COMPMID-2268: Implement NEG for NEON.

Change-Id: I90c023dbea8ea12e9af677294ba576b2bfcc02a4
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/184216
Tested-by: bsgcomp <bsgcomp@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1099
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

8 files changed, 251 insertions, 17 deletions

diff --git a/arm_compute/core/NEON/kernels/NEElementwiseUnaryKernel.h b/arm_compute/core/NEON/kernels/NEElementwiseUnaryKernel.h
index f632b1a93a..2c019b52f0 100644
--- a/arm_compute/core/NEON/kernels/NEElementwiseUnaryKernel.h
+++ b/arm_compute/core/NEON/kernels/NEElementwiseUnaryKernel.h
@@ -88,7 +88,7 @@ public:
 
 protected:
     // Inherited methods overridden:
-    static Status validate_arguments(const ITensorInfo &input, const ITensorInfo &output);
+    static Status validate_arguments(ElementWiseUnary op, const ITensorInfo &input, const ITensorInfo &output);
 
     /** Function to use for the particular tensor types passed to configure() */
     std::function<void(const ITensor *input, ITensor *output, const Window &window)> _function;
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index a2dfbb7d82..544ebff410 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -578,6 +578,7 @@ enum class ElementWiseUnary
 {
     RSQRT, /**< Reverse square root */
     EXP,   /**< Exponential */
+    NEG,   /**< Negate */
 };
 
 /** The normalization type used for the normalization layer */
diff --git a/arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.h b/arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.h
index 76827903fa..f4b7e89889 100644
--- a/arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.h
@@ -69,5 +69,25 @@ public:
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *output);
 };
+
+/** Basic function to negate an input tensor. */
+class NENegLayer : public INESimpleFunction
+{
+public:
+    /** Initialize the function
+     *
+     * @param[in]  input  Input tensor. Data types supported: F16/F32/S32.
+     * @param[out] output Output tensor. Data types supported: same as @p input.
+     */
+    void configure(const ITensor *input, ITensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref NENegLayer
+     *
+     * @param[in] input  First tensor input info. Data types supported: F16/F32/S32.
+     * @param[in] output Output tensor info. Data types supported: Same as @p input.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output);
+};
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_NEELEMENTWISEUNARYLAYER_H__ */
diff --git a/src/core/NEON/kernels/NEElementwiseUnaryKernel.cpp b/src/core/NEON/kernels/NEElementwiseUnaryKernel.cpp
index 34696d872a..d62b165727 100644
--- a/src/core/NEON/kernels/NEElementwiseUnaryKernel.cpp
+++ b/src/core/NEON/kernels/NEElementwiseUnaryKernel.cpp
@@ -55,12 +55,15 @@ inline ScalarType elementwise_op_scalar(const ScalarType &a)
             return 1 / sqrt(a);
         case ElementWiseUnary::EXP:
             return std::exp(a);
+        case ElementWiseUnary::NEG:
+            return -a;
         default:
             ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
     }
 }
 
-template <ElementWiseUnary op, typename VectorType>
+/* Elementwise operations that are supported for float */
+template <ElementWiseUnary op, bool is_float, typename VectorType, typename std::enable_if<is_float, int>::type = 0>
 inline VectorType elementwise_op(const VectorType &a)
 {
     switch(op)
@@ -69,12 +72,27 @@ inline VectorType elementwise_op(const VectorType &a)
             return wrapper::vinvsqrt(a);
         case ElementWiseUnary::EXP:
             return wrapper::vexpq(a);
+        case ElementWiseUnary::NEG:
+            return wrapper::vneg(a);
         default:
             ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
     }
 }
 
-template <ElementWiseUnary op, typename ScalarType>
+/* Elementwise operations that are supported for non floats */
+template <ElementWiseUnary op, bool is_float, typename VectorType, typename std::enable_if<!is_float, int>::type = 0>
+inline VectorType elementwise_op(const VectorType &a)
+{
+    switch(op)
+    {
+        case ElementWiseUnary::NEG:
+            return wrapper::vneg(a);
+        default:
+            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
+    }
+}
+
+template <ElementWiseUnary op, typename ScalarType, bool is_float>
 void elementwise_op(const ITensor *in, ITensor *out, const Window &window)
 {
     const int  window_step_x  = 16 / sizeof(ScalarType);
@@ -95,7 +113,7 @@ void elementwise_op(const ITensor *in, ITensor *out, const Window &window)
         int x = window_start_x;
         for(; x <= window_end_x - window_step_x; x += window_step_x)
         {
-            wrapper::vstore(output_ptr + x, elementwise_op<op>(wrapper::vloadq(input_ptr + x)));
+            wrapper::vstore(output_ptr + x, elementwise_op<op, is_float>(wrapper::vloadq(input_ptr + x)));
         }
         for(; x < window_end_x; ++x)
         {
@@ -115,10 +133,11 @@ configure_func(const ITensor *input, ITensor *output)
 
     static std::map<std::string, NEElementwiseUnaryKernel::ElementwiseUnaryFunction *> map_function =
     {
-        { "op_F32_F32", &elementwise_op<op, float> }
+        { "op_F32_F32", &elementwise_op<op, float, true> },
+        { "op_S32_S32", &elementwise_op<op, int32_t, false> },
     };
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-    map_function["op_F16_F16"] = &elementwise_op<op, float16_t>;
+    map_function["op_F16_F16"] = &elementwise_op<op, float16_t, true>;
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
 
     auto it = map_function.find(function_to_call);
@@ -142,7 +161,7 @@ NEElementwiseUnaryKernel::NEElementwiseUnaryKernel()
 
 void NEElementwiseUnaryKernel::configure(ElementWiseUnary op, const ITensor *input, ITensor *output)
 {
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input->info(), *output->info()));
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(op, *input->info(), *output->info()));
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Configure kernel window
@@ -168,16 +187,29 @@ void NEElementwiseUnaryKernel::configure(ElementWiseUnary op, const ITensor *inp
         case ElementWiseUnary::EXP:
             _function = configure_func<ElementWiseUnary::EXP>(input, output);
             break;
+        case ElementWiseUnary::NEG:
+            _function = configure_func<ElementWiseUnary::NEG>(input, output);
+            break;
         default:
             ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
     }
 }
 
-Status NEElementwiseUnaryKernel::validate_arguments(const ITensorInfo &input, const ITensorInfo &output)
+Status NEElementwiseUnaryKernel::validate_arguments(ElementWiseUnary op, const ITensorInfo &input, const ITensorInfo &output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::F16, DataType::F32);
-
+    switch(op)
+    {
+        case ElementWiseUnary::EXP:
+        case ElementWiseUnary::RSQRT:
+            ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::F16, DataType::F32);
+            break;
+        case ElementWiseUnary::NEG:
+            ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::F16, DataType::F32, DataType::S32);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
+    }
     // Validate in case of configured output
     if(output.total_size() > 0)
     {
@@ -189,9 +221,8 @@ Status NEElementwiseUnaryKernel::validate_arguments(const ITensorInfo &input, co
 
 Status NEElementwiseUnaryKernel::validate(ElementWiseUnary op, const ITensorInfo *input, const ITensorInfo *output)
 {
-    ARM_COMPUTE_UNUSED(op);
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input, *output));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(op, *input, *output));
     return Status{};
 }
 
diff --git a/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp b/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp
index 10142c732f..48f4975b1a 100644
--- a/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp
+++ b/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp
@@ -51,4 +51,16 @@ Status NEExpLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
     return NEElementwiseUnaryKernel::validate(ElementWiseUnary::EXP, input, output);
 }
+
+void NENegLayer::configure(const ITensor *input, ITensor *output)
+{
+    auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>();
+    k->configure(ElementWiseUnary::NEG, input, output);
+    _kernel = std::move(k);
+}
+Status NENegLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+    return NEElementwiseUnaryKernel::validate(ElementWiseUnary::NEG, input, output);
+}
+
 } // namespace arm_compute
diff --git a/tests/validation/NEON/ElementwiseNegation.cpp b/tests/validation/NEON/ElementwiseNegation.cpp
new file mode 100644
index 0000000000..7e7c838472
--- /dev/null
+++ b/tests/validation/NEON/ElementwiseNegation.cpp
@@ -0,0 +1,133 @@
+/*
+ * 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/NEElementwiseUnaryLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/PaddingCalculator.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/ElementWiseUnaryFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RelativeTolerance<float> tolerance_fp32(0.000001f);
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+RelativeTolerance<float> tolerance_fp16(0.01f);
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+} // namespace
+TEST_SUITE(NEON)
+TEST_SUITE(NegLayer)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), shape, data_type)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type);
+    Tensor dst = create_tensor<Tensor>(shape, data_type);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NENegLayer neg_layer;
+    neg_layer.configure(&src, &dst);
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(src.info()->valid_region(), valid_region);
+    validate(dst.info()->valid_region(), valid_region);
+}
+
+template <typename T>
+using NENegLayerFixture = NegValidationFixture<Tensor, Accessor, NENegLayer, T>;
+
+TEST_SUITE(Float)
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, NENegLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                     DataType::F16)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp16);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NENegLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                   DataType::F16)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp16);
+}
+
+TEST_SUITE_END() // FP16
+#endif           // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NENegLayerFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NENegLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                    DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_fp32);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+
+TEST_SUITE(Integer)
+TEST_SUITE(S32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NENegLayerFixture<int32_t>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
+                                                                                                  DataType::S32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, NENegLayerFixture<int32_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType",
+                                                                                                      DataType::S32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END() // S32
+TEST_SUITE_END() // Integer
+
+TEST_SUITE_END() // NegLayer
+TEST_SUITE_END() // NEON
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/ElementWiseUnaryFixture.h b/tests/validation/fixtures/ElementWiseUnaryFixture.h
index f508bc1d34..ba131630a3 100644
--- a/tests/validation/fixtures/ElementWiseUnaryFixture.h
+++ b/tests/validation/fixtures/ElementWiseUnaryFixture.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -53,7 +53,7 @@ public:
 
 protected:
     template <typename U>
-    void fill(U &&tensor, int i)
+    void fill(U &&tensor, int i, DataType data_type)
     {
         switch(_op)
         {
@@ -69,6 +69,28 @@ protected:
                 library->fill(tensor, distribution, i);
                 break;
             }
+            case ElementWiseUnary::NEG:
+            {
+                switch(data_type)
+                {
+                    case DataType::F32:
+                    case DataType::F16:
+                    {
+                        std::uniform_real_distribution<> distribution(-2.0f, 2.0f);
+                        library->fill(tensor, distribution, i);
+                        break;
+                    }
+                    case DataType::S32:
+                    {
+                        std::uniform_int_distribution<int32_t> distribution(-100, 100);
+                        library->fill(tensor, distribution, i);
+                        break;
+                    }
+                    default:
+                        ARM_COMPUTE_ERROR("DataType for Elementwise Negation Not implemented");
+                }
+                break;
+            }
             default:
                 ARM_COMPUTE_ERROR("Not implemented");
         }
@@ -95,7 +117,7 @@ protected:
         ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
 
         // Fill tensors
-        fill(AccessorType(src), 0);
+        fill(AccessorType(src), 0, data_type);
 
         // Compute function
         elwiseunary_layer.run();
@@ -109,7 +131,7 @@ protected:
         SimpleTensor<T> src{ shape, data_type };
 
         // Fill reference
-        fill(src, 0);
+        fill(src, 0, data_type);
 
         return reference::elementwise_unary<T>(src, _op);
     }
@@ -140,6 +162,17 @@ public:
         ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::EXP);
     }
 };
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class NegValidationFixture : public ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(const TensorShape &shape, DataType data_type)
+    {
+        ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::NEG);
+    }
+};
 } // namespace validation
 } // namespace test
 } // namespace arm_compute
diff --git a/tests/validation/reference/ElementWiseUnary.cpp b/tests/validation/reference/ElementWiseUnary.cpp
index ae7f256339..79310eae0f 100644
--- a/tests/validation/reference/ElementWiseUnary.cpp
+++ b/tests/validation/reference/ElementWiseUnary.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -46,6 +46,9 @@ SimpleTensor<T> elementwise_unary(const SimpleTensor<T> &src, ElementWiseUnary o
             case ElementWiseUnary::EXP:
                 dst[i] = std::exp(src[i]);
                 break;
+            case ElementWiseUnary::NEG:
+                dst[i] = -src[i];
+                break;
             default:
                 ARM_COMPUTE_ERROR("Not implemented");
         }
@@ -56,6 +59,7 @@ SimpleTensor<T> elementwise_unary(const SimpleTensor<T> &src, ElementWiseUnary o
 
 template SimpleTensor<float> elementwise_unary(const SimpleTensor<float> &src, ElementWiseUnary op);
 template SimpleTensor<half> elementwise_unary(const SimpleTensor<half> &src, ElementWiseUnary op);
+template SimpleTensor<int32_t> elementwise_unary(const SimpleTensor<int32_t> &src, ElementWiseUnary op);
 } // namespace reference
 } // namespace validation
 } // namespace test