COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
diff --git a/tests/validation/NEON/SoftmaxLayer.cpp b/tests/validation/NEON/SoftmaxLayer.cpp
new file mode 100644
index 0000000..f5c7a21
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+++ b/tests/validation/NEON/SoftmaxLayer.cpp
@@ -0,0 +1,196 @@
+/*
+ * Copyright (c) 2017 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 "Globals.h"
+#include "NEON/Helper.h"
+#include "NEON/NEAccessor.h"
+#include "TensorLibrary.h"
+#include "TypePrinter.h"
+#include "Utils.h"
+#include "validation/Datasets.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+
+#include "boost_wrapper.h"
+
+#include <random>
+#include <string>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::neon;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+/** Tolerance for float operations */
+const float tolerance = 0.000001f;
+/** Tolerance for fixed point operations */
+const float tolerance_fixed_point = 2.f;
+
+/** Compute Neon softmax layer function.
+ *
+ * @param[in] shape                Shape of the input and output tensors.
+ * @param[in] dt                   Shape Data type of tensors.
+ * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers.
+ *
+ * @return Computed output tensor.
+ */
+Tensor compute_softmax_layer(const TensorShape &shape, DataType dt, int fixed_point_position = 0)
+{
+    // Create tensors
+    Tensor src = create_tensor(shape, dt, 1, fixed_point_position);
+    Tensor dst = create_tensor(shape, dt, 1, fixed_point_position);
+
+    // Create and configure function
+    NESoftmaxLayer smx_layer;
+    smx_layer.configure(&src, &dst);
+
+    // Allocate tensors
+    src.allocator()->allocate();
+    dst.allocator()->allocate();
+
+    BOOST_TEST(!src.info()->is_resizable());
+    BOOST_TEST(!dst.info()->is_resizable());
+
+    // Fill tensors
+    if(arm_compute::is_data_type_float(dt))
+    {
+        std::uniform_real_distribution<> distribution(-10, 10);
+        library->fill(NEAccessor(src), distribution, 0);
+    }
+    else
+    {
+        int                             one_fixed = 1 << fixed_point_position;
+        std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
+        library->fill(NEAccessor(src), distribution, 0);
+    }
+
+    // Compute function
+    smx_layer.run();
+
+    return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(NEON)
+BOOST_AUTO_TEST_SUITE(SoftmaxLayer)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration, (SmallShapes() + LargeShapes()) * CNNDataTypes(), shape, dt)
+{
+    // Set fixed point position data type allowed
+    int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
+
+    // Create tensors
+    Tensor src = create_tensor(shape, dt, 1, fixed_point_position);
+    Tensor dst = create_tensor(shape, dt, 1, fixed_point_position);
+
+    BOOST_TEST(src.info()->is_resizable());
+    BOOST_TEST(dst.info()->is_resizable());
+
+    // Create and configure function
+    NESoftmaxLayer smx_layer;
+    smx_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);
+
+    // Validate padding
+    int               step = 16 / arm_compute::data_size_from_type(dt);
+    const PaddingSize padding(0, required_padding(shape.x(), step), 0, 0);
+    validate(src.info()->padding(), padding);
+    validate(dst.info()->padding(), padding);
+}
+
+BOOST_AUTO_TEST_SUITE(Float)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall, SmallShapes() * CNNFloatDataTypes(), shape, dt)
+{
+    // Compute function
+    Tensor dst = compute_softmax_layer(shape, dt);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_softmax_layer(shape, dt);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge, LargeShapes() * CNNFloatDataTypes(), shape, dt)
+{
+    // Compute function
+    Tensor dst = compute_softmax_layer(shape, dt);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_softmax_layer(shape, dt);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE(Quantized)
+// Testing for fixed point position [1,6) as reciprocal limits the maximum fixed point position to 5
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall, SmallShapes() * CNNFixedPointDataTypes() * boost::unit_test::data::xrange(1, 6),
+                     shape, dt, fixed_point_position)
+{
+    // Compute function
+    Tensor dst = compute_softmax_layer(shape, dt, fixed_point_position);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_softmax_layer(shape, dt, fixed_point_position);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_fixed_point);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge, LargeShapes() * CNNFixedPointDataTypes() * boost::unit_test::data::xrange(1, 6),
+                     shape, dt, fixed_point_position)
+{
+    // Compute function
+    Tensor dst = compute_softmax_layer(shape, dt, fixed_point_position);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_softmax_layer(shape, dt, fixed_point_position);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_fixed_point);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif