COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
diff --git a/tests/validation/NEON/FullyConnectedLayer.cpp b/tests/validation/NEON/FullyConnectedLayer.cpp
new file mode 100644
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+++ b/tests/validation/NEON/FullyConnectedLayer.cpp
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+/*
+ * 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 "NEON/Helper.h"
+#include "NEON/NEAccessor.h"
+#include "TypePrinter.h"
+#include "dataset/FullyConnectedLayerDataset.h"
+#include "validation/Datasets.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
+
+#include <random>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::neon;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+const float tolerance_qs8 = 1.0f;   /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
+
+Tensor compute_fully_connected_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt,
+                                     bool transpose_weights, int fixed_point_position)
+{
+    // Create tensors
+    Tensor src  = create_tensor(input_shape, dt, 1, fixed_point_position);
+    Tensor bias = create_tensor(bias_shape, dt, 1, fixed_point_position);
+    Tensor dst  = create_tensor(output_shape, dt, 1, fixed_point_position);
+
+    // Swap the first and second dimension of weights' shape if transpose_weights is true
+    TensorShape ws = weights_shape;
+    if(transpose_weights)
+    {
+        const size_t dimx = ws.x();
+        ws.set(0, ws.y());
+        ws.set(1, dimx);
+    }
+
+    Tensor weights = create_tensor(ws, dt, 1, fixed_point_position);
+
+    // Create and configure function.
+    // Note: We pass the weights already transposed
+    NEFullyConnectedLayer fc;
+    fc.configure(&src, &weights, &bias, &dst, false);
+
+    // Allocate tensors
+    src.allocator()->allocate();
+    weights.allocator()->allocate();
+    bias.allocator()->allocate();
+    dst.allocator()->allocate();
+
+    BOOST_TEST(!src.info()->is_resizable());
+    BOOST_TEST(!weights.info()->is_resizable());
+    BOOST_TEST(!bias.info()->is_resizable());
+    BOOST_TEST(!dst.info()->is_resizable());
+
+    // Fill tensors
+    if(dt == DataType::F32)
+    {
+        std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+        library->fill(NEAccessor(src), distribution, 0);
+        library->fill(NEAccessor(weights), distribution, 1);
+        library->fill(NEAccessor(bias), distribution, 2);
+    }
+    else
+    {
+        library->fill_tensor_uniform(NEAccessor(src), 0);
+        library->fill_tensor_uniform(NEAccessor(weights), 1);
+        library->fill_tensor_uniform(NEAccessor(bias), 2);
+    }
+
+    // Compute NEFullyConnectedLayer function
+    fc.run();
+
+    return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(NEON)
+BOOST_AUTO_TEST_SUITE(FullyConnectedLayer)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration,
+                     SmallFullyConnectedLayerDataset() * boost::unit_test::data::make({ DataType::F32, DataType::QS8 }),
+                     fc_set, dt)
+{
+    // Set fixed point position data type allowed
+    int fixed_point_position = (dt == DataType::F32) ? 0 : 3;
+
+    // Create tensors
+    Tensor src  = create_tensor(fc_set.src_shape, dt, 1, fixed_point_position);
+    Tensor bias = create_tensor(fc_set.bias_shape, dt, 1, fixed_point_position);
+    Tensor dst  = create_tensor(fc_set.dst_shape, dt, 1, fixed_point_position);
+
+    // Swap the first and second dimension of weights' shape if transpose_weights is true
+    TensorShape ws = fc_set.weights_shape;
+    if(fc_set.transpose_weights)
+    {
+        const size_t dimx = ws.x();
+        ws.set(0, ws.y());
+        ws.set(1, dimx);
+    }
+
+    Tensor weights = create_tensor(ws, dt, 1, fixed_point_position);
+
+    BOOST_TEST(src.info()->is_resizable());
+    BOOST_TEST(weights.info()->is_resizable());
+    BOOST_TEST(bias.info()->is_resizable());
+    BOOST_TEST(dst.info()->is_resizable());
+
+    // Create and configure function.
+    // Note: We pass the weights already transposed
+    NEFullyConnectedLayer fc;
+    fc.configure(&src, &weights, &bias, &dst, false);
+
+    // Validate valid region
+    const ValidRegion src_valid_region     = shape_to_valid_region(fc_set.src_shape);
+    const ValidRegion weights_valid_region = shape_to_valid_region(ws);
+    const ValidRegion bias_valid_region    = shape_to_valid_region(fc_set.bias_shape);
+    const ValidRegion dst_valid_region     = shape_to_valid_region(fc_set.dst_shape);
+
+    validate(src.info()->valid_region(), src_valid_region);
+    validate(weights.info()->valid_region(), weights_valid_region);
+    validate(bias.info()->valid_region(), bias_valid_region);
+    validate(dst.info()->valid_region(), dst_valid_region);
+}
+
+BOOST_AUTO_TEST_SUITE(Float)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall,
+                     SmallFullyConnectedLayerDataset() * boost::unit_test::data::make({ DataType::F32 }),
+                     fc_set, dt)
+{
+    // Compute function
+    Tensor dst = compute_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, 0);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, 0);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_f32);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge,
+                     LargeFullyConnectedLayerDataset() * boost::unit_test::data::make({ DataType::F32 }),
+                     fc_set, dt)
+{
+    // Compute function
+    Tensor dst = compute_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, 0);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, 0);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_f32);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE(Quantized)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(RunSmall,
+                     SmallFullyConnectedLayerDataset() * boost::unit_test::data::make({ DataType::QS8 }) * boost::unit_test::data::xrange(4, 7),
+                     fc_set, dt, fixed_point_position)
+{
+    // Compute function
+    Tensor dst = compute_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, fixed_point_position);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, fixed_point_position);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_qs8);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(RunLarge,
+                     LargeFullyConnectedLayerDataset() * boost::unit_test::data::make({ DataType::QS8 }) * boost::unit_test::data::xrange(4, 7),
+                     fc_set, dt, fixed_point_position)
+{
+    // Compute function
+    Tensor dst = compute_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, fixed_point_position);
+
+    // Compute reference
+    RawTensor ref_dst = Reference::compute_reference_fully_connected_layer(fc_set.src_shape, fc_set.weights_shape, fc_set.bias_shape, fc_set.dst_shape, dt, fc_set.transpose_weights, fixed_point_position);
+
+    // Validate output
+    validate(NEAccessor(dst), ref_dst, tolerance_qs8);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif