COMPMID-1493 Create tests/validate_examples/graph_fully_connected

Add graph example with validation for fully-connected layer

Change-Id: I06fcc670b7097609f04eb040fedf56108c9484d2
Signed-off-by: John Kesapides <john.kesapides@arm.com>
Reviewed-on: https://review.mlplatform.org/c/764
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

3 files changed, 614 insertions, 8 deletions

diff --git a/tests/validate_examples/graph_fully_connected.cpp b/tests/validate_examples/graph_fully_connected.cpp
new file mode 100644
index 0000000000..e4f51175f0
--- /dev/null
+++ b/tests/validate_examples/graph_fully_connected.cpp
@@ -0,0 +1,596 @@
+/*
+ * 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/graph.h"
+
+#include "support/ToolchainSupport.h"
+
+#include "tests/NEON/Accessor.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/reference/FullyConnectedLayer.h"
+#include "tests/validation/reference/Permute.h"
+
+#include "utils/CommonGraphOptions.h"
+#include "utils/GraphUtils.h"
+#include "utils/Utils.h"
+
+#include "ValidateExample.h"
+
+#include <utility>
+
+using namespace arm_compute::utils;
+using namespace arm_compute::graph::frontend;
+using namespace arm_compute::graph_utils;
+using namespace arm_compute::graph;
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::validation;
+namespace
+{
+/** Structure holding all the input tensor graph parameters */
+struct TensorParams
+{
+    int              width{ 1 };
+    int              height{ 1 };
+    int              fm{ 1 };
+    int              batch{ 1 };
+    QuantizationInfo quant_info{ 1.0f, 0 };
+    uint64_t         range_low{ 0 };
+    uint64_t         range_high{ 16 };
+};
+/** Structure holding all the verification graph parameters */
+struct VerificationParams
+{
+    float absolute_tolerance{ -1.f };
+    float relative_tolerance{ -1.f };
+    float tolerance_number{ -1.f };
+};
+
+/** Structure holding all the common graph parameters */
+struct FrameworkParams
+{
+    bool                       help{ false };
+    int                        threads{ 0 };
+    arm_compute::graph::Target target{ arm_compute::graph::Target::NEON };
+};
+
+/** Structure holding all the fully_connected layer graph parameters */
+struct FullyConnectedParams
+{
+    arm_compute::DataType   data_type{ DataType::F32 };
+    arm_compute::DataLayout data_layout{ DataLayout::NCHW };
+    FullyConnectedLayerInfo info{};
+    int                     num_outputs{ 1 };
+};
+
+/** Structure holding all the graph Example parameters */
+struct ExampleParams
+{
+    FrameworkParams      common_params{};
+    TensorParams         input{};
+    TensorParams         weights{};
+    TensorParams         output{};
+    VerificationParams   verification{};
+    FullyConnectedParams fully_connected{};
+};
+
+/** Formatted output of the fully_connectedParams type
+ *
+ * @param[out] os            Output stream.
+ * @param[in]  common_params fully_connected parameters to output
+ *
+ * @return Modified output stream.
+ */
+::std::ostream &operator<<(::std::ostream &os, const ExampleParams &common_params)
+{
+    std::string false_str = std::string("false");
+    std::string true_str  = std::string("true");
+
+    os << "Threads : " << common_params.common_params.threads << std::endl;
+    os << "Target : " << common_params.common_params.target << std::endl;
+    os << "Data type : " << common_params.fully_connected.data_type << std::endl;
+    os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")"
+       << std::endl;
+    os << "Number of outputs : " << common_params.fully_connected.num_outputs << std::endl;
+    return os;
+}
+
+/** fully_connected command line options used to configure the graph examples
+ *
+ * (Similar to common options)
+ * The options in this object get populated when "parse()" is called on the parser used to construct it.
+ * The expected workflow is:
+ *
+ * CommandLineParser parser;
+ * CommonOptions options( parser );
+ * parser.parse(argc, argv);
+ */
+class FullyConnectedOptions final
+{
+public:
+    explicit FullyConnectedOptions(CommandLineParser &parser) noexcept
+        : width(parser.add_option<SimpleOption<int>>("width", 3)),
+          batch(parser.add_option<SimpleOption<int>>("batch", 1)),
+          help(parser.add_option<ToggleOption>("help")),
+          threads(parser.add_option<SimpleOption<int>>("threads")),
+          target(),
+          data_type(),
+          absolute_tolerance(parser.add_option<SimpleOption<float>>("abs_tolerance", -1.0f)),
+          relative_tolerance(parser.add_option<SimpleOption<float>>("rel_tolerance", -1.0f)),
+          tolerance_number(parser.add_option<SimpleOption<float>>("tolerance_num", -1.0f)),
+          input_scale(parser.add_option<SimpleOption<float>>("input_scale", 1.0f)),
+          input_offset(parser.add_option<SimpleOption<int>>("input_offset", 0)),
+          weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)),
+          weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)),
+          output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)),
+          output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)),
+          num_outputs(parser.add_option<SimpleOption<int>>("num_outputs", 1)),
+          input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")),
+          input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")),
+          weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")),
+          weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high"))
+    {
+        const std::set<arm_compute::graph::Target> supported_targets
+        {
+            Target::NEON,
+            Target::CL,
+            Target::GC,
+        };
+
+        const std::set<arm_compute::DataType> supported_data_types
+        {
+            DataType::F16,
+            DataType::F32,
+            DataType::QASYMM8,
+        };
+
+        target    = parser.add_option<EnumOption<Target>>("target", supported_targets, Target::NEON);
+        data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32);
+
+        target->set_help("Target to execute on");
+        data_type->set_help("Data type to use");
+        help->set_help("Show this help message");
+        width->set_help("Set Input dimension width");
+        batch->set_help("Set Input dimension batch");
+        absolute_tolerance->set_help("Absolute tolerance used for verification");
+        relative_tolerance->set_help("Absolute tolerance used for verification");
+        tolerance_number->set_help("Absolute tolerance used for verification");
+        input_scale->set_help("Quantization scale from QASYMM8");
+        input_offset->set_help("Quantization offset from QASYMM8");
+        weights_scale->set_help("Quantization scale from QASYMM8");
+        weights_offset->set_help("Quantization offset from QASYMM8");
+        output_scale->set_help("Quantization scale from QASYMM8");
+        output_offset->set_help("Quantization offset from QASYMM8");
+        num_outputs->set_help("Number of outputs.");
+        input_range_low->set_help("Lower bound for input randomization range");
+        input_range_high->set_help("Lower bound for input randomization range");
+        weights_range_low->set_help("Lower bound for input randomization range");
+        weights_range_high->set_help("Lower bound for input randomization range");
+    }
+
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    FullyConnectedOptions(const FullyConnectedOptions &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    FullyConnectedOptions &operator=(const FullyConnectedOptions &) = delete;
+    /** Allow instances of this class to be moved */
+    FullyConnectedOptions(FullyConnectedOptions &&) noexcept(true) = default;
+    /** Allow instances of this class to be moved */
+    FullyConnectedOptions &operator=(FullyConnectedOptions &&) noexcept(true) = default;
+    /** Default destructor */
+    ~FullyConnectedOptions() = default;
+
+    SimpleOption<int>                      *width;              /**< Input width */
+    SimpleOption<int>                      *batch;              /**< Input batch */
+    ToggleOption                           *help;               /**< show help message */
+    SimpleOption<int>                      *threads;            /**< Number of threads option */
+    EnumOption<arm_compute::graph::Target> *target;             /**< Graph execution target */
+    EnumOption<arm_compute::DataType>      *data_type;          /**< Graph data type */
+    SimpleOption<float>                    *absolute_tolerance; /**< Absolute tolerance used in verification */
+    SimpleOption<float>                    *relative_tolerance; /**< Relative tolerance used in verification */
+    SimpleOption<float>                    *tolerance_number;   /**< Tolerance number used in verification */
+    SimpleOption<float>                    *input_scale;        /**< Input Quantization scale from QASSYMM8 */
+    SimpleOption<int>                      *input_offset;       /**< Input Quantization offset from QASSYMM8 */
+    SimpleOption<float>                    *weights_scale;      /**< Weights Quantization scale from QASSYMM8 */
+    SimpleOption<int>                      *weights_offset;     /**< Weights Quantization offset from QASSYMM8 */
+    SimpleOption<float>                    *output_scale;       /**< Output Quantization scale from QASSYMM8 */
+    SimpleOption<int>                      *output_offset;      /**< Output Quantization offset from QASSYMM8 */
+    SimpleOption<int>                      *num_outputs;        /**< Number of outputs. */
+    SimpleOption<uint64_t>                 *input_range_low;    /**< Lower bound for input randomization range */
+    SimpleOption<uint64_t>                 *input_range_high;   /**< Upper bound for input randomization range */
+    SimpleOption<uint64_t>                 *weights_range_low;  /**< Lower bound for weights randomization range */
+    SimpleOption<uint64_t>                 *weights_range_high; /**< Upper bound for weights randomization range */
+};
+
+/** Consumes the fully_connected graph options and creates a structure containing any information
+ *
+ * @param[in] options Options to consume
+ *
+ * @return fully_connectedparams structure containing the common graph parameters
+ */
+ExampleParams consume_fully_connected_graph_parameters(FullyConnectedOptions &options)
+{
+    ExampleParams common_params;
+
+    common_params.common_params.help    = options.help->is_set() ? options.help->value() : false;
+    common_params.common_params.threads = options.threads->value();
+    common_params.common_params.target  = options.target->value();
+
+    common_params.input.width             = options.width->value();
+    common_params.input.batch             = options.batch->value();
+    common_params.input.quant_info.scale  = options.input_scale->value();
+    common_params.input.quant_info.offset = options.input_offset->value();
+    common_params.input.range_low         = options.input_range_low->value();
+    common_params.input.range_high        = options.input_range_high->value();
+
+    common_params.weights.quant_info.scale  = options.weights_scale->value();
+    common_params.weights.quant_info.offset = options.weights_offset->value();
+    common_params.weights.range_low         = options.weights_range_low->value();
+    common_params.weights.range_high        = options.weights_range_high->value();
+
+    common_params.output.quant_info.scale  = options.output_scale->value();
+    common_params.output.quant_info.offset = options.output_offset->value();
+
+    common_params.fully_connected.data_type   = options.data_type->value();
+    common_params.fully_connected.num_outputs = options.num_outputs->value();
+
+    common_params.verification.absolute_tolerance = options.absolute_tolerance->value();
+    common_params.verification.relative_tolerance = options.relative_tolerance->value();
+    common_params.verification.tolerance_number   = options.tolerance_number->value();
+
+    return common_params;
+}
+
+/** fully_connectedLayer Graph example validation accessor class */
+template <typename D>
+class FullyConnectedVerifyAccessor final : public graph::ITensorAccessor
+{
+public:
+    using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type;
+
+    /** Constructor
+     *
+     * @param[in] params fully_connected parameters
+     */
+    explicit FullyConnectedVerifyAccessor(ExampleParams &params)
+        : _params(params)
+    {
+    }
+
+    // Inherited methods overridden:
+    bool access_tensor(ITensor &tensor) override
+    {
+        const RelativeTolerance<float> rel_tolerance(relative_tolenace(_params.verification.relative_tolerance));  /**< Relative tolerance */
+        const AbsoluteTolerance<float> abs_tolerance(absolute_tolerance(_params.verification.absolute_tolerance)); /**< Absolute tolerance */
+        const float                    tolerance_num(tolerance_number(_params.verification.tolerance_number));     /**< Tolerance number */
+
+        // Calculate Tensor shapes for verification
+        const TensorShape      input_shape        = TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch);
+        const TensorDescriptor input_descriptor   = TensorDescriptor(input_shape, _params.fully_connected.data_type, _params.input.quant_info);
+        const TensorDescriptor weights_descriptor = FullyConnectedLayerNode::compute_weights_descriptor(input_descriptor,
+                                                                                                        _params.fully_connected.num_outputs,
+                                                                                                        _params.fully_connected.info,
+                                                                                                        _params.weights.quant_info);
+        const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info);
+
+        //Create Input tensors
+        SimpleTensor<D>     src{ input_descriptor.shape, _params.fully_connected.data_type, 1, input_descriptor.quant_info };
+        SimpleTensor<D>     weights{ weights_descriptor.shape, _params.fully_connected.data_type, 1, weights_descriptor.quant_info };
+        SimpleTensor<TBias> bias{ TensorShape(tensor.info()->tensor_shape().x()), _params.fully_connected.data_type, 1, _params.input.quant_info };
+
+        //Fill the tensors with random values
+        fill_tensor<D>(src, 0, static_cast<D>(_params.input.range_low), static_cast<D>(_params.input.range_high));
+        fill_tensor<D>(weights, 1, static_cast<D>(_params.weights.range_low), static_cast<D>(_params.weights.range_high));
+        fill_tensor<TBias>(bias, 2, static_cast<TBias>(_params.input.range_low), static_cast<TBias>(_params.input.range_high));
+
+        //Calculate reference
+        SimpleTensor<D> output = reference::fully_connected_layer<D>(src, weights, bias, output_desciptor.shape, _params.output.quant_info);
+
+        arm_compute::test::validation::validate(Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance);
+
+        return false;
+    }
+
+private:
+    /** Fill tensor with Random values.
+     *
+     * Validate the given tensor against the reference result.
+     *
+     * @param[out] tensor The tensor we want to file
+     * @param[in]  seed   seed for the randomization function
+     * @param[in]  low    lower bound for random values
+     * @param[in]  high   upper bound for random values
+     *
+     * @return None.
+     */
+    template <typename T>
+    void fill_tensor(arm_compute::test::SimpleTensor<T> &tensor, std::random_device::result_type seed, T low, T high)
+    {
+        std::mt19937 gen(seed);
+        switch(tensor.data_type())
+        {
+            case arm_compute::DataType::QASYMM8:
+            {
+                const uint8_t qasymm8_low  = tensor.quantization_info().quantize(low, RoundingPolicy::TO_NEAREST_UP);
+                const uint8_t qasymm8_high = tensor.quantization_info().quantize(high, RoundingPolicy::TO_NEAREST_UP);
+
+                std::uniform_int_distribution<uint8_t> distribution(qasymm8_low, qasymm8_high);
+
+                for(int i = 0; i < tensor.num_elements(); ++i)
+                {
+                    tensor[i] = tensor.quantization_info().quantize(distribution(gen), RoundingPolicy::TO_NEAREST_UP);
+                }
+
+                break;
+            }
+            case arm_compute::DataType::S32:
+            {
+                std::uniform_int_distribution<int32_t> distribution(static_cast<int32_t>(low), static_cast<uint32_t>(high));
+
+                for(int i = 0; i < tensor.num_elements(); ++i)
+                {
+                    tensor[i] = distribution(gen);
+                }
+
+                break;
+            }
+
+            case arm_compute::DataType::F16:
+            {
+                std::uniform_real_distribution<float> distribution(static_cast<half>(low), static_cast<half>(high));
+
+                for(int i = 0; i < tensor.num_elements(); ++i)
+                {
+                    tensor[i] = static_cast<half>(distribution(gen));
+                }
+                break;
+            }
+            case arm_compute::DataType::F32:
+            {
+                std::uniform_real_distribution<float> distribution(static_cast<float>(low), static_cast<float>(high));
+
+                for(int i = 0; i < tensor.num_elements(); ++i)
+                {
+                    tensor[i] = distribution(gen);
+                }
+
+                break;
+            }
+            default:
+                ARM_COMPUTE_ERROR("NOT SUPPORTED!");
+        }
+    }
+    /** Select relative tolerance.
+     *
+     * Select relative tolerance if not supplied by user.
+     *
+     * @param[in] user_value supplied relative tolerance. -1 designates no user input
+     *
+     * @return Appropriate relative tolerance.
+     */
+    float relative_tolenace(float user_value)
+    {
+        const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance
+        {
+            {
+                arm_compute::graph::Target::CL,
+                {   { DataType::F16, 0.2f },
+                    { DataType::F32, 0.05f },
+                    { DataType::QASYMM8, 1.0f }
+                }
+            },
+            {
+                arm_compute::graph::Target::NEON,
+                {   { DataType::F16, 0.2f },
+                    { DataType::F32, 0.01f },
+                    { DataType::QASYMM8, 1.0f }
+                }
+            }
+        };
+        if(user_value == -1)
+        {
+            return relative_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type);
+        }
+
+        return user_value;
+    }
+
+    /** Select absolute tolerance.
+     *
+     * Select absolute tolerance if not supplied by user.
+     *
+     * @param[in] user_value supplied absolute tolerance. -1 designates no user input
+     *
+     * @return Appropriate absolute tolerance.
+     */
+    float absolute_tolerance(float user_value)
+    {
+        const std::map<Target, const std::map<DataType, float>> absolute_tolerance
+        {
+            {
+                Target::CL,
+                {   { DataType::F16, 0.0f },
+                    { DataType::F32, 0.0001f },
+                    { DataType::QASYMM8, 1.0f }
+                }
+            },
+            {
+                Target::NEON,
+                {   { DataType::F16, 0.3f },
+                    { DataType::F32, 0.1f },
+                    { DataType::QASYMM8, 1.0f }
+                }
+            }
+        };
+
+        if(user_value == -1)
+        {
+            return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type);
+        }
+        return user_value;
+    }
+    /** Select tolerance number.
+     *
+     * Select tolerance number if not supplied by user.
+     *
+     * @param[in] user_value supplied tolerance number. -1 designates no user input
+     *
+     * @return Appropriate tolerance number.
+     */
+    float tolerance_number(float user_value)
+    {
+        const std::map<Target, const std::map<DataType, float>> absolute_tolerance
+        {
+            {
+                Target::CL,
+                {   { DataType::F16, 0.07f },
+                    { DataType::F32, 0.07f },
+                    { DataType::QASYMM8, 0.0f }
+                }
+            },
+            {
+                Target::NEON,
+                {   { DataType::F16, 0.07f },
+                    { DataType::F32, 0.0f },
+                    { DataType::QASYMM8, 0.0f }
+                }
+            }
+        };
+
+        if(user_value == -1)
+        {
+            return absolute_tolerance.at(_params.common_params.target).at(_params.fully_connected.data_type);
+        }
+        return user_value;
+    }
+
+    ExampleParams _params;
+};
+
+/** Generates appropriate fully_connected verify accessor
+ *
+ * @param[in] params User supplied parameters for fully_connected.
+ *
+ * @return A fully_connected verify accessor for the requested datatype.
+ */
+inline std::unique_ptr<graph::ITensorAccessor> get_fully_connected_verify_accessor(ExampleParams params)
+{
+    switch(params.fully_connected.data_type)
+    {
+        case DataType::QASYMM8:
+        {
+            return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<uint8_t>>(
+                       params);
+        }
+        case DataType::F16:
+        {
+            return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<half>>(
+                       params);
+        }
+        case DataType::F32:
+        {
+            return arm_compute::support::cpp14::make_unique<FullyConnectedVerifyAccessor<float>>(
+                       params);
+        }
+        default:
+            ARM_COMPUTE_ERROR("NOT SUPPORTED!");
+    }
+}
+
+} // namespace
+
+class Graphfully_connectedValidateExample final : public ValidateExample
+{
+public:
+    Graphfully_connectedValidateExample()
+        : graph(0, "fully_connected Graph example")
+    {
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        CommandLineParser parser;
+
+        FullyConnectedOptions Options(parser);
+
+        parser.parse(argc, argv);
+
+        ExampleParams params = consume_fully_connected_graph_parameters(Options);
+
+        if(params.common_params.help)
+        {
+            parser.print_help(argv[0]);
+            return false;
+        }
+
+        std::cout << params << std::endl;
+
+        // Create input descriptor
+        const TensorShape      input_shape      = TensorShape(params.input.width, params.input.height, params.input.fm, params.input.batch);
+        const TensorDescriptor input_descriptor = TensorDescriptor(input_shape, params.fully_connected.data_type, params.input.quant_info, params.fully_connected.data_layout);
+
+        const PixelValue lower = PixelValue(params.input.range_low, params.fully_connected.data_type, params.input.quant_info);
+        const PixelValue upper = PixelValue(params.input.range_high, params.fully_connected.data_type, params.input.quant_info);
+
+        const PixelValue weights_lower = PixelValue(params.weights.range_low, params.fully_connected.data_type, params.weights.quant_info);
+        const PixelValue weights_upper = PixelValue(params.weights.range_high, params.fully_connected.data_type, params.weights.quant_info);
+
+        graph << params.common_params.target
+              << InputLayer(input_descriptor, get_random_accessor(lower, upper, 0))
+              << FullyConnectedLayer(params.fully_connected.num_outputs,
+                                     get_random_accessor(weights_lower, weights_upper, 1),
+                                     get_random_accessor(lower, upper, 2),
+                                     params.fully_connected.info, params.weights.quant_info, params.output.quant_info)
+              << OutputLayer(get_fully_connected_verify_accessor(params));
+
+        GraphConfig config;
+        config.num_threads = params.common_params.threads;
+
+        graph.finalize(params.common_params.target, config);
+
+        return true;
+    }
+
+    void do_run() override
+    {
+        graph.run();
+    }
+
+    void do_teardown() override
+    {
+    }
+
+private:
+    Stream graph;
+};
+
+/** Main program for Graph fully_connected test
+ *
+ * @param[in] argc Number of arguments
+ * @param[in] argv Arguments ( Input dimensions [width, batch]
+ *                             Fully connected  [num_outputs,type]
+ *                             Verification[tolerance_number,absolute_tolerance,relative_tolerance] )
+ *
+ */
+int main(int argc, char **argv)
+{
+    return arm_compute::utils::run_example<Graphfully_connectedValidateExample>(argc, argv);
+}
diff --git a/tests/validation/reference/FullyConnectedLayer.cpp b/tests/validation/reference/FullyConnectedLayer.cpp
index d65d0caab0..07ddf6d308 100644
--- a/tests/validation/reference/FullyConnectedLayer.cpp
+++ b/tests/validation/reference/FullyConnectedLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -105,10 +105,16 @@ void vector_matrix_multiply(const SimpleTensor<T> &src, const SimpleTensor<T> &w
 } // namespace
 
 template <typename T, typename TB>
-SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &dst_shape)
+SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &dst_shape, QuantizationInfo out_quant_info)
 {
+    // if no explicit quantization has been set you the same as src
+    if(out_quant_info == QuantizationInfo())
+    {
+        out_quant_info = src.quantization_info();
+    }
+
     // Create reference
-    SimpleTensor<T> dst{ TensorShape{ dst_shape }, src.data_type(), 1, src.quantization_info() };
+    SimpleTensor<T> dst{ TensorShape{ dst_shape }, src.data_type(), 1, out_quant_info };
 
     // Sanity checks
     const int          num_batch_dimensions = std::max(0, static_cast<int>(dst_shape.num_dimensions()) - 1);
@@ -145,9 +151,12 @@ SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTe
     return dst;
 }
 
-template SimpleTensor<float> fully_connected_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &dst_shape);
-template SimpleTensor<half> fully_connected_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &dst_shape);
-template SimpleTensor<uint8_t> fully_connected_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &dst_shape);
+template SimpleTensor<float> fully_connected_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &dst_shape,
+                                                   QuantizationInfo out_quant_info);
+template SimpleTensor<half> fully_connected_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &dst_shape,
+                                                  QuantizationInfo out_quant_info);
+template SimpleTensor<uint8_t> fully_connected_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &dst_shape,
+                                                     QuantizationInfo out_quant_info);
 } // namespace reference
 } // namespace validation
 } // namespace test
diff --git a/tests/validation/reference/FullyConnectedLayer.h b/tests/validation/reference/FullyConnectedLayer.h
index 1dfb496924..f474a1cfb8 100644
--- a/tests/validation/reference/FullyConnectedLayer.h
+++ b/tests/validation/reference/FullyConnectedLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -36,7 +36,8 @@ namespace validation
 namespace reference
 {
 template <typename T, typename TB>
-SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &dst_shape);
+SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &dst_shape,
+                                      QuantizationInfo out_quant_info = QuantizationInfo());
 } // namespace reference
 } // namespace validation
 } // namespace test