COMPMID-1754: NEON: Implement Maximum, Minumum, SquaredDifference

Change-Id: I77e8c6a8af6ad841293ed5e66ed582035cc1424b
Reviewed-on: https://review.mlplatform.org/339
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/validation/NEON/ElementwiseMax.cpp b/tests/validation/NEON/ElementwiseMax.cpp
new file mode 100644
index 0000000..c77f485
--- /dev/null
+++ b/tests/validation/NEON/ElementwiseMax.cpp
@@ -0,0 +1,264 @@
+/*
+ * 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEElementwiseOperations.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/ElementwiseOperationsFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RelativeTolerance<float> tolerance_fp32(0.000001f);
+/** Input data sets **/
+const auto ElementwiseMaxQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)),
+                                                  framework::dataset::make("DataType",
+                                                                           DataType::QASYMM8));
+/** Input data sets **/
+const auto ElementwiseMaxS32Dataset = combine(combine(framework::dataset::make("DataType", DataType::S32), framework::dataset::make("DataType", DataType::S32)), framework::dataset::make("DataType",
+                                              DataType::S32));
+const auto ElementwiseMaxS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::S16 }), framework::dataset::make("DataType", DataType::S16)),
+                                              framework::dataset::make("DataType", DataType::S16));
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+const auto ElementwiseMaxFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)),
+                                               framework::dataset::make("DataType", DataType::F16));
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+const auto ElementwiseMaxFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)),
+                                               framework::dataset::make("DataType", DataType::F32));
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(ElementwiseMax)
+
+template <typename T>
+using NEElementwiseMaxFixture = ElementwiseMaxValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+               framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
+                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
+                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),      // Invalid data type combination
+                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),     // Mismatching shapes
+                                                      }),
+               framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16),
+                                                       TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
+                                                     })),
+               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
+                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
+                                                       TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
+                                                     })),
+               framework::dataset::make("Expected", { true, true, true, false, false})),
+               input1_info, input2_info, output_info, expected)
+{
+    ARM_COMPUTE_EXPECT(bool(NEElementwiseMax::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_SUITE(S32)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
+               shape)
+{
+    // Create tensors
+    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::S32);
+    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::S32);
+    Tensor dst      = create_tensor<Tensor>(shape, DataType::S32);
+
+    // Create and Configure function
+    NEElementwiseMax add;
+    add.configure(&ref_src1, &ref_src2, &dst);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<int32_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // S32
+
+TEST_SUITE(S16)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::S16 })),
+               shape, data_type)
+{
+    // Create tensors
+    Tensor ref_src1 = create_tensor<Tensor>(shape, data_type);
+    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::S16);
+    Tensor dst      = create_tensor<Tensor>(shape, DataType::S16);
+
+    // Create and Configure function
+    NEElementwiseMax add;
+    add.configure(&ref_src1, &ref_src2, &dst);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS16Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxS16Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // S16
+
+template <typename T>
+using NEElementwiseMaxQuantizedFixture = ElementwiseMaxValidationQuantizedFixture<Tensor, Accessor, NEElementwiseMax, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
+               shape)
+{
+    // Create tensors
+    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::QASYMM8);
+    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::QASYMM8);
+    Tensor dst      = create_tensor<Tensor>(shape, DataType::QASYMM8);
+
+    // Create and Configure function
+    NEElementwiseMin add;
+    add.configure(&ref_src1, &ref_src2, &dst);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(),
+                                                                                                                       ElementwiseMaxQASYMM8Dataset),
+                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })),
+                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
+                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
+}
+
+template <typename T>
+using NEElementwiseMaxQuantizedBroadcastFixture = ElementwiseMaxQuantizedBroadcastValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;
+
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxQuantizedBroadcastFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapesBroadcast(),
+                       ElementwiseMaxQASYMM8Dataset),
+                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })),
+                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
+                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE(Float)
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+TEST_SUITE(F16)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMaxFP16Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // F16
+#endif           /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+TEST_SUITE(F32)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
+               shape)
+{
+    // Create tensors
+    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::F32);
+    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::F32);
+    Tensor dst      = create_tensor<Tensor>(shape, DataType::F32);
+
+    // Create and Configure function
+    NEElementwiseMax add;
+    add.configure(&ref_src1, &ref_src2, &dst);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+
+template <typename T>
+using NEElementwiseMaxBroadcastFixture = ElementwiseMaxBroadcastValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;
+
+FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(),
+                       ElementwiseMaxFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(),
+                       ElementwiseMaxFP32Dataset))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // F32
+TEST_SUITE_END() // Float
+
+TEST_SUITE_END() // ElementwiseMax
+TEST_SUITE_END() // NEON
+} // namespace validation
+} // namespace test
+} // namespace arm_compute