST_SUITE(Float)
+FIXTURE_DATA_TEST_CASE(SmallROIAlignLayerFloat, NEROIAlignLayerFixture<float>, framework::DatasetMode::ALL,
+                       framework::dataset::combine(framework::dataset::combine(datasets::SmallROIDataset(),
+                                                                               framework::dataset::make("DataType", { DataType::F32 })),
+                                                   framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, relative_tolerance_f32, .02f, absolute_tolerance_f32);
+}
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+FIXTURE_DATA_TEST_CASE(SmallROIAlignLayerHalf, NEROIAlignLayerFixture<half>, framework::DatasetMode::ALL,
+                       framework::dataset::combine(framework::dataset::combine(datasets::SmallROIDataset(),
+                                                                               framework::dataset::make("DataType", { DataType::F16 })),
+                                                   framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, relative_tolerance_f16, .02f, absolute_tolerance_f16);
+}
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+TEST_SUITE_END() // Float
+
+TEST_SUITE_END() // RoiAlign
+TEST_SUITE_END() // NEON
+} // namespace validation
+} // namespace test
+} // namespace arm_compute