COMPMID-1330: Add support for NormalizePlanarYUV operator in CL

Change-Id: Id0754b9e2bc3ef7ff2c4c21c3b89709588c41bd3
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146637
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>

5 files changed, 210 insertions, 27 deletions

diff --git a/tests/validation/CL/NormalizePlanarYUVLayer.cpp b/tests/validation/CL/NormalizePlanarYUVLayer.cpp
new file mode 100644
index 0000000000..aa1a00e106
--- /dev/null
+++ b/tests/validation/CL/NormalizePlanarYUVLayer.cpp
@@ -0,0 +1,142 @@
+/*
+ * 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/core/Types.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/CLTensorAllocator.h"
+#include "arm_compute/runtime/CL/functions/CLNormalizePlanarYUVLayer.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/RandomNormalizePlanarYUVLayerDataset.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/NormalizePlanarYUVLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+constexpr RelativeTolerance<float> tolerance_f16(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(NormalizePlanarYUVLayer)
+
+template <typename T>
+using CLNormalizePlanarYUVLayerFixture = NormalizePlanarYUVLayerValidationFixture<CLTensor, CLAccessor, CLNormalizePlanarYUVLayer, T>;
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::RandomNormalizePlanarYUVLayerDataset(), framework::dataset::make("DataType", { DataType::F16 })),
+                                                                   framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+               shape0, shape1, dt, data_layout)
+{
+    TensorShape src_dst_shapes = shape0;
+    if(data_layout == DataLayout::NHWC)
+    {
+        permute(src_dst_shapes, PermutationVector(2U, 0U, 1U));
+    }
+
+    // Create tensors
+    CLTensor src  = create_tensor<CLTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+    CLTensor dst  = create_tensor<CLTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+    CLTensor mean = create_tensor<CLTensor>(shape1, dt, 1);
+    CLTensor sd   = create_tensor<CLTensor>(shape1, dt, 1);
+
+    // Create and Configure function
+    CLNormalizePlanarYUVLayer norm;
+    norm.configure(&src, &dst, &mean, &sd);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(src_dst_shapes);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+                    framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),     // Mismatching data types
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),     // Window shrink
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8),      // Unsupported data type
+                        TensorInfo(TensorShape(32U, 16U, 8U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),     // Mismatching mean and sd shapes
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),     // Mismatching shapes
+                        }),
+                    framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8),
+                        TensorInfo(TensorShape(32U, 16U, 8U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
+                        TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32),
+                        })),
+                framework::dataset::make("MSTDInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::U8),
+                    TensorInfo(TensorShape(8U), 1, DataType::F16),
+                    TensorInfo(TensorShape(6U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::F32),
+                    })),
+                    framework::dataset::make("Expected", { false, false, false, true, false, false })),
+                    input_info, output_info, msd_info, expected)
+{
+    const auto &mean_info = msd_info;
+    const auto &sd_info   = msd_info;
+    bool has_error = bool(CLNormalizePlanarYUVLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &sd_info.clone()->set_is_resizable(false)));
+    ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_SUITE(Float)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(Random, CLNormalizePlanarYUVLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomNormalizePlanarYUVLayerDataset(),
+                                                                                                                  framework::dataset::make("DataType", DataType::F16)),
+                                                                                                                  framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f16, 0);
+}
+TEST_SUITE_END()
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(Random, CLNormalizePlanarYUVLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomNormalizePlanarYUVLayerDataset(),
+                                                                                                                   framework::dataset::make("DataType", DataType::F32)),
+                                                                                                                   framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/GLES_COMPUTE/NormalizePlanarYUVLayer.cpp b/tests/validation/GLES_COMPUTE/NormalizePlanarYUVLayer.cpp
index e06b19cfea..540a2be143 100644
--- a/tests/validation/GLES_COMPUTE/NormalizePlanarYUVLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/NormalizePlanarYUVLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -70,10 +70,46 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Ran
     validate(dst.info()->valid_region(), valid_region);
 }
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+                    framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),     // Mismatching data types
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),     // Window shrink
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8),      // Unsupported data type
+                        TensorInfo(TensorShape(32U, 16U, 8U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),     // Mismatching mean and sd shapes
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),     // Mismatching shapes
+                        }),
+                    framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
+                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8),
+                        TensorInfo(TensorShape(32U, 16U, 8U), 1, DataType::F16),
+                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
+                        TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F16),
+                        })),
+                framework::dataset::make("MSTDInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::U8),
+                    TensorInfo(TensorShape(8U), 1, DataType::F16),
+                    TensorInfo(TensorShape(6U), 1, DataType::F16),
+                    TensorInfo(TensorShape(2U), 1, DataType::F16),
+                    })),
+                    framework::dataset::make("Expected", { false, false, false, true, false, false })),
+                    input_info, output_info, msd_info, expected)
+{
+    const auto &mean_info = msd_info;
+    const auto &sd_info   = msd_info;
+    bool has_error = bool(GCNormalizePlanarYUVLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &sd_info.clone()->set_is_resizable(false)));
+    ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 TEST_SUITE(Float)
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, GCNormalizePlanarYUVLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomNormalizePlanarYUVLayerDataset(),
-                                                                                                                  framework::dataset::make("DataType", DataType::F16)))
+FIXTURE_DATA_TEST_CASE(Random, GCNormalizePlanarYUVLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomNormalizePlanarYUVLayerDataset(),
+                                                                                                                  framework::dataset::make("DataType", DataType::F16)),
+                                                                                                                  framework::dataset::make("DataLayout", { DataLayout::NCHW })))
 {
     // Validate output
     validate(GCAccessor(_target), _reference, tolerance_f16, 0);
diff --git a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
index 09905cfef7..cc73e530ef 100644
--- a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
+++ b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
@@ -45,16 +45,16 @@ class NormalizePlanarYUVLayerValidationFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape shape0, TensorShape shape1, DataType dt)
+    void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout)
     {
         _data_type = dt;
-        _target    = compute_target(shape0, shape1, dt);
+        _target    = compute_target(shape0, shape1, dt, data_layout);
         _reference = compute_reference(shape0, shape1, dt);
     }
 
 protected:
     template <typename U>
-    void fill(U &&src_tensor, U &&mean_tensor, U &&sd_tensor)
+    void fill(U &&src_tensor, U &&mean_tensor, U &&std_tensor)
     {
         if(is_data_type_float(_data_type))
         {
@@ -62,43 +62,48 @@ protected:
             float max_bound = 0.f;
             std::tie(min_bound, max_bound) = get_normalize_planar_yuv_layer_test_bounds<T>();
             std::uniform_real_distribution<> distribution(min_bound, max_bound);
-            std::uniform_real_distribution<> distribution_sd(0.1, max_bound);
+            std::uniform_real_distribution<> distribution_std(0.1, max_bound);
             library->fill(src_tensor, distribution, 0);
             library->fill(mean_tensor, distribution, 1);
-            library->fill(sd_tensor, distribution_sd, 2);
+            library->fill(std_tensor, distribution_std, 2);
         }
     }
 
-    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType dt)
+    TensorType compute_target(TensorShape shape0, const TensorShape &shape1, DataType dt, DataLayout data_layout)
     {
+        if(data_layout == DataLayout::NHWC)
+        {
+            permute(shape0, PermutationVector(2U, 0U, 1U));
+        }
+
         // Create tensors
-        TensorType src  = create_tensor<TensorType>(shape0, dt, 1);
-        TensorType dst  = create_tensor<TensorType>(shape0, dt, 1);
+        TensorType src  = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout);
+        TensorType dst  = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout);
         TensorType mean = create_tensor<TensorType>(shape1, dt, 1);
-        TensorType sd   = create_tensor<TensorType>(shape1, dt, 1);
+        TensorType std  = create_tensor<TensorType>(shape1, dt, 1);
 
         // Create and configure function
         FunctionType norm;
-        norm.configure(&src, &dst, &mean, &sd);
+        norm.configure(&src, &dst, &mean, &std);
 
         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS);
-        ARM_COMPUTE_EXPECT(sd.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(std.info()->is_resizable(), framework::LogLevel::ERRORS);
 
         // Allocate tensors
         src.allocator()->allocate();
         dst.allocator()->allocate();
         mean.allocator()->allocate();
-        sd.allocator()->allocate();
+        std.allocator()->allocate();
 
         ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS);
-        ARM_COMPUTE_EXPECT(!sd.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!std.info()->is_resizable(), framework::LogLevel::ERRORS);
 
         // Fill tensors
-        fill(AccessorType(src), AccessorType(mean), AccessorType(sd));
+        fill(AccessorType(src), AccessorType(mean), AccessorType(std));
 
         // Compute function
         norm.run();
@@ -111,12 +116,12 @@ protected:
         // Create reference
         SimpleTensor<T> ref_src{ shape0, dt, 1 };
         SimpleTensor<T> ref_mean{ shape1, dt, 1 };
-        SimpleTensor<T> ref_sd{ shape1, dt, 1 };
+        SimpleTensor<T> ref_std{ shape1, dt, 1 };
 
         // Fill reference
-        fill(ref_src, ref_mean, ref_sd);
+        fill(ref_src, ref_mean, ref_std);
 
-        return reference::normalize_planar_yuv_layer(ref_src, ref_mean, ref_sd);
+        return reference::normalize_planar_yuv_layer(ref_src, ref_mean, ref_std);
     }
 
     TensorType      _target{};
diff --git a/tests/validation/reference/NormalizePlanarYUVLayer.cpp b/tests/validation/reference/NormalizePlanarYUVLayer.cpp
index 2442943bb4..afb899220d 100644
--- a/tests/validation/reference/NormalizePlanarYUVLayer.cpp
+++ b/tests/validation/reference/NormalizePlanarYUVLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -35,7 +35,7 @@ namespace reference
 {
 // NormalizePlanarYUV Layer for floating point type
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *>
-SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &sd)
+SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &std)
 {
     SimpleTensor<T> result(src.shape(), src.data_type());
 
@@ -53,7 +53,7 @@ SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const Sim
                 for(int l = 0; l < cols; ++l)
                 {
                     const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth;
-                    result[pos]   = (src[pos] - mean[i]) / sd[i];
+                    result[pos]   = (src[pos] - mean[i]) / std[i];
                 }
             }
         }
@@ -61,8 +61,8 @@ SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const Sim
     return result;
 }
 
-template SimpleTensor<half> normalize_planar_yuv_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &sd);
-
+template SimpleTensor<half> normalize_planar_yuv_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &std);
+template SimpleTensor<float> normalize_planar_yuv_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &std);
 } // namespace reference
 } // namespace validation
 } // namespace test
diff --git a/tests/validation/reference/NormalizePlanarYUVLayer.h b/tests/validation/reference/NormalizePlanarYUVLayer.h
index c8740a383b..41ce48630c 100644
--- a/tests/validation/reference/NormalizePlanarYUVLayer.h
+++ b/tests/validation/reference/NormalizePlanarYUVLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -36,7 +36,7 @@ namespace validation
 namespace reference
 {
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
-SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &sd);
+SimpleTensor<T> normalize_planar_yuv_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &std);
 } // namespace reference
 } // namespace validation
 } // namespace test