COMPMID-1310: Create graph validation executables.

Change-Id: I9e0b57b1b83fe5a95777cdaeddba6ecef650bafc
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/138697
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

61 files changed, 1770 insertions, 1783 deletions

diff --git a/arm_compute/core/utils/misc/Utility.h b/arm_compute/core/utils/misc/Utility.h
index a2784a2fc0..0a9f180b4c 100644
--- a/arm_compute/core/utils/misc/Utility.h
+++ b/arm_compute/core/utils/misc/Utility.h
@@ -192,6 +192,21 @@ inline bool check_aligned(void *ptr, const size_t alignment)
 {
     return (reinterpret_cast<std::uintptr_t>(ptr) % alignment) == 0;
 }
+
+/** Convert string to lower case.
+ *
+ * @param[in] string To be converted string.
+ *
+ * @return Lower case string.
+ */
+inline std::string tolower(std::string string)
+{
+    std::transform(string.begin(), string.end(), string.begin(), [](unsigned char c)
+    {
+        return std::tolower(c);
+    });
+    return string;
+}
 } // namespace utility
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_MISC_UTILITY_H__ */
diff --git a/arm_compute/graph/Graph.h b/arm_compute/graph/Graph.h
index 16f5f97986..2a776826e5 100644
--- a/arm_compute/graph/Graph.h
+++ b/arm_compute/graph/Graph.h
@@ -72,7 +72,7 @@ public:
      * @tparam NT Node operation
      * @tparam Ts Arguments to operation
      *
-     * @param args Node arguments
+     * @param[in] args Node arguments
      *
      * @return ID of the node
      */
@@ -114,9 +114,11 @@ public:
     GraphID id() const;
     /** Returns graph input nodes
      *
-     * @return vector containing the graph inputs
+     * @param[in] type Type of nodes to return
+     *
+     * @return vector containing the graph node of given type
      */
-    const std::vector<NodeID> &inputs();
+    const std::vector<NodeID> &nodes(NodeType type);
     /** Returns nodes of graph
      *
      * @warning Nodes can be nullptr if they have been removed during the mutation steps of the graph
@@ -238,10 +240,7 @@ inline NodeID Graph::add_node(Ts &&... args)
     node->set_id(nid);
 
     // Keep track of input nodes
-    if(node->type() == NodeType::Input)
-    {
-        _tagged_nodes[NodeType::Input].push_back(nid);
-    }
+    _tagged_nodes[node->type()].push_back(nid);
 
     // Associate a new tensor with each output
     for(auto &output : node->_outputs)
diff --git a/arm_compute/graph/TypeLoader.h b/arm_compute/graph/TypeLoader.h
new file mode 100644
index 0000000000..77f096133d
--- /dev/null
+++ b/arm_compute/graph/TypeLoader.h
@@ -0,0 +1,105 @@
+/*
+ * 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.
+ */
+#ifndef __ARM_COMPUTE_GRAPH_TYPE_LOADER_H__
+#define __ARM_COMPUTE_GRAPH_TYPE_LOADER_H__
+
+#include "arm_compute/graph/Types.h"
+
+#include <istream>
+
+namespace arm_compute
+{
+/** Converts a string to a strong types enumeration @ref DataType
+ *
+ * @param[in] name String to convert
+ *
+ * @return Converted DataType enumeration
+ */
+arm_compute::DataType data_type_from_name(const std::string &name);
+
+/** Input Stream operator for @ref DataType
+ *
+ * @param[in]  stream    Stream to parse
+ * @param[out] data_type Output data type
+ *
+ * @return Updated stream
+ */
+inline ::std::istream &operator>>(::std::istream &stream, arm_compute::DataType &data_type)
+{
+    std::string value;
+    stream >> value;
+    data_type = data_type_from_name(value);
+    return stream;
+}
+
+/** Converts a string to a strong types enumeration @ref DataLayout
+ *
+ * @param[in] name String to convert
+ *
+ * @return Converted DataLayout enumeration
+ */
+arm_compute::DataLayout data_layout_from_name(const std::string &name);
+
+/** Input Stream operator for @ref DataLayout
+ *
+ * @param[in]  stream      Stream to parse
+ * @param[out] data_layout Output data layout
+ *
+ * @return Updated stream
+ */
+inline ::std::istream &operator>>(::std::istream &stream, arm_compute::DataLayout &data_layout)
+{
+    std::string value;
+    stream >> value;
+    data_layout = data_layout_from_name(value);
+    return stream;
+}
+
+namespace graph
+{
+/** Converts a string to a strong types enumeration @ref Target
+ *
+ * @param[in] name String to convert
+ *
+ * @return Converted Target enumeration
+ */
+Target target_from_name(const std::string &name);
+
+/** Input Stream operator for @ref Target
+ *
+ * @param[in]  stream Stream to parse
+ * @param[out] target Output target
+ *
+ * @return Updated stream
+ */
+inline ::std::istream &operator>>(::std::istream &stream, Target &target)
+{
+    std::string value;
+    stream >> value;
+    target = target_from_name(value);
+    return stream;
+}
+} // namespace graph
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GRAPH_TYPE_LOADER_H__ */
diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h
index 177a5e2f38..c3601f2373 100644
--- a/arm_compute/graph/TypePrinter.h
+++ b/arm_compute/graph/TypePrinter.h
@@ -28,89 +28,12 @@
 #include "arm_compute/core/Types.h"
 #include "arm_compute/graph/Types.h"
 
+#include "utils/TypePrinter.h"
+
 namespace arm_compute
 {
 namespace graph
 {
-/** Formatted output of the Dimensions type. */
-template <typename T>
-inline ::std::ostream &operator<<(::std::ostream &os, const arm_compute::Dimensions<T> &dimensions)
-{
-    if(dimensions.num_dimensions() > 0)
-    {
-        os << dimensions[0];
-
-        for(unsigned int d = 1; d < dimensions.num_dimensions(); ++d)
-        {
-            os << "x" << dimensions[d];
-        }
-    }
-
-    return os;
-}
-
-/** Formatted output of the Size2D type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const Size2D &size)
-{
-    os << size.width << "x" << size.height;
-
-    return os;
-}
-
-/** Formatted output of the DataType type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const DataType &data_type)
-{
-    switch(data_type)
-    {
-        case DataType::UNKNOWN:
-            os << "UNKNOWN";
-            break;
-        case DataType::U8:
-            os << "U8";
-            break;
-        case DataType::QASYMM8:
-            os << "QASYMM8";
-            break;
-        case DataType::S8:
-            os << "S8";
-            break;
-        case DataType::U16:
-            os << "U16";
-            break;
-        case DataType::S16:
-            os << "S16";
-            break;
-        case DataType::U32:
-            os << "U32";
-            break;
-        case DataType::S32:
-            os << "S32";
-            break;
-        case DataType::U64:
-            os << "U64";
-            break;
-        case DataType::S64:
-            os << "S64";
-            break;
-        case DataType::F16:
-            os << "F16";
-            break;
-        case DataType::F32:
-            os << "F32";
-            break;
-        case DataType::F64:
-            os << "F64";
-            break;
-        case DataType::SIZET:
-            os << "SIZET";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
-
 /** Formatted output of the Target. */
 inline ::std::ostream &operator<<(::std::ostream &os, const Target &target)
 {
@@ -135,24 +58,6 @@ inline ::std::ostream &operator<<(::std::ostream &os, const Target &target)
     return os;
 }
 
-/** Formatted output of the DataLayout */
-inline ::std::ostream &operator<<(::std::ostream &os, const DataLayout &data_layout)
-{
-    switch(data_layout)
-    {
-        case DataLayout::NCHW:
-            os << "NCHW";
-            break;
-        case DataLayout::NHWC:
-            os << "NHWC";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
-
 inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type)
 {
     switch(node_type)
@@ -224,100 +129,6 @@ inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type)
     return os;
 }
 
-/** Formatted output of the activation function type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const ActivationLayerInfo::ActivationFunction &act_function)
-{
-    switch(act_function)
-    {
-        case ActivationLayerInfo::ActivationFunction::ABS:
-            os << "ABS";
-            break;
-        case ActivationLayerInfo::ActivationFunction::LINEAR:
-            os << "LINEAR";
-            break;
-        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-            os << "LOGISTIC";
-            break;
-        case ActivationLayerInfo::ActivationFunction::RELU:
-            os << "RELU";
-            break;
-        case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
-            os << "BOUNDED_RELU";
-            break;
-        case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
-            os << "LEAKY_RELU";
-            break;
-        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-            os << "SOFT_RELU";
-            break;
-        case ActivationLayerInfo::ActivationFunction::SQRT:
-            os << "SQRT";
-            break;
-        case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
-            os << "LU_BOUNDED_RELU";
-            break;
-        case ActivationLayerInfo::ActivationFunction::SQUARE:
-            os << "SQUARE";
-            break;
-        case ActivationLayerInfo::ActivationFunction::TANH:
-            os << "TANH";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
-
-inline std::string to_string(const ActivationLayerInfo::ActivationFunction &act_function)
-{
-    std::stringstream str;
-    str << act_function;
-    return str.str();
-}
-
-/** Formatted output of the PoolingType type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const PoolingType &pool_type)
-{
-    switch(pool_type)
-    {
-        case PoolingType::AVG:
-            os << "AVG";
-            break;
-        case PoolingType::MAX:
-            os << "MAX";
-            break;
-        case PoolingType::L2:
-            os << "L2";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
-
-/** Formatted output of the NormType type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const NormType &norm_type)
-{
-    switch(norm_type)
-    {
-        case NormType::CROSS_MAP:
-            os << "CROSS_MAP";
-            break;
-        case NormType::IN_MAP_1D:
-            os << "IN_MAP_1D";
-            break;
-        case NormType::IN_MAP_2D:
-            os << "IN_MAP_2D";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
-
 /** Formatted output of the EltwiseOperation type. */
 inline ::std::ostream &operator<<(::std::ostream &os, const EltwiseOperation &eltwise_op)
 {
@@ -401,52 +212,6 @@ inline ::std::ostream &operator<<(::std::ostream &os, const DepthwiseConvolution
 
     return os;
 }
-
-/** Formatted output of the PadStrideInfo type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const PadStrideInfo &pad_stride_info)
-{
-    os << pad_stride_info.stride().first << "," << pad_stride_info.stride().second;
-    os << ";";
-    os << pad_stride_info.pad_left() << "," << pad_stride_info.pad_right() << ","
-       << pad_stride_info.pad_top() << "," << pad_stride_info.pad_bottom();
-
-    return os;
-}
-
-/** Formatted output of the QuantizationInfo type. */
-inline ::std::ostream &operator<<(::std::ostream &os, const QuantizationInfo &quantization_info)
-{
-    os << "Scale:" << quantization_info.scale << "~"
-       << "Offset:" << quantization_info.offset;
-    return os;
-}
-
-/** Formatted output of the Interpolation policy type.
- *
- * @param[out] os     Output stream.
- * @param[in]  policy Interpolation policy to output.
- *
- * @return Modified output stream.
- */
-inline ::std::ostream &operator<<(::std::ostream &os, const InterpolationPolicy &policy)
-{
-    switch(policy)
-    {
-        case InterpolationPolicy::NEAREST_NEIGHBOR:
-            os << "NEAREST NEIGHBOR";
-            break;
-        case InterpolationPolicy::BILINEAR:
-            os << "BILINEAR";
-            break;
-        case InterpolationPolicy::AREA:
-            os << "AREA";
-            break;
-        default:
-            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
-    }
-
-    return os;
-}
 } // namespace graph
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_GRAPH_TYPE_PRINTER_H__ */
diff --git a/arm_compute/graph/algorithms/BFS.h b/arm_compute/graph/algorithms/BFS.h
index 36ca872f15..97292d733b 100644
--- a/arm_compute/graph/algorithms/BFS.h
+++ b/arm_compute/graph/algorithms/BFS.h
@@ -85,7 +85,7 @@ inline std::vector<NodeID> bfs(Graph &g)
     std::list<NodeID> queue;
 
     // Push inputs and mark as visited
-    for(auto &input : g.inputs())
+    for(auto &input : g.nodes(NodeType::Input))
     {
         if(input != EmptyNodeID)
         {
diff --git a/arm_compute/graph/detail/ExecutionHelpers.h b/arm_compute/graph/detail/ExecutionHelpers.h
index 23dd207695..3a357776e4 100644
--- a/arm_compute/graph/detail/ExecutionHelpers.h
+++ b/arm_compute/graph/detail/ExecutionHelpers.h
@@ -95,13 +95,17 @@ void call_all_const_node_accessors(Graph &g);
 /** Call all input node accessors
  *
  * @param[in] workload Workload to execute
+ *
+ * @return  True if all the accesses were valid
  */
-void call_all_input_node_accessors(ExecutionWorkload &workload);
+bool call_all_input_node_accessors(ExecutionWorkload &workload);
 /** Call all output node accessors
  *
  * @param[in] workload Workload to execute
+ *
+ * @return  True if all the accessors expect more data
  */
-void call_all_output_node_accessors(ExecutionWorkload &workload);
+bool call_all_output_node_accessors(ExecutionWorkload &workload);
 /** Prepares all tasks for execution
  *
  * @param[in] workload Workload to prepare
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index c6c0ab2ac5..3b93d85524 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -778,11 +778,11 @@ To cross compile the examples with the Graph API, such as graph_lenet.cpp, you n
 
 i.e. to cross compile the "graph_lenet" example for Linux 32bit:
 
-	arm-linux-gnueabihf-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
+	arm-linux-gnueabihf-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
 
 i.e. to cross compile the "graph_lenet" example for Linux 64bit:
 
-	aarch64-linux-gnu-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
+	aarch64-linux-gnu-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
 
 (notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different)
 
@@ -811,11 +811,11 @@ To compile natively the examples with the Graph API, such as graph_lenet.cpp, yo
 
 i.e. to natively compile the "graph_lenet" example for Linux 32bit:
 
-	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
+	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
 
 i.e. to natively compile the "graph_lenet" example for Linux 64bit:
 
-	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
+	g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet
 
 (notice the only difference with the 32 bit command is that we don't need the -mfpu option)
 
@@ -918,9 +918,9 @@ To cross compile the examples with the Graph API, such as graph_lenet.cpp, you n
 (notice the compute library has to be built with both neon and opencl enabled - neon=1 and opencl=1)
 
 	#32 bit:
-	arm-linux-androideabi-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_arm -static-libstdc++ -pie -DARM_COMPUTE_CL
+	arm-linux-androideabi-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_arm -static-libstdc++ -pie -DARM_COMPUTE_CL
 	#64 bit:
-	aarch64-linux-android-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL
+	aarch64-linux-android-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL
 
 @note Due to some issues in older versions of the Mali OpenCL DDK (<= r13p0), we recommend to link arm_compute statically on Android.
 @note When linked statically the arm_compute_graph library currently needs the --whole-archive linker flag in order to work properly
diff --git a/examples/SConscript b/examples/SConscript
index c3576fb1a0..bada734659 100644
--- a/examples/SConscript
+++ b/examples/SConscript
@@ -47,6 +47,7 @@ else:
 
 # Build graph examples
 graph_utils = examples_env.Object("../utils/GraphUtils.cpp")
+graph_utils += examples_env.Object("../utils/CommonGraphOptions.cpp")
 examples_libs = examples_env.get("LIBS",[])
 for file in Glob("./graph_*.cpp"):
     example = os.path.basename(os.path.splitext(str(file))[0])
diff --git a/examples/cl_convolution.cpp b/examples/cl_convolution.cpp
index 8f3d7e3a30..b15bbb6cb4 100644
--- a/examples/cl_convolution.cpp
+++ b/examples/cl_convolution.cpp
@@ -57,7 +57,7 @@ const int16_t gaussian5x5[] =
 class CLConvolutionExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         PPMLoader ppm;
 
@@ -95,6 +95,8 @@ public:
             ppm.fill_image(src);
             output_filename = std::string(argv[1]) + "_out.ppm";
         }
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/cl_events.cpp b/examples/cl_events.cpp
index 4a46df961c..a9c508ac58 100644
--- a/examples/cl_events.cpp
+++ b/examples/cl_events.cpp
@@ -37,7 +37,7 @@ using namespace utils;
 class CLEventsExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         /** [OpenCL events] **/
         PPMLoader     ppm;
@@ -84,6 +84,8 @@ public:
             output_filename = std::string(argv[1]) + "_out.ppm";
         }
         /** [OpenCL events] **/
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/cl_sgemm.cpp b/examples/cl_sgemm.cpp
index fa57885450..805aec1cf3 100644
--- a/examples/cl_sgemm.cpp
+++ b/examples/cl_sgemm.cpp
@@ -39,7 +39,7 @@ using namespace utils;
 class CLSGEMMExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         NPYLoader npy0, npy1, npy2;
         alpha = 1.0f;
@@ -164,6 +164,8 @@ public:
 
         // Dummy run for CLTuner
         sgemm.run();
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/gc_absdiff.cpp b/examples/gc_absdiff.cpp
index 1024dace26..f53459231f 100644
--- a/examples/gc_absdiff.cpp
+++ b/examples/gc_absdiff.cpp
@@ -38,7 +38,7 @@ using namespace utils;
 class GCAbsDiffExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         PPMLoader ppm1, ppm2;
 
@@ -90,6 +90,8 @@ public:
         {
             ppm2.fill_image(src2);
         }
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/gc_dc.cpp b/examples/gc_dc.cpp
index 8b6f4414e0..f3f194252e 100644
--- a/examples/gc_dc.cpp
+++ b/examples/gc_dc.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017, 2018 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -36,7 +36,7 @@ using namespace utils;
 class GCDCExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         ARM_COMPUTE_UNUSED(argc);
         ARM_COMPUTE_UNUSED(argv);
@@ -86,6 +86,8 @@ public:
             *reinterpret_cast<half_float::half *>(it.ptr()) = half_float::half(1.f);
         });
         src.unmap();
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp
index 5328662b6d..95d36342f9 100644
--- a/examples/graph_alexnet.cpp
+++ b/examples/graph_alexnet.cpp
@@ -23,13 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <iostream>
-#include <memory>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -37,71 +34,47 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement AlexNet's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphAlexnetExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphAlexnetExample()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "AlexNet")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(227U, 227U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(227U, 227U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               // Layer 1
               << ConvolutionLayer(
                   11U, 11U, 96U,
@@ -169,12 +142,15 @@ public:
               .set_name("fc8")
               // Softmax
               << SoftmaxLayer().set_name("prob")
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -183,13 +159,18 @@ public:
     }
 
 private:
-    Stream graph{ 0, "AlexNet" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 };
 
 /** Main program for AlexNet
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
+ *
+ * @return Return code
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_googlenet.cpp b/examples/graph_googlenet.cpp
index 2dba67f5eb..e23107f081 100644
--- a/examples/graph_googlenet.cpp
+++ b/examples/graph_googlenet.cpp
@@ -23,12 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <tuple>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -36,71 +34,47 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement Googlenet's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphGooglenetExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphGooglenetExample()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "GoogleNet")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               << ConvolutionLayer(
                   7U, 7U, 64U,
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv1/conv1_7x7_s2_w.npy"),
@@ -140,12 +114,15 @@ public:
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/loss3/loss3_classifier_w.npy"),
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/loss3/loss3_classifier_b.npy"))
               << SoftmaxLayer()
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -154,7 +131,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "GoogleNet" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
     BranchLayer get_inception_node(const std::string &data_path, std::string &&param_path,
                                    unsigned int a_filt,
@@ -215,7 +195,7 @@ private:
 /** Main program for Googlenet
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp
index d1d6ab4e05..30b1b7d7ce 100644
--- a/examples/graph_inception_v3.cpp
+++ b/examples/graph_inception_v3.cpp
@@ -23,12 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <tuple>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -36,70 +34,46 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement InceptionV3's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class InceptionV3Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    InceptionV3Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "InceptionV3")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(299U, 299U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor), false))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(299U, 299U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor), false))
               << ConvolutionLayer(3U, 3U, 32U,
                                   get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_weights.npy"),
                                   std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(2, 2, 0, 0))
@@ -218,12 +192,15 @@ public:
               .set_name("Logits/Conv2d_1c_1x1/convolution")
               << ReshapeLayer(TensorShape(1001U)).set_name("Predictions/Reshape")
               << SoftmaxLayer().set_name("Predictions/Softmax")
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
 
     void do_run() override
@@ -232,7 +209,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "InceptionV3" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
 private:
     BranchLayer get_inception_node_A(const std::string &data_path, std::string &&param_path,
@@ -863,7 +843,7 @@ private:
 /** Main program for Inception V3
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_inception_v4.cpp b/examples/graph_inception_v4.cpp
index ed95baa99e..e7c1bc69e2 100644
--- a/examples/graph_inception_v4.cpp
+++ b/examples/graph_inception_v4.cpp
@@ -23,12 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <tuple>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -36,73 +34,46 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement InceptionV4's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class InceptionV4Example final : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    InceptionV4Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "InceptionV4")
     {
-        // Disabled the test for now because the process gets killed on Linux Firefly 32 bit even when using ConvolutionMethodHint::DIRECT.
-        // Needs to review/rework to run the code below.
-#if __aarch64__
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(299U, 299U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor), false))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(299U, 299U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor), false))
               // Conv2d_1a_3x3
               << ConvolutionLayer(3U, 3U, 32U,
                                   get_weights_accessor(data_path, "/cnn_data/inceptionv4_model/Conv2d_1a_3x3_weights.npy"),
@@ -165,28 +136,27 @@ public:
                   get_weights_accessor(data_path, "/cnn_data/inceptionv4_model/Logits_Logits_weights.npy"),
                   get_weights_accessor(data_path, "/cnn_data/inceptionv4_model/Logits_Logits_biases.npy"))
               << SoftmaxLayer()
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
-#else  /* __aarch64__ */
-        using namespace arm_compute;
-        ARM_COMPUTE_UNUSED(argc);
-        ARM_COMPUTE_UNUSED(argv);
-#endif /* __aarch64__ */
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
 
     void do_run() override
     {
-#if __aarch64__
         graph.run();
-#endif /* __aarch64__ */
     }
 
 private:
-    Stream graph{ 0, "InceptionV4" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
 private:
     BranchLayer get_mixed_3a(const std::string &data_path)
@@ -747,7 +717,7 @@ private:
 /** Main program for Inception V4
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_lenet.cpp b/examples/graph_lenet.cpp
index 32c75827d3..f90892aeee 100644
--- a/examples/graph_lenet.cpp
+++ b/examples/graph_lenet.cpp
@@ -22,13 +22,11 @@
  * SOFTWARE.
  */
 #include "arm_compute/graph.h"
-
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -41,55 +39,39 @@ using namespace arm_compute::graph_utils;
 class GraphLenetExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphLenetExample()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "LeNet")
     {
-        std::string  data_path;   /** Path to the trainable data */
-        unsigned int batches = 4; /** Number of batches */
-
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [batches] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [batches] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            //Do something with argv[1]
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " [path_to_data] [batches] [fast_math_hint]\n\n";
-            std::cout << "No number of batches where specified, thus will use the default : " << batches << "\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            batches   = std::strtol(argv[3], nullptr, 0);
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            //Do something with argv[1] and argv[2]
-            data_path      = argv[2];
-            batches        = std::strtol(argv[3], nullptr, 0);
-            fast_math_hint = (std::strtol(argv[4], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string  data_path = common_params.data_path;
+        unsigned int batches   = 4; /** Number of batches */
+
         //conv1 << pool1 << conv2 << pool2 << fc1 << act1 << fc2 << smx
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(28U, 28U, 1U, batches), DataType::F32), get_input_accessor(""))
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(28U, 28U, 1U, batches), common_params.data_type), get_input_accessor(common_params))
               << ConvolutionLayer(
                   5U, 5U, 20U,
                   get_weights_accessor(data_path, "/cnn_data/lenet_model/conv1_w.npy"),
@@ -116,12 +98,15 @@ public:
                   get_weights_accessor(data_path, "/cnn_data/lenet_model/ip2_b.npy"))
               .set_name("ip2")
               << SoftmaxLayer().set_name("prob")
-              << OutputLayer(get_output_accessor(""));
+              << OutputLayer(get_output_accessor(common_params));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -130,7 +115,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "LeNet" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 };
 
 /** Main program for LeNet
diff --git a/examples/graph_mobilenet.cpp b/examples/graph_mobilenet.cpp
index 40243bb111..9304b2b380 100644
--- a/examples/graph_mobilenet.cpp
+++ b/examples/graph_mobilenet.cpp
@@ -23,11 +23,11 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
+using namespace arm_compute;
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -35,107 +35,112 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement MobileNet's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Model ID (0 = MobileNetV1_1.0_224, 1 = MobileNetV1_0.75_160), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] data layout, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
-class GraphMobilenetExample : public Example
+class GraphMobilenetExample : public Example // NOLINT
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphMobilenetExample()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "MobileNetV1")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+        // Add model id option
+        model_id_opt = cmd_parser.add_option<SimpleOption<int>>("model-id", 0);
+        model_id_opt->set_help("Mobilenet model id (0: 1.0_224, else: 0.75_160");
+    }
+    /** Prevent instances of this class from being copy constructed */
+    GraphMobilenetExample(const GraphMobilenetExample &) = delete;
+    /** Prevent instances of this class from being copied */
+    GraphMobilenetExample &operator=(const GraphMobilenetExample &) = delete;
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int                  target                     = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target                     target_hint                = set_target_hint(target);
-        DepthwiseConvolutionMethod depthwise_convolution_hint = DepthwiseConvolutionMethod::OPTIMIZED_3x3;
-        FastMathHint               fast_math_hint             = FastMathHint::DISABLED;
-
-        // Set model to execute. 0 (MobileNetV1_1.0_224), 1 (MobileNetV1_0.75_160)
-        int model_id = (argc > 2) ? std::strtol(argv[2], nullptr, 10) : 0;
-        ARM_COMPUTE_ERROR_ON_MSG(model_id > 1, "Invalid model ID. Model must be 0 (MobileNetV1_1.0_224) or 1 (MobileNetV1_0.75_160)");
-        int layout_id = (argc > 3) ? std::strtol(argv[3], nullptr, 10) : 0;
-        ARM_COMPUTE_ERROR_ON_MSG(layout_id > 1, "Invalid layout ID. Layout must be 0 (NCHW) or 1 (NHWC)");
-
-        float            depth_scale           = (model_id == 0) ? 1.f : 0.75;
-        unsigned int     spatial_size          = (model_id == 0) ? 224 : 160;
-        std::string      model_path            = (model_id == 0) ? "/cnn_data/mobilenet_v1_1_224_model/" : "/cnn_data/mobilenet_v1_075_160_model/";
-        TensorDescriptor input_descriptor_nchw = TensorDescriptor(TensorShape(spatial_size, spatial_size, 3U, 1U), DataType::F32);
-        TensorDescriptor input_descriptor_nhwc = TensorDescriptor(TensorShape(3U, spatial_size, spatial_size, 1U), DataType::F32).set_layout(DataLayout::NHWC);
-        TensorDescriptor input_descriptor      = (layout_id == 0) ? input_descriptor_nchw : input_descriptor_nhwc;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [model] [layout] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No model ID provided: using MobileNetV1_1.0_224\n\n";
-            std::cout << "No data layout provided: using NCHW\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [model] [layout] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No model ID provided: using MobileNetV1_1.0_224\n\n";
-            std::cout << "No data layout provided: using NCHW\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
-        else if(argc == 3)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [layout] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data layout provided: using NCHW\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 6)
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get model parameters
+        int model_id = model_id_opt->value();
+
+        // Create input descriptor
+        unsigned int spatial_size = (model_id == 0 || common_params.data_type == DataType::QASYMM8) ? 224 : 160;
+        TensorShape  tensor_shape = TensorShape(spatial_size, spatial_size, 3U, 1U);
+        if(common_params.data_layout == DataLayout::NHWC)
         {
-            data_path = argv[4];
-            image     = argv[5];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
+            arm_compute::permute(tensor_shape, arm_compute::PermutationVector(2U, 0U, 1U));
         }
-        else if(argc == 7)
+        TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
+
+        // Set graph hints
+        graph << common_params.target
+              << DepthwiseConvolutionMethod::OPTIMIZED_3x3 // FIXME(COMPMID-1073): Add heuristics to automatically call the optimized 3x3 method
+              << common_params.fast_math_hint;
+
+        // Create core graph
+        if(arm_compute::is_data_type_float(common_params.data_type))
         {
-            data_path = argv[4];
-            image     = argv[5];
-            label     = argv[6];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
+            create_graph_float(input_descriptor, model_id);
         }
         else
         {
-            data_path      = argv[4];
-            image          = argv[5];
-            label          = argv[6];
-            fast_math_hint = (std::strtol(argv[7], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            create_graph_qasymm(input_descriptor);
         }
 
+        // Create common tail
+        graph << ReshapeLayer(TensorShape(1001U)).set_name("Reshape")
+              << SoftmaxLayer().set_name("Softmax")
+              << OutputLayer(get_output_accessor(common_params, 5));
+
+        // Finalize graph
+        GraphConfig config;
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
+    }
+    void do_run() override
+    {
+        // Run graph
+        graph.run();
+    }
+
+private:
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    SimpleOption<int> *model_id_opt{ nullptr };
+    CommonGraphParams  common_params;
+    Stream             graph;
+
+    void create_graph_float(TensorDescriptor &input_descriptor, int model_id)
+    {
+        float       depth_scale = (model_id == 0) ? 1.f : 0.75;
+        std::string model_path  = (model_id == 0) ? "/cnn_data/mobilenet_v1_1_224_model/" : "/cnn_data/mobilenet_v1_075_160_model/";
+
+        // Create a preprocessor object
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
         // Add model path to data path
         if(!data_path.empty())
         {
             data_path += model_path;
         }
 
-        graph << target_hint
-              << depthwise_convolution_hint
-              << fast_math_hint
-              << InputLayer(input_descriptor,
-                            get_input_accessor(image, std::move(preprocessor), false))
+        graph << InputLayer(input_descriptor,
+                            get_input_accessor(common_params, std::move(preprocessor), false))
               << ConvolutionLayer(
                   3U, 3U, 32U * depth_scale,
                   get_weights_accessor(data_path, "Conv2d_0_weights.npy", DataLayout::NCHW),
@@ -150,47 +155,122 @@ public:
                   0.001f)
               .set_name("Conv2d_0/BatchNorm")
               << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f)).set_name("Conv2d_0/Relu6");
-        graph << get_dwsc_node(data_path, "Conv2d_1", 64 * depth_scale, PadStrideInfo(1, 1, 1, 1), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_2", 128 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_3", 128 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_4", 256 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_5", 256 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_6", 512 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_7", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_8", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_9", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_10", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_11", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_12", 1024 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
-        graph << get_dwsc_node(data_path, "Conv2d_13", 1024 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_1", 64 * depth_scale, PadStrideInfo(1, 1, 1, 1), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_2", 128 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_3", 128 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_4", 256 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_5", 256 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_6", 512 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_7", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_8", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_9", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_10", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_11", 512 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_12", 1024 * depth_scale, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
+        graph << get_dwsc_node_float(data_path, "Conv2d_13", 1024 * depth_scale, PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::CEIL), PadStrideInfo(1, 1, 0, 0));
         graph << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)).set_name("Logits/AvgPool_1a")
               << ConvolutionLayer(
                   1U, 1U, 1001U,
                   get_weights_accessor(data_path, "Logits_Conv2d_1c_1x1_weights.npy", DataLayout::NCHW),
                   get_weights_accessor(data_path, "Logits_Conv2d_1c_1x1_biases.npy"),
                   PadStrideInfo(1, 1, 0, 0))
-              .set_name("Logits/Conv2d_1c_1x1")
-              << ReshapeLayer(TensorShape(1001U)).set_name("Reshape")
-              << SoftmaxLayer().set_name("Softmax")
-              << OutputLayer(get_output_accessor(label, 5));
-
-        // Finalize graph
-        GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+              .set_name("Logits/Conv2d_1c_1x1");
     }
-    void do_run() override
+
+    void create_graph_qasymm(TensorDescriptor &input_descriptor)
     {
-        // Run graph
-        graph.run();
-    }
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
 
-private:
-    Stream graph{ 0, "MobileNetV1" };
+        // Quantization info taken from the AndroidNN QASYMM8 MobileNet example
+        const QuantizationInfo in_quant_info  = QuantizationInfo(0.0078125f, 128);
+        const QuantizationInfo mid_quant_info = QuantizationInfo(0.0784313753247f, 128);
+
+        const std::vector<QuantizationInfo> conv_weights_quant_info =
+        {
+            QuantizationInfo(0.031778190285f, 156), // conv0
+            QuantizationInfo(0.00604454148561f, 66) // conv14
+        };
+
+        const std::vector<QuantizationInfo> depth_weights_quant_info =
+        {
+            QuantizationInfo(0.254282623529f, 129),  // dwsc1
+            QuantizationInfo(0.12828284502f, 172),   // dwsc2
+            QuantizationInfo(0.265911251307f, 83),   // dwsc3
+            QuantizationInfo(0.0985597148538f, 30),  // dwsc4
+            QuantizationInfo(0.0631204470992f, 54),  // dwsc5
+            QuantizationInfo(0.0137207424268f, 141), // dwsc6
+            QuantizationInfo(0.0817828401923f, 125), // dwsc7
+            QuantizationInfo(0.0393880493939f, 164), // dwsc8
+            QuantizationInfo(0.211694166064f, 129),  // dwsc9
+            QuantizationInfo(0.158015936613f, 103),  // dwsc10
+            QuantizationInfo(0.0182712618262f, 137), // dwsc11
+            QuantizationInfo(0.0127998134121f, 134), // dwsc12
+            QuantizationInfo(0.299285322428f, 161)   // dwsc13
+        };
 
-    BranchLayer get_dwsc_node(const std::string &data_path, std::string &&param_path,
-                              unsigned int  conv_filt,
-                              PadStrideInfo dwc_pad_stride_info, PadStrideInfo conv_pad_stride_info)
+        const std::vector<QuantizationInfo> point_weights_quant_info =
+        {
+            QuantizationInfo(0.0425766184926f, 129),  // dwsc1
+            QuantizationInfo(0.0250773020089f, 94),   // dwsc2
+            QuantizationInfo(0.015851572156f, 93),    // dwsc3
+            QuantizationInfo(0.0167811904103f, 98),   // dwsc4
+            QuantizationInfo(0.00951790809631f, 135), // dwsc5
+            QuantizationInfo(0.00999817531556f, 128), // dwsc6
+            QuantizationInfo(0.00590536883101f, 126), // dwsc7
+            QuantizationInfo(0.00576109671965f, 133), // dwsc8
+            QuantizationInfo(0.00830461271107f, 142), // dwsc9
+            QuantizationInfo(0.0152327232063f, 72),   // dwsc10
+            QuantizationInfo(0.00741417845711f, 125), // dwsc11
+            QuantizationInfo(0.0135628981516f, 142),  // dwsc12
+            QuantizationInfo(0.0338749065995f, 140)   // dwsc13
+        };
+
+        graph << InputLayer(input_descriptor.set_quantization_info(in_quant_info),
+                            get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/" + common_params.image))
+              << ConvolutionLayer(
+                  3U, 3U, 32U,
+                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_weights.npy"),
+                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_bias.npy"),
+                  PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR),
+                  1, conv_weights_quant_info.at(0), mid_quant_info)
+              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_1", 64U, PadStrideInfo(1U, 1U, 1U, 1U), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(0), point_weights_quant_info.at(0));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_2", 128U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(1),
+                                      point_weights_quant_info.at(1));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_3", 128U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(2),
+                                      point_weights_quant_info.at(2));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_4", 256U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(3),
+                                      point_weights_quant_info.at(3));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_5", 256U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(4),
+                                      point_weights_quant_info.at(4));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_6", 512U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(5),
+                                      point_weights_quant_info.at(5));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_7", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(6),
+                                      point_weights_quant_info.at(6));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_8", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(7),
+                                      point_weights_quant_info.at(7));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_9", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(8),
+                                      point_weights_quant_info.at(8));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_10", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(9),
+                                      point_weights_quant_info.at(9));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_11", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(10),
+                                      point_weights_quant_info.at(10));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_12", 1024U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(11),
+                                      point_weights_quant_info.at(11));
+        graph << get_dwsc_node_qasymm(data_path, "Conv2d_13", 1024U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(12),
+                                      point_weights_quant_info.at(12))
+              << PoolingLayer(PoolingLayerInfo(PoolingType::AVG))
+              << ConvolutionLayer(
+                  1U, 1U, 1001U,
+                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_weights.npy"),
+                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_bias.npy"),
+                  PadStrideInfo(1U, 1U, 0U, 0U), 1, conv_weights_quant_info.at(1));
+    }
+
+    BranchLayer get_dwsc_node_float(const std::string &data_path, std::string &&param_path,
+                                    unsigned int  conv_filt,
+                                    PadStrideInfo dwc_pad_stride_info, PadStrideInfo conv_pad_stride_info)
     {
         std::string total_path = param_path + "_";
         SubStream   sg(graph);
@@ -225,18 +305,36 @@ private:
 
         return BranchLayer(std::move(sg));
     }
+
+    BranchLayer get_dwsc_node_qasymm(const std::string &data_path, std::string &&param_path,
+                                     const unsigned int conv_filt,
+                                     PadStrideInfo dwc_pad_stride_info, PadStrideInfo conv_pad_stride_info,
+                                     QuantizationInfo depth_weights_quant_info, QuantizationInfo point_weights_quant_info)
+    {
+        std::string total_path = "/cnn_data/mobilenet_qasymm8_model/" + param_path + "_";
+        SubStream   sg(graph);
+
+        sg << DepthwiseConvolutionLayer(
+               3U, 3U,
+               get_weights_accessor(data_path, total_path + "depthwise_weights.npy"),
+               get_weights_accessor(data_path, total_path + "depthwise_bias.npy"),
+               dwc_pad_stride_info, depth_weights_quant_info)
+           << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f))
+           << ConvolutionLayer(
+               1U, 1U, conv_filt,
+               get_weights_accessor(data_path, total_path + "pointwise_weights.npy"),
+               get_weights_accessor(data_path, total_path + "pointwise_bias.npy"),
+               conv_pad_stride_info, 1, point_weights_quant_info)
+           << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f));
+
+        return BranchLayer(std::move(sg));
+    }
 };
 
 /** Main program for MobileNetV1
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner),
- *                             [optional] Model ID (0 = MobileNetV1_1.0_224, 1 = MobileNetV1_0.75_160),
- *                             [optional] Path to the weights folder,
- *                             [optional] image,
- *                             [optional] labels,
- *                             [optional] data layout,
- *                             [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_mobilenet_qasymm8.cpp b/examples/graph_mobilenet_qasymm8.cpp
deleted file mode 100644
index 2801209985..0000000000
--- a/examples/graph_mobilenet_qasymm8.cpp
+++ /dev/null
@@ -1,239 +0,0 @@
-/*
- * Copyright (c) 2017-2018 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/graph.h"
-#include "support/ToolchainSupport.h"
-#include "utils/GraphUtils.h"
-#include "utils/Utils.h"
-
-#include <cstdlib>
-
-using namespace arm_compute;
-using namespace arm_compute::utils;
-using namespace arm_compute::graph::frontend;
-using namespace arm_compute::graph_utils;
-
-/** Example demonstrating how to implement QASYMM8 MobileNet's network using the Compute Library's graph API
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] npy_input, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
- */
-class GraphMobileNetQASYMM8Example : public Example
-{
-public:
-    void do_setup(int argc, char **argv) override
-    {
-        std::string data_path; /* Path to the trainable data */
-        std::string input;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Quantization info taken from the AndroidNN QASYMM8 MobileNet example
-        const QuantizationInfo in_quant_info  = QuantizationInfo(0.0078125f, 128);
-        const QuantizationInfo mid_quant_info = QuantizationInfo(0.0784313753247f, 128);
-
-        const std::vector<QuantizationInfo> conv_weights_quant_info =
-        {
-            QuantizationInfo(0.031778190285f, 156), // conv0
-            QuantizationInfo(0.00604454148561f, 66) // conv14
-        };
-
-        const std::vector<QuantizationInfo> depth_weights_quant_info =
-        {
-            QuantizationInfo(0.254282623529f, 129),  // dwsc1
-            QuantizationInfo(0.12828284502f, 172),   // dwsc2
-            QuantizationInfo(0.265911251307f, 83),   // dwsc3
-            QuantizationInfo(0.0985597148538f, 30),  // dwsc4
-            QuantizationInfo(0.0631204470992f, 54),  // dwsc5
-            QuantizationInfo(0.0137207424268f, 141), // dwsc6
-            QuantizationInfo(0.0817828401923f, 125), // dwsc7
-            QuantizationInfo(0.0393880493939f, 164), // dwsc8
-            QuantizationInfo(0.211694166064f, 129),  // dwsc9
-            QuantizationInfo(0.158015936613f, 103),  // dwsc10
-            QuantizationInfo(0.0182712618262f, 137), // dwsc11
-            QuantizationInfo(0.0127998134121f, 134), // dwsc12
-            QuantizationInfo(0.299285322428f, 161)   // dwsc13
-        };
-
-        const std::vector<QuantizationInfo> point_weights_quant_info =
-        {
-            QuantizationInfo(0.0425766184926f, 129),  // dwsc1
-            QuantizationInfo(0.0250773020089f, 94),   // dwsc2
-            QuantizationInfo(0.015851572156f, 93),    // dwsc3
-            QuantizationInfo(0.0167811904103f, 98),   // dwsc4
-            QuantizationInfo(0.00951790809631f, 135), // dwsc5
-            QuantizationInfo(0.00999817531556f, 128), // dwsc6
-            QuantizationInfo(0.00590536883101f, 126), // dwsc7
-            QuantizationInfo(0.00576109671965f, 133), // dwsc8
-            QuantizationInfo(0.00830461271107f, 142), // dwsc9
-            QuantizationInfo(0.0152327232063f, 72),   // dwsc10
-            QuantizationInfo(0.00741417845711f, 125), // dwsc11
-            QuantizationInfo(0.0135628981516f, 142),  // dwsc12
-            QuantizationInfo(0.0338749065995f, 140)   // dwsc13
-        };
-
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
-
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [npy_input] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [npy_input] [labels] [fast_math_hint]\n\n";
-            std::cout << "No input provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            input     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            input     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            input          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
-        }
-
-        graph << target_hint
-              << DepthwiseConvolutionMethod::OPTIMIZED_3x3 // FIXME(COMPMID-1073): Add heuristics to automatically call the optimized 3x3 method
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::QASYMM8, in_quant_info),
-                            get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/" + input))
-              << ConvolutionLayer(
-                  3U, 3U, 32U,
-                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_weights.npy"),
-                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Conv2d_0_bias.npy"),
-                  PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR),
-                  1, conv_weights_quant_info.at(0), mid_quant_info)
-              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f));
-        graph << get_dwsc_node(data_path, "Conv2d_1", 64U, PadStrideInfo(1U, 1U, 1U, 1U), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(0), point_weights_quant_info.at(0));
-        graph << get_dwsc_node(data_path, "Conv2d_2", 128U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(1),
-                               point_weights_quant_info.at(1));
-        graph << get_dwsc_node(data_path, "Conv2d_3", 128U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(2),
-                               point_weights_quant_info.at(2));
-        graph << get_dwsc_node(data_path, "Conv2d_4", 256U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(3),
-                               point_weights_quant_info.at(3));
-        graph << get_dwsc_node(data_path, "Conv2d_5", 256U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(4),
-                               point_weights_quant_info.at(4));
-        graph << get_dwsc_node(data_path, "Conv2d_6", 512U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(5),
-                               point_weights_quant_info.at(5));
-        graph << get_dwsc_node(data_path, "Conv2d_7", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(6),
-                               point_weights_quant_info.at(6));
-        graph << get_dwsc_node(data_path, "Conv2d_8", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(7),
-                               point_weights_quant_info.at(7));
-        graph << get_dwsc_node(data_path, "Conv2d_9", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(8),
-                               point_weights_quant_info.at(8));
-        graph << get_dwsc_node(data_path, "Conv2d_10", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(9),
-                               point_weights_quant_info.at(9));
-        graph << get_dwsc_node(data_path, "Conv2d_11", 512U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(10),
-                               point_weights_quant_info.at(10));
-        graph << get_dwsc_node(data_path, "Conv2d_12", 1024U, PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(11),
-                               point_weights_quant_info.at(11));
-        graph << get_dwsc_node(data_path, "Conv2d_13", 1024U, PadStrideInfo(1U, 1U, 1U, 1U, 1U, 1U, DimensionRoundingType::FLOOR), PadStrideInfo(1U, 1U, 0U, 0U), depth_weights_quant_info.at(12),
-                               point_weights_quant_info.at(12))
-              << PoolingLayer(PoolingLayerInfo(PoolingType::AVG))
-              << ConvolutionLayer(
-                  1U, 1U, 1001U,
-                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_weights.npy"),
-                  get_weights_accessor(data_path, "/cnn_data/mobilenet_qasymm8_model/Logits_Conv2d_1c_1x1_bias.npy"),
-                  PadStrideInfo(1U, 1U, 0U, 0U), 1, conv_weights_quant_info.at(1))
-              << ReshapeLayer(TensorShape(1001U))
-              << SoftmaxLayer()
-              << OutputLayer(get_output_accessor(label, 5));
-
-        // Finalize graph
-        GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
-    }
-    void do_run() override
-    {
-        // Run graph
-        graph.run();
-    }
-
-private:
-    Stream graph{ 0, "MobileNetV1_QASYMM8" };
-
-    /** This function produces a depthwise separable convolution node (i.e. depthwise + pointwise layers) with ReLU6 activation after each layer.
-     *
-     * @param[in] data_path                Path to trainable data folder
-     * @param[in] param_path               Prefix of specific set of weights/biases data
-     * @param[in] conv_filt                Filters depths for pointwise convolution
-     * @param[in] dwc_pad_stride_info      PadStrideInfo for depthwise convolution
-     * @param[in] conv_pad_stride_info     PadStrideInfo for pointwise convolution
-     * @param[in] depth_weights_quant_info QuantizationInfo for depthwise convolution's weights
-     * @param[in] point_weights_quant_info QuantizationInfo for pointwise convolution's weights
-     *
-     * @return The complete dwsc node
-     */
-    BranchLayer get_dwsc_node(const std::string &data_path, std::string &&param_path,
-                              const unsigned int conv_filt,
-                              PadStrideInfo dwc_pad_stride_info, PadStrideInfo conv_pad_stride_info,
-                              QuantizationInfo depth_weights_quant_info, QuantizationInfo point_weights_quant_info)
-    {
-        std::string total_path = "/cnn_data/mobilenet_qasymm8_model/" + param_path + "_";
-        SubStream   sg(graph);
-
-        sg << DepthwiseConvolutionLayer(
-               3U, 3U,
-               get_weights_accessor(data_path, total_path + "depthwise_weights.npy"),
-               get_weights_accessor(data_path, total_path + "depthwise_bias.npy"),
-               dwc_pad_stride_info, depth_weights_quant_info)
-           << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f))
-           << ConvolutionLayer(
-               1U, 1U, conv_filt,
-               get_weights_accessor(data_path, total_path + "pointwise_weights.npy"),
-               get_weights_accessor(data_path, total_path + "pointwise_bias.npy"),
-               conv_pad_stride_info, 1, point_weights_quant_info)
-           << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f));
-
-        return BranchLayer(std::move(sg));
-    }
-};
-/** Main program for MobileNetQASYMM8
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Path to the weights folder, [optional] npy_input, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
- */
-int main(int argc, char **argv)
-{
-    return arm_compute::utils::run_example<GraphMobileNetQASYMM8Example>(argc, argv);
-}
diff --git a/examples/graph_resnet50.cpp b/examples/graph_resnet50.cpp
index bafa9a5852..66fc6e869d 100644
--- a/examples/graph_resnet50.cpp
+++ b/examples/graph_resnet50.cpp
@@ -23,11 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -35,72 +34,47 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement ResNet50 network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphResNet50Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphResNet50Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "ResNet50")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb,
-                                                                                                                   false /* Do not convert to BGR */);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor), false /* Do not convert to BGR */))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb,
+                                                                                                                   false /* Do not convert to BGR */);
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor), false /* Do not convert to BGR */))
               << ConvolutionLayer(
                   7U, 7U, 64U,
                   get_weights_accessor(data_path, "/cnn_data/resnet50_model/conv1_weights.npy"),
@@ -131,12 +105,15 @@ public:
               .set_name("logits/convolution")
               << FlattenLayer().set_name("predictions/Reshape")
               << SoftmaxLayer().set_name("predictions/Softmax")
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
 
     void do_run() override
@@ -146,7 +123,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "ResNet50" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
     void add_residual_block(const std::string &data_path, const std::string &name, unsigned int base_depth, unsigned int num_units, unsigned int stride)
     {
@@ -252,7 +232,7 @@ private:
 /** Main program for ResNet50
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_resnext50.cpp b/examples/graph_resnext50.cpp
index f96a02e6d6..c0a2308a1f 100644
--- a/examples/graph_resnext50.cpp
+++ b/examples/graph_resnext50.cpp
@@ -23,11 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -35,67 +34,43 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement ResNeXt50 network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] npy_in, [optional] npy_out, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphResNeXt50Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphResNeXt50Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "ResNeXt50")
+    {
+    }
+    bool do_setup(int argc, char **argv) override
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string npy_in;    /* Input npy data */
-        std::string npy_out;   /* Output npy data */
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [npy_in] [npy_out] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [npy_in] [npy_out] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [npy_in] [npy_out] [fast_math_hint]\n\n";
-            std::cout << "No input npy file provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            npy_in    = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [npy_out] [fast_math_hint]\n\n";
-            std::cout << "No output npy file provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            npy_in    = argv[3];
-            npy_out   = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            npy_in         = argv[3];
-            npy_out        = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(npy_in))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params))
               << ScaleLayer(get_weights_accessor(data_path, "/cnn_data/resnext50_model/bn_data_mul.npy"),
                             get_weights_accessor(data_path, "/cnn_data/resnext50_model/bn_data_add.npy"))
               .set_name("bn_data/Scale")
@@ -115,12 +90,15 @@ public:
 
         graph << PoolingLayer(PoolingLayerInfo(PoolingType::AVG)).set_name("pool1")
               << FlattenLayer().set_name("predictions/Reshape")
-              << OutputLayer(get_npy_output_accessor(npy_out, TensorShape(2048U), DataType::F32));
+              << OutputLayer(get_npy_output_accessor(common_params.labels, TensorShape(2048U), DataType::F32));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
 
     void do_run() override
@@ -130,7 +108,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "ResNeXt50" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
     void add_residual_block(const std::string &data_path, unsigned int base_depth, unsigned int stage, unsigned int num_units, unsigned int stride_conv_unit1)
     {
@@ -200,7 +181,7 @@ private:
 /** Main program for ResNeXt50
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [[optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] npy_in, [optional] npy_out )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_squeezenet.cpp b/examples/graph_squeezenet.cpp
index b632688839..a290b91148 100644
--- a/examples/graph_squeezenet.cpp
+++ b/examples/graph_squeezenet.cpp
@@ -23,85 +23,58 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <tuple>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
-using namespace arm_compute::logging;
 
 /** Example demonstrating how to implement Squeezenet's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphSqueezenetExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphSqueezenetExample()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "SqueezeNetV1")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               << ConvolutionLayer(
                   7U, 7U, 96U,
                   get_weights_accessor(data_path, "/cnn_data/squeezenet_v1.0_model/conv1_w.npy"),
@@ -176,12 +149,15 @@ public:
               << PoolingLayer(PoolingLayerInfo(PoolingType::AVG))
               << FlattenLayer()
               << SoftmaxLayer()
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -190,7 +166,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "SqueezeNetV1" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
     BranchLayer get_expand_fire_node(const std::string &data_path, std::string &&param_path, unsigned int expand1_filt, unsigned int expand3_filt)
     {
@@ -218,7 +197,7 @@ private:
 /** Main program for Squeezenet v1.0
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_squeezenet_v1_1.cpp b/examples/graph_squeezenet_v1_1.cpp
index b2c5a442cd..8ce928c5b1 100644
--- a/examples/graph_squeezenet_v1_1.cpp
+++ b/examples/graph_squeezenet_v1_1.cpp
@@ -23,12 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-#include <tuple>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -36,71 +34,47 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement Squeezenet's v1.1 network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphSqueezenet_v1_1Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphSqueezenet_v1_1Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "SqueezeNetV1.1")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(227U, 227U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(227U, 227U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               << ConvolutionMethod::DIRECT
               << ConvolutionLayer(
                   3U, 3U, 64U,
@@ -177,12 +151,15 @@ public:
               << PoolingLayer(PoolingLayerInfo(PoolingType::AVG))
               << FlattenLayer()
               << SoftmaxLayer()
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -191,7 +168,10 @@ public:
     }
 
 private:
-    Stream graph{ 0, "SqueezeNetV1.1" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 
     BranchLayer get_expand_fire_node(const std::string &data_path, std::string &&param_path, unsigned int expand1_filt, unsigned int expand3_filt)
     {
@@ -219,7 +199,7 @@ private:
 /** Main program for Squeezenet v1.1
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_vgg16.cpp b/examples/graph_vgg16.cpp
index d70c56eadd..5ff306507f 100644
--- a/examples/graph_vgg16.cpp
+++ b/examples/graph_vgg16.cpp
@@ -23,11 +23,10 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
@@ -35,71 +34,47 @@ using namespace arm_compute::graph_utils;
 /** Example demonstrating how to implement VGG16's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphVGG16Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphVGG16Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "VGG16")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
-        {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               // Layer 1
               << ConvolutionLayer(
                   3U, 3U, 64U,
@@ -231,12 +206,15 @@ public:
               .set_name("fc8")
               // Softmax
               << SoftmaxLayer().set_name("prob")
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -245,13 +223,16 @@ public:
     }
 
 private:
-    Stream graph{ 0, "VGG16" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 };
 
 /** Main program for VGG16
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/graph_vgg19.cpp b/examples/graph_vgg19.cpp
index 8a0ec6fdbd..8bf88b96ed 100644
--- a/examples/graph_vgg19.cpp
+++ b/examples/graph_vgg19.cpp
@@ -23,83 +23,57 @@
  */
 #include "arm_compute/graph.h"
 #include "support/ToolchainSupport.h"
+#include "utils/CommonGraphOptions.h"
 #include "utils/GraphUtils.h"
 #include "utils/Utils.h"
 
-#include <cstdlib>
-
 using namespace arm_compute::utils;
 using namespace arm_compute::graph::frontend;
 using namespace arm_compute::graph_utils;
-
 /** Example demonstrating how to implement VGG19's network using the Compute Library's graph API
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 class GraphVGG19Example : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    GraphVGG19Example()
+        : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "VGG19")
     {
-        std::string data_path; /* Path to the trainable data */
-        std::string image;     /* Image data */
-        std::string label;     /* Label data */
-
-        // Create a preprocessor object
-        const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } };
-        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+    }
+    bool do_setup(int argc, char **argv) override
+    {
+        // Parse arguments
+        cmd_parser.parse(argc, argv);
 
-        // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int    target         = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target       target_hint    = set_target_hint(target);
-        FastMathHint fast_math_hint = FastMathHint::DISABLED;
+        // Consume common parameters
+        common_params = consume_common_graph_parameters(common_opts);
 
-        // Parse arguments
-        if(argc < 2)
-        {
-            // Print help
-            std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 2)
-        {
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No data folder provided: using random values\n\n";
-        }
-        else if(argc == 3)
+        // Return when help menu is requested
+        if(common_params.help)
         {
-            data_path = argv[2];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels] [fast_math_hint]\n\n";
-            std::cout << "No image provided: using random values\n\n";
-        }
-        else if(argc == 4)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels] [fast_math_hint]\n\n";
-            std::cout << "No text file with labels provided: skipping output accessor\n\n";
-        }
-        else if(argc == 5)
-        {
-            data_path = argv[2];
-            image     = argv[3];
-            label     = argv[4];
-            std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " " << argv[4] << " [fast_math_hint]\n\n";
-            std::cout << "No fast math info provided: disabling fast math\n\n";
-        }
-        else
-        {
-            data_path      = argv[2];
-            image          = argv[3];
-            label          = argv[4];
-            fast_math_hint = (std::strtol(argv[5], nullptr, 1) == 0) ? FastMathHint::DISABLED : FastMathHint::ENABLED;
+            cmd_parser.print_help(argv[0]);
+            return false;
         }
 
-        graph << target_hint
-              << fast_math_hint
-              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32),
-                            get_input_accessor(image, std::move(preprocessor)))
+        // Checks
+        ARM_COMPUTE_ERROR_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!");
+
+        // Print parameter values
+        std::cout << common_params << std::endl;
+
+        // Get trainable parameters data path
+        std::string data_path = common_params.data_path;
+
+        // Create a preprocessor object
+        const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } };
+        std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
+
+        graph << common_params.target
+              << common_params.fast_math_hint
+              << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), common_params.data_type),
+                            get_input_accessor(common_params, std::move(preprocessor)))
               // Layer 1
               << ConvolutionLayer(
                   3U, 3U, 64U,
@@ -244,12 +218,15 @@ public:
               .set_name("fc8")
               // Softmax
               << SoftmaxLayer().set_name("prob")
-              << OutputLayer(get_output_accessor(label, 5));
+              << OutputLayer(get_output_accessor(common_params, 5));
 
         // Finalize graph
         GraphConfig config;
-        config.use_tuner = (target == 2);
-        graph.finalize(target_hint, config);
+        config.num_threads = common_params.threads;
+        config.use_tuner   = common_params.enable_tuner;
+        graph.finalize(common_params.target, config);
+
+        return true;
     }
     void do_run() override
     {
@@ -258,13 +235,16 @@ public:
     }
 
 private:
-    Stream graph{ 0, "VGG19" };
+    CommandLineParser  cmd_parser;
+    CommonGraphOptions common_opts;
+    CommonGraphParams  common_params;
+    Stream             graph;
 };
 
 /** Main program for VGG19
  *
  * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) )
+ * @param[in] argv Arguments
  */
 int main(int argc, char **argv)
 {
diff --git a/examples/neon_cartoon_effect.cpp b/examples/neon_cartoon_effect.cpp
index e6e0f34154..4285aa41e3 100644
--- a/examples/neon_cartoon_effect.cpp
+++ b/examples/neon_cartoon_effect.cpp
@@ -34,7 +34,7 @@ using namespace utils;
 class NEONCartoonEffectExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         // Open PPM file
         PPMLoader ppm;
@@ -75,6 +75,8 @@ public:
             ppm.fill_image(src_img);
             output_filename = std::string(argv[1]) + "_out.ppm";
         }
+
+        return true;
     }
 
     void do_run() override
diff --git a/examples/neon_cnn.cpp b/examples/neon_cnn.cpp
index 05b6c832bc..1df81256b9 100644
--- a/examples/neon_cnn.cpp
+++ b/examples/neon_cnn.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016, 2018 ARM Limited.
+ * Copyright (c) 2016-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -36,7 +36,7 @@ using namespace utils;
 class NEONCNNExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         ARM_COMPUTE_UNUSED(argc);
         ARM_COMPUTE_UNUSED(argv);
@@ -227,6 +227,8 @@ public:
 
         // Finalize the manager. (Validity checks, memory allocations etc)
         mm_transitions->finalize();
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/neon_convolution.cpp b/examples/neon_convolution.cpp
index 8efb932081..1a7e865908 100644
--- a/examples/neon_convolution.cpp
+++ b/examples/neon_convolution.cpp
@@ -53,7 +53,7 @@ const int16_t gaussian5x5[] =
 class NEONConvolutionExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         /** [Accurate padding] **/
         PPMLoader ppm;
@@ -94,6 +94,8 @@ public:
             output_filename = std::string(argv[1]) + "_out.ppm";
         }
         /** [Accurate padding] **/
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/neon_copy_objects.cpp b/examples/neon_copy_objects.cpp
index 9409cf366c..84a2abd379 100644
--- a/examples/neon_copy_objects.cpp
+++ b/examples/neon_copy_objects.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016, 2018 ARM Limited.
+ * Copyright (c) 2016-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -36,7 +36,7 @@ using namespace utils;
 class NEONCopyObjectsExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         ARM_COMPUTE_UNUSED(argc);
         ARM_COMPUTE_UNUSED(argv);
@@ -135,6 +135,8 @@ public:
         output_it);
 
         /** [Copy objects example] */
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/neon_scale.cpp b/examples/neon_scale.cpp
index 252bfc9ae7..b04d916aaf 100644
--- a/examples/neon_scale.cpp
+++ b/examples/neon_scale.cpp
@@ -33,7 +33,7 @@ using namespace utils;
 class NEONScaleExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         PPMLoader ppm;
 
@@ -72,6 +72,8 @@ public:
             ppm.fill_image(src);
             output_filename = std::string(argv[1]) + "_out.ppm";
         }
+
+        return true;
     }
     void do_run() override
     {
diff --git a/examples/neoncl_scale_median_gaussian.cpp b/examples/neoncl_scale_median_gaussian.cpp
index 173575c061..1b26517d9f 100644
--- a/examples/neoncl_scale_median_gaussian.cpp
+++ b/examples/neoncl_scale_median_gaussian.cpp
@@ -43,7 +43,7 @@ using namespace utils;
 class NEONCLScaleMedianGaussianExample : public Example
 {
 public:
-    void do_setup(int argc, char **argv) override
+    bool do_setup(int argc, char **argv) override
     {
         /** [NEON / OpenCL Interop] */
         PPMLoader ppm;
@@ -88,6 +88,8 @@ public:
             const std::string output_filename = std::string(argv[1]) + "_out.ppm";
         }
         /** [NEON / OpenCL Interop] */
+
+        return true;
     }
     void do_run() override
     {
diff --git a/src/graph/Graph.cpp b/src/graph/Graph.cpp
index e1ffeed668..ed24f18943 100644
--- a/src/graph/Graph.cpp
+++ b/src/graph/Graph.cpp
@@ -41,9 +41,9 @@ bool Graph::remove_node(NodeID nid)
 
     std::unique_ptr<INode> &node = _nodes[nid];
 
-    // Remove node connections
     if(node)
     {
+        // Remove node connections
         for(auto &input_eid : node->_input_edges)
         {
             remove_connection(input_eid);
@@ -52,6 +52,10 @@ bool Graph::remove_node(NodeID nid)
         {
             remove_connection(outpud_eid);
         }
+
+        // Remove nid from tagged nodes
+        std::vector<NodeID> &tnodes = _tagged_nodes.at(node->type());
+        tnodes.erase(std::remove(tnodes.begin(), tnodes.end(), nid), tnodes.end());
     }
 
     node = nullptr;
@@ -164,9 +168,9 @@ GraphID Graph::id() const
     return _id;
 }
 
-const std::vector<NodeID> &Graph::inputs()
+const std::vector<NodeID> &Graph::nodes(NodeType type)
 {
-    return _tagged_nodes[NodeType::Input];
+    return _tagged_nodes[type];
 }
 
 std::vector<std::unique_ptr<INode>> &Graph::nodes()
diff --git a/src/graph/GraphManager.cpp b/src/graph/GraphManager.cpp
index 10661ea275..db6650cf69 100644
--- a/src/graph/GraphManager.cpp
+++ b/src/graph/GraphManager.cpp
@@ -27,6 +27,7 @@
 #include "arm_compute/graph/GraphContext.h"
 #include "arm_compute/graph/Logger.h"
 #include "arm_compute/graph/PassManager.h"
+#include "arm_compute/graph/TypePrinter.h"
 #include "arm_compute/graph/Utils.h"
 #include "arm_compute/graph/detail/CrossLayerMemoryManagerHelpers.h"
 #include "arm_compute/graph/detail/ExecutionHelpers.h"
@@ -53,7 +54,12 @@ void GraphManager::finalize_graph(Graph &graph, GraphContext &ctx, PassManager &
 
     // Force target to all graph construct
     // TODO (geopin01) : Support heterogeneous execution
-    Target forced_target = is_target_supported(target) ? target : get_default_target();
+    Target forced_target = target;
+    if(!is_target_supported(target))
+    {
+        forced_target = get_default_target();
+        ARM_COMPUTE_LOG_GRAPH_INFO("Switching target from " << target << " to " << forced_target << std::endl);
+    }
     force_target_to_graph(graph, forced_target);
 
     // Configure all tensors
@@ -103,14 +109,23 @@ void GraphManager::execute_graph(Graph &graph)
     auto it = _workloads.find(graph.id());
     ARM_COMPUTE_ERROR_ON_MSG(it == std::end(_workloads), "Graph is not registered!");
 
-    // Call input accessors
-    detail::call_all_input_node_accessors(it->second);
-
-    // Run graph
-    detail::call_all_tasks(it->second);
-
-    // Call output accessors
-    detail::call_all_output_node_accessors(it->second);
+    while(true)
+    {
+        // Call input accessors
+        if(!detail::call_all_input_node_accessors(it->second))
+        {
+            return;
+        }
+
+        // Run graph
+        detail::call_all_tasks(it->second);
+
+        // Call output accessors
+        if(!detail::call_all_output_node_accessors(it->second))
+        {
+            return;
+        }
+    }
 }
 
 void GraphManager::invalidate_graph(Graph &graph)
diff --git a/src/graph/Tensor.cpp b/src/graph/Tensor.cpp
index ef253feb2c..98501280af 100644
--- a/src/graph/Tensor.cpp
+++ b/src/graph/Tensor.cpp
@@ -90,12 +90,12 @@ bool Tensor::call_accessor()
     }
 
     // Call accessor
-    _accessor->access_tensor(_handle->tensor());
+    bool retval = _accessor->access_tensor(_handle->tensor());
 
     // Unmap tensor
     _handle->unmap();
 
-    return true;
+    return retval;
 }
 
 void Tensor::bind_edge(EdgeID eid)
diff --git a/src/graph/TypeLoader.cpp b/src/graph/TypeLoader.cpp
new file mode 100644
index 0000000000..30a3546821
--- /dev/null
+++ b/src/graph/TypeLoader.cpp
@@ -0,0 +1,89 @@
+/*
+ * 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 OTHERWNISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/graph/TypeLoader.h"
+
+#include "arm_compute/core/utils/misc/Utility.h"
+
+#include <map>
+
+namespace arm_compute
+{
+arm_compute::DataType data_type_from_name(const std::string &name)
+{
+    static const std::map<std::string, arm_compute::DataType> data_types =
+    {
+        { "f16", DataType::F16 },
+        { "f32", DataType::F32 },
+        { "qasymm8", DataType::QASYMM8 },
+    };
+
+    try
+    {
+        return data_types.at(arm_compute::utility::tolower(name));
+    }
+    catch(const std::out_of_range &)
+    {
+        throw std::invalid_argument(name);
+    }
+}
+
+arm_compute::DataLayout data_layout_from_name(const std::string &name)
+{
+    static const std::map<std::string, arm_compute::DataLayout> data_layouts =
+    {
+        { "nhwc", DataLayout::NHWC },
+        { "nchw", DataLayout::NCHW },
+    };
+
+    try
+    {
+        return data_layouts.at(arm_compute::utility::tolower(name));
+    }
+    catch(const std::out_of_range &)
+    {
+        throw std::invalid_argument(name);
+    }
+}
+namespace graph
+{
+Target target_from_name(const std::string &name)
+{
+    static const std::map<std::string, Target> targets =
+    {
+        { "neon", Target::NEON },
+        { "cl", Target::CL },
+        { "gles", Target::GC },
+    };
+
+    try
+    {
+        return targets.at(arm_compute::utility::tolower(name));
+    }
+    catch(const std::out_of_range &)
+    {
+        throw std::invalid_argument(name);
+    }
+}
+} // namespace graph
+} // namespace arm_compute
diff --git a/src/graph/detail/ExecutionHelpers.cpp b/src/graph/detail/ExecutionHelpers.cpp
index d68092a2e7..6df67fcfec 100644
--- a/src/graph/detail/ExecutionHelpers.cpp
+++ b/src/graph/detail/ExecutionHelpers.cpp
@@ -206,15 +206,12 @@ void call_all_const_node_accessors(Graph &g)
     }
 }
 
-void call_all_input_node_accessors(ExecutionWorkload &workload)
+bool call_all_input_node_accessors(ExecutionWorkload &workload)
 {
-    for(auto &input : workload.inputs)
+    return !std::any_of(std::begin(workload.inputs), std::end(workload.inputs), [](Tensor * input_tensor)
     {
-        if(input != nullptr)
-        {
-            input->call_accessor();
-        }
-    }
+        return (input_tensor == nullptr) || !input_tensor->call_accessor();
+    });
 }
 
 void prepare_all_tasks(ExecutionWorkload &workload)
@@ -256,15 +253,15 @@ void call_all_tasks(ExecutionWorkload &workload)
     }
 }
 
-void call_all_output_node_accessors(ExecutionWorkload &workload)
+bool call_all_output_node_accessors(ExecutionWorkload &workload)
 {
-    for(auto &output : workload.outputs)
+    bool is_valid = true;
+    std::for_each(std::begin(workload.outputs), std::end(workload.outputs), [&](Tensor * output_tensor)
     {
-        if(output != nullptr)
-        {
-            output->call_accessor();
-        }
-    }
+        is_valid = is_valid && (output_tensor != nullptr) && output_tensor->call_accessor();
+    });
+
+    return is_valid;
 }
 } // namespace detail
 } // namespace graph
diff --git a/tests/SConscript b/tests/SConscript
index a58e1f2ea9..4465080d5b 100644
--- a/tests/SConscript
+++ b/tests/SConscript
@@ -198,17 +198,17 @@ if test_env['benchmark_examples']:
 
     # Graph examples
     graph_utils = test_env.Object(source="../utils/GraphUtils.cpp", target="GraphUtils")
+    graph_params = test_env.Object(source="../utils/CommonGraphOptions.cpp", target="CommonGraphOptions")
     for file in Glob("../examples/graph_*.cpp"):
         example = "benchmark_" + os.path.basename(os.path.splitext(str(file))[0])
         if env['os'] in ['android', 'bare_metal'] or env['standalone']:
-            prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils]+ files_benchmark_examples, LIBS = test_env["LIBS"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--whole-archive',arm_compute_lib,'-Wl,--no-whole-archive'])
+            prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils, graph_params]+ files_benchmark_examples, LIBS = test_env["LIBS"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--whole-archive',arm_compute_lib,'-Wl,--no-whole-archive'])
             arm_compute_benchmark_examples += [ prog ]
         else:
             #-Wl,--allow-shlib-undefined: Ignore dependencies of dependencies
-            prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils]+ files_benchmark_examples, LIBS = test_env["LIBS"] + ["arm_compute_graph"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--allow-shlib-undefined'] )
+            prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils, graph_params]+ files_benchmark_examples, LIBS = test_env["LIBS"] + ["arm_compute_graph"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--allow-shlib-undefined'] )
             arm_compute_benchmark_examples += [ prog ]
     Depends(arm_compute_benchmark_examples, arm_compute_test_framework)
     Depends(arm_compute_benchmark_examples, arm_compute_lib)
     Default(arm_compute_benchmark_examples)
     Export('arm_compute_benchmark_examples')
-
diff --git a/tests/benchmark_examples/RunExample.cpp b/tests/benchmark_examples/RunExample.cpp
index f6a9742048..05430e7628 100644
--- a/tests/benchmark_examples/RunExample.cpp
+++ b/tests/benchmark_examples/RunExample.cpp
@@ -30,9 +30,9 @@
 #include "arm_compute/runtime/Scheduler.h"
 #include "tests/framework/Framework.h"
 #include "tests/framework/Macros.h"
-#include "tests/framework/command_line/CommandLineParser.h"
 #include "tests/framework/command_line/CommonOptions.h"
 #include "tests/framework/instruments/Instruments.h"
+#include "utils/command_line/CommandLineParser.h"
 
 #ifdef ARM_COMPUTE_CL
 #include "arm_compute/runtime/CL/CLScheduler.h"
@@ -74,9 +74,9 @@ public:
 
 int run_example(int argc, char **argv, std::unique_ptr<Example> example)
 {
-    framework::CommandLineParser parser;
-    framework::CommonOptions     options(parser);
-    auto                         example_args = parser.add_option<framework::ListOption<std::string>>("example_args");
+    utils::CommandLineParser parser;
+    framework::CommonOptions options(parser);
+    auto                     example_args = parser.add_option<utils::ListOption<std::string>>("example_args");
     example_args->set_help("Arguments to pass to the example separated by commas (e.g: arg0,arg1,arg2)");
     framework::Framework &framework = framework::Framework::get();
 
diff --git a/tests/framework/command_line/CommandLineParser.h b/tests/framework/command_line/CommandLineParser.h
deleted file mode 100644
index adb5214e2f..0000000000
--- a/tests/framework/command_line/CommandLineParser.h
+++ /dev/null
@@ -1,117 +0,0 @@
-/*
- * 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.
- */
-#ifndef ARM_COMPUTE_TEST_COMMANDLINEPARSER
-#define ARM_COMPUTE_TEST_COMMANDLINEPARSER
-
-#include "../Utils.h"
-#include "Option.h"
-
-#include <map>
-#include <memory>
-#include <string>
-#include <utility>
-#include <vector>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace framework
-{
-/** Class to parse command line arguments. */
-class CommandLineParser final
-{
-public:
-    /** Default constructor. */
-    CommandLineParser() = default;
-
-    /** Function to add a new option to the parser.
-     *
-     * @param[in] name Name of the option. Will be available under --name=VALUE.
-     * @param[in] args Option specific configuration arguments.
-     *
-     * @return Pointer to the option. The option is owned by the parser.
-     */
-    template <typename T, typename... As>
-    T *add_option(const std::string &name, As &&... args);
-
-    /** Function to add a new positional argument to the parser.
-     *
-     * @param[in] args Option specific configuration arguments.
-     *
-     * @return Pointer to the option. The option is owned by the parser.
-     */
-    template <typename T, typename... As>
-    T *add_positional_option(As &&... args);
-
-    /** Parses the command line arguments and updates the options accordingly.
-     *
-     * @param[in] argc Number of arguments.
-     * @param[in] argv Arguments.
-     */
-    void parse(int argc, char **argv);
-
-    /** Validates the previously parsed command line arguments.
-     *
-     * Validation fails if not all required options are provided. Additionally
-     * warnings are generated for options that have illegal values or unknown
-     * options.
-     *
-     * @return True if all required options have been provided.
-     */
-    bool validate() const;
-
-    /** Prints a help message for all configured options.
-     *
-     * @param[in] program_name Name of the program to be used in the help message.
-     */
-    void print_help(const std::string &program_name) const;
-
-private:
-    using OptionsMap              = std::map<std::string, std::unique_ptr<Option>>;
-    using PositionalOptionsVector = std::vector<std::unique_ptr<Option>>;
-
-    OptionsMap               _options{};
-    PositionalOptionsVector  _positional_options{};
-    std::vector<std::string> _unknown_options{};
-    std::vector<std::string> _invalid_options{};
-};
-
-template <typename T, typename... As>
-inline T *CommandLineParser::add_option(const std::string &name, As &&... args)
-{
-    auto result = _options.emplace(name, support::cpp14::make_unique<T>(name, std::forward<As>(args)...));
-    return static_cast<T *>(result.first->second.get());
-}
-
-template <typename T, typename... As>
-inline T *CommandLineParser::add_positional_option(As &&... args)
-{
-    _positional_options.emplace_back(support::cpp14::make_unique<T>(std::forward<As>(args)...));
-    return static_cast<T *>(_positional_options.back().get());
-}
-} // namespace framework
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_COMMANDLINEPARSER */
diff --git a/tests/framework/command_line/CommonOptions.cpp b/tests/framework/command_line/CommonOptions.cpp
index e0b93f6830..f1c140e6fe 100644
--- a/tests/framework/command_line/CommonOptions.cpp
+++ b/tests/framework/command_line/CommonOptions.cpp
@@ -25,9 +25,10 @@
 
 #include "../Framework.h"
 #include "../printers/Printers.h"
-#include "CommandLineParser.h"
 #include <unistd.h>
 
+using namespace arm_compute::utils;
+
 namespace arm_compute
 {
 namespace test
diff --git a/tests/framework/command_line/CommonOptions.h b/tests/framework/command_line/CommonOptions.h
index 651316c557..b29c1d8dd5 100644
--- a/tests/framework/command_line/CommonOptions.h
+++ b/tests/framework/command_line/CommonOptions.h
@@ -25,7 +25,10 @@
 #define ARM_COMPUTE_TEST_COMMONOPTIONS
 
 #include "../instruments/Instruments.h"
-#include "CommandLineOptions.h"
+
+#include "utils/command_line/CommandLineOptions.h"
+#include "utils/command_line/CommandLineParser.h"
+
 #include <memory>
 
 namespace arm_compute
@@ -34,7 +37,6 @@ namespace test
 {
 namespace framework
 {
-class CommandLineParser;
 class Printer;
 enum class LogFormat;
 enum class LogLevel;
@@ -56,7 +58,7 @@ public:
      *
      * @param[in,out] parser A parser on which "parse()" hasn't been called yet.
      */
-    CommonOptions(CommandLineParser &parser);
+    CommonOptions(arm_compute::utils::CommandLineParser &parser);
     /** Prevent instances of this class from being copy constructed */
     CommonOptions(const CommonOptions &) = delete;
     /** Prevent instances of this class from being copied */
@@ -69,19 +71,19 @@ public:
      */
     std::vector<std::unique_ptr<Printer>> create_printers();
 
-    ToggleOption                               *help;           /**< Show help option */
-    EnumListOption<InstrumentsDescription>     *instruments;    /**< Instruments option */
-    SimpleOption<int>                          *iterations;     /**< Number of iterations option */
-    SimpleOption<int>                          *threads;        /**< Number of threads option */
-    EnumOption<LogFormat>                      *log_format;     /**< Log format option */
-    SimpleOption<std::string>                  *log_file;       /**< Log file option */
-    EnumOption<LogLevel>                       *log_level;      /**< Logging level option */
-    ToggleOption                               *throw_errors;   /**< Throw errors option */
-    ToggleOption                               *color_output;   /**< Color output option */
-    ToggleOption                               *pretty_console; /**< Pretty console option */
-    SimpleOption<std::string>                  *json_file;      /**< JSON output file option */
-    SimpleOption<std::string>                  *pretty_file;    /**< Pretty output file option */
-    std::vector<std::shared_ptr<std::ofstream>> log_streams;    /**< Log streams */
+    arm_compute::utils::ToggleOption                           *help;           /**< Show help option */
+    arm_compute::utils::EnumListOption<InstrumentsDescription> *instruments;    /**< Instruments option */
+    arm_compute::utils::SimpleOption<int>                      *iterations;     /**< Number of iterations option */
+    arm_compute::utils::SimpleOption<int>                      *threads;        /**< Number of threads option */
+    arm_compute::utils::EnumOption<LogFormat>                  *log_format;     /**< Log format option */
+    arm_compute::utils::SimpleOption<std::string>              *log_file;       /**< Log file option */
+    arm_compute::utils::EnumOption<LogLevel>                   *log_level;      /**< Logging level option */
+    arm_compute::utils::ToggleOption                           *throw_errors;   /**< Throw errors option */
+    arm_compute::utils::ToggleOption                           *color_output;   /**< Color output option */
+    arm_compute::utils::ToggleOption                           *pretty_console; /**< Pretty console option */
+    arm_compute::utils::SimpleOption<std::string>              *json_file;      /**< JSON output file option */
+    arm_compute::utils::SimpleOption<std::string>              *pretty_file;    /**< Pretty output file option */
+    std::vector<std::shared_ptr<std::ofstream>>                 log_streams;    /**< Log streams */
 };
 
 } // namespace framework
diff --git a/tests/framework/command_line/Option.cpp b/tests/framework/command_line/Option.cpp
deleted file mode 100644
index d60c35a698..0000000000
--- a/tests/framework/command_line/Option.cpp
+++ /dev/null
@@ -1,68 +0,0 @@
-/*
- * 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 "Option.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace framework
-{
-Option::Option(std::string name)
-    : _name{ std::move(name) }
-{
-}
-
-Option::Option(std::string name, bool is_required, bool is_set)
-    : _name{ std::move(name) }, _is_required{ is_required }, _is_set{ is_set }
-{
-}
-
-std::string Option::name() const
-{
-    return _name;
-}
-
-void Option::set_required(bool is_required)
-{
-    _is_required = is_required;
-}
-
-void Option::set_help(std::string help)
-{
-    _help = std::move(help);
-}
-
-bool Option::is_required() const
-{
-    return _is_required;
-}
-
-bool Option::is_set() const
-{
-    return _is_set;
-}
-} // namespace framework
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/framework/command_line/ToggleOption.cpp b/tests/framework/command_line/ToggleOption.cpp
deleted file mode 100644
index df5b1f813b..0000000000
--- a/tests/framework/command_line/ToggleOption.cpp
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
- * 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 "ToggleOption.h"
-
-#include <utility>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace framework
-{
-ToggleOption::ToggleOption(std::string name, bool default_value)
-    : SimpleOption<bool>
-{
-    std::move(name), default_value
-}
-{
-}
-
-bool ToggleOption::parse(std::string value)
-{
-    if(value == "true")
-    {
-        _value  = true;
-        _is_set = true;
-    }
-    else if(value == "false")
-    {
-        _value  = false;
-        _is_set = true;
-    }
-
-    return _is_set;
-}
-
-std::string ToggleOption::help() const
-{
-    return "--" + name() + ", --no-" + name() + " - " + _help;
-}
-} // namespace framework
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/main.cpp b/tests/main.cpp
index 4a8a82d490..ae9a47e1d4 100644
--- a/tests/main.cpp
+++ b/tests/main.cpp
@@ -28,11 +28,11 @@
 #include "tests/framework/Framework.h"
 #include "tests/framework/Macros.h"
 #include "tests/framework/Profiler.h"
-#include "tests/framework/command_line/CommandLineOptions.h"
-#include "tests/framework/command_line/CommandLineParser.h"
 #include "tests/framework/command_line/CommonOptions.h"
 #include "tests/framework/instruments/Instruments.h"
 #include "tests/framework/printers/Printers.h"
+#include "utils/command_line/CommandLineOptions.h"
+#include "utils/command_line/CommandLineParser.h"
 
 #ifdef ARM_COMPUTE_CL
 #include "arm_compute/runtime/CL/CLScheduler.h"
@@ -72,7 +72,7 @@ int main(int argc, char **argv)
 
     framework::Framework &framework = framework::Framework::get();
 
-    framework::CommandLineParser parser;
+    utils::CommandLineParser parser;
 
     std::set<framework::DatasetMode> allowed_modes
     {
@@ -83,23 +83,23 @@ int main(int argc, char **argv)
 
     framework::CommonOptions options(parser);
 
-    auto dataset_mode = parser.add_option<framework::EnumOption<framework::DatasetMode>>("mode", allowed_modes, framework::DatasetMode::PRECOMMIT);
+    auto dataset_mode = parser.add_option<utils::EnumOption<framework::DatasetMode>>("mode", allowed_modes, framework::DatasetMode::PRECOMMIT);
     dataset_mode->set_help("For managed datasets select which group to use");
-    auto filter = parser.add_option<framework::SimpleOption<std::string>>("filter", ".*");
+    auto filter = parser.add_option<utils::SimpleOption<std::string>>("filter", ".*");
     filter->set_help("Regular expression to select test cases");
-    auto filter_id = parser.add_option<framework::SimpleOption<std::string>>("filter-id");
+    auto filter_id = parser.add_option<utils::SimpleOption<std::string>>("filter-id");
     filter_id->set_help("List of test ids. ... can be used to define a range.");
-    auto stop_on_error = parser.add_option<framework::ToggleOption>("stop-on-error");
+    auto stop_on_error = parser.add_option<utils::ToggleOption>("stop-on-error");
     stop_on_error->set_help("Abort execution after the first failed test (useful for debugging)");
-    auto seed = parser.add_option<framework::SimpleOption<std::random_device::result_type>>("seed", std::random_device()());
+    auto seed = parser.add_option<utils::SimpleOption<std::random_device::result_type>>("seed", std::random_device()());
     seed->set_help("Global seed for random number generation");
-    auto list_tests = parser.add_option<framework::ToggleOption>("list-tests", false);
+    auto list_tests = parser.add_option<utils::ToggleOption>("list-tests", false);
     list_tests->set_help("List all test names");
-    auto test_instruments = parser.add_option<framework::ToggleOption>("test-instruments", false);
+    auto test_instruments = parser.add_option<utils::ToggleOption>("test-instruments", false);
     test_instruments->set_help("Test if the instruments work on the platform");
-    auto error_on_missing_assets = parser.add_option<framework::ToggleOption>("error-on-missing-assets", false);
+    auto error_on_missing_assets = parser.add_option<utils::ToggleOption>("error-on-missing-assets", false);
     error_on_missing_assets->set_help("Mark a test as failed instead of skipping it when assets are missing");
-    auto assets = parser.add_positional_option<framework::SimpleOption<std::string>>("assets");
+    auto assets = parser.add_positional_option<utils::SimpleOption<std::string>>("assets");
     assets->set_help("Path to the assets directory");
 
     try
diff --git a/tests/validate_examples/RunExample.cpp b/tests/validate_examples/RunExample.cpp
index 8b1c39b844..b4e5d37648 100644
--- a/tests/validate_examples/RunExample.cpp
+++ b/tests/validate_examples/RunExample.cpp
@@ -33,9 +33,9 @@
 #include "tests/Globals.h"
 #include "tests/framework/Framework.h"
 #include "tests/framework/Macros.h"
-#include "tests/framework/command_line/CommandLineParser.h"
 #include "tests/framework/command_line/CommonOptions.h"
 #include "tests/framework/instruments/Instruments.h"
+#include "utils/command_line/CommandLineParser.h"
 
 #ifdef ARM_COMPUTE_CL
 #include "arm_compute/runtime/CL/CLScheduler.h"
@@ -87,13 +87,13 @@ public:
 
 int run_example(int argc, char **argv, std::unique_ptr<ValidateExample> example)
 {
-    framework::CommandLineParser parser;
-    framework::CommonOptions     options(parser);
-    auto                         example_args = parser.add_option<framework::ListOption<std::string>>("example_args");
+    utils::CommandLineParser parser;
+    framework::CommonOptions options(parser);
+    auto                     example_args = parser.add_option<utils::ListOption<std::string>>("example_args");
     example_args->set_help("Arguments to pass to the example separated by commas (e.g: arg0,arg1,arg2)");
-    auto seed = parser.add_option<framework::SimpleOption<std::random_device::result_type>>("seed", std::random_device()());
+    auto seed = parser.add_option<utils::SimpleOption<std::random_device::result_type>>("seed", std::random_device()());
     seed->set_help("Global seed for random number generation");
-    auto validate = parser.add_option<framework::SimpleOption<int>>("validate", 1);
+    auto validate = parser.add_option<utils::SimpleOption<int>>("validate", 1);
     validate->set_help("Enable / disable output validation (0/1)");
 
     framework::Framework &framework = framework::Framework::get();
diff --git a/utils/CommonGraphOptions.cpp b/utils/CommonGraphOptions.cpp
new file mode 100644
index 0000000000..d6ff0516aa
--- /dev/null
+++ b/utils/CommonGraphOptions.cpp
@@ -0,0 +1,190 @@
+/*
+ * 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 "CommonGraphOptions.h"
+
+#include "arm_compute/graph/TypeLoader.h"
+#include "arm_compute/graph/TypePrinter.h"
+
+#include "support/ToolchainSupport.h"
+
+#include <map>
+
+using namespace arm_compute::graph;
+
+namespace
+{
+std::pair<unsigned int, unsigned int> parse_validation_range(const std::string &validation_range)
+{
+    std::pair<unsigned int /* start */, unsigned int /* end */> range = { 0, std::numeric_limits<unsigned int>::max() };
+    if(!validation_range.empty())
+    {
+        std::string       str;
+        std::stringstream stream(validation_range);
+
+        // Get first value
+        std::getline(stream, str, ',');
+        if(stream.fail())
+        {
+            return range;
+        }
+        else
+        {
+            range.first = arm_compute::support::cpp11::stoi(str);
+        }
+
+        // Get second value
+        std::getline(stream, str);
+        if(stream.fail())
+        {
+            range.second = range.first;
+            return range;
+        }
+        else
+        {
+            range.second = arm_compute::support::cpp11::stoi(str);
+        }
+    }
+    return range;
+}
+} // namespace
+
+namespace arm_compute
+{
+namespace utils
+{
+::std::ostream &operator<<(::std::ostream &os, const CommonGraphParams &common_params)
+{
+    std::string false_str = std::string("false");
+    std::string true_str  = std::string("true");
+
+    os << "Threads : " << common_params.threads << std::endl;
+    os << "Target : " << common_params.target << std::endl;
+    os << "Data type : " << common_params.data_type << std::endl;
+    os << "Data layout : " << common_params.data_layout << std::endl;
+    os << "Tuner enabled? : " << (common_params.enable_tuner ? true_str : false_str) << std::endl;
+    os << "Fast math enabled? : " << (common_params.fast_math_hint == FastMathHint::ENABLED ? true_str : false_str) << std::endl;
+    if(!common_params.data_path.empty())
+    {
+        os << "Data path : " << common_params.data_path << std::endl;
+    }
+    if(!common_params.image.empty())
+    {
+        os << "Image file : " << common_params.image << std::endl;
+    }
+    if(!common_params.labels.empty())
+    {
+        os << "Labels file : " << common_params.labels << std::endl;
+    }
+    if(!common_params.validation_file.empty())
+    {
+        os << "Validation range : " << common_params.validation_range_start << "-" << common_params.validation_range_end << std::endl;
+        os << "Validation file : " << common_params.validation_file << std::endl;
+        if(!common_params.validation_path.empty())
+        {
+            os << "Validation path : " << common_params.validation_path << std::endl;
+        }
+    }
+
+    return os;
+}
+
+CommonGraphOptions::CommonGraphOptions(CommandLineParser &parser)
+    : help(parser.add_option<ToggleOption>("help")),
+      threads(parser.add_option<SimpleOption<int>>("threads", 1)),
+      target(),
+      data_type(),
+      data_layout(),
+      enable_tuner(parser.add_option<ToggleOption>("enable-tuner")),
+      fast_math_hint(parser.add_option<ToggleOption>("fast-math")),
+      data_path(parser.add_option<SimpleOption<std::string>>("data")),
+      image(parser.add_option<SimpleOption<std::string>>("image")),
+      labels(parser.add_option<SimpleOption<std::string>>("labels")),
+      validation_file(parser.add_option<SimpleOption<std::string>>("validation-file")),
+      validation_path(parser.add_option<SimpleOption<std::string>>("validation-path")),
+      validation_range(parser.add_option<SimpleOption<std::string>>("validation-range"))
+{
+    std::set<arm_compute::graph::Target> supported_targets
+    {
+        Target::NEON,
+        Target::CL,
+        Target::GC,
+    };
+
+    std::set<arm_compute::DataType> supported_data_types
+    {
+        DataType::F16,
+        DataType::F32,
+        DataType::QASYMM8,
+    };
+
+    std::set<DataLayout> supported_data_layouts
+    {
+        DataLayout::NHWC,
+        DataLayout::NCHW,
+    };
+
+    target      = parser.add_option<EnumOption<Target>>("target", supported_targets, Target::NEON);
+    data_type   = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32);
+    data_layout = parser.add_option<EnumOption<DataLayout>>("layout", supported_data_layouts, DataLayout::NCHW);
+
+    help->set_help("Show this help message");
+    threads->set_help("Number of threads to use");
+    target->set_help("Target to execute on");
+    data_type->set_help("Data type to use");
+    data_layout->set_help("Data layout to use");
+    enable_tuner->set_help("Enable tuner");
+    fast_math_hint->set_help("Enable fast math");
+    data_path->set_help("Path where graph parameters reside");
+    image->set_help("Input image for the graph");
+    labels->set_help("File containing the output labels");
+    validation_file->set_help("File used to validate the graph");
+    validation_path->set_help("Path to the validation data");
+    validation_range->set_help("Range of the images to validate for (Format : start,end)");
+}
+
+CommonGraphParams consume_common_graph_parameters(CommonGraphOptions &options)
+{
+    FastMathHint fast_math_hint_value = options.fast_math_hint->value() ? FastMathHint::ENABLED : FastMathHint::DISABLED;
+    auto         validation_range     = parse_validation_range(options.validation_range->value());
+
+    CommonGraphParams common_params;
+    common_params.help                   = options.help->is_set() ? options.help->value() : false;
+    common_params.threads                = options.threads->value();
+    common_params.target                 = options.target->value();
+    common_params.data_type              = options.data_type->value();
+    common_params.data_layout            = options.data_layout->value();
+    common_params.enable_tuner           = options.enable_tuner->is_set() ? options.enable_tuner->value() : false;
+    common_params.fast_math_hint         = options.fast_math_hint->is_set() ? fast_math_hint_value : FastMathHint::DISABLED;
+    common_params.data_path              = options.data_path->value();
+    common_params.image                  = options.image->value();
+    common_params.labels                 = options.labels->value();
+    common_params.validation_file        = options.validation_file->value();
+    common_params.validation_path        = options.validation_path->value();
+    common_params.validation_range_start = validation_range.first;
+    common_params.validation_range_end   = validation_range.second;
+
+    return common_params;
+}
+} // namespace utils
+} // namespace arm_compute
diff --git a/utils/CommonGraphOptions.h b/utils/CommonGraphOptions.h
new file mode 100644
index 0000000000..ef2e4fb946
--- /dev/null
+++ b/utils/CommonGraphOptions.h
@@ -0,0 +1,111 @@
+/*
+ * 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.
+ */
+#ifndef ARM_COMPUTE_EXAMPLES_UTILS_COMMON_GRAPH_OPTIONS
+#define ARM_COMPUTE_EXAMPLES_UTILS_COMMON_GRAPH_OPTIONS
+
+#include "utils/command_line/CommandLineOptions.h"
+#include "utils/command_line/CommandLineParser.h"
+
+#include "arm_compute/graph/TypeLoader.h"
+#include "arm_compute/graph/TypePrinter.h"
+
+namespace arm_compute
+{
+namespace utils
+{
+/** Structure holding all the common graph parameters */
+struct CommonGraphParams
+{
+    bool                             help{ false };
+    int                              threads{ 0 };
+    arm_compute::graph::Target       target{ arm_compute::graph::Target::NEON };
+    arm_compute::DataType            data_type{ DataType::F32 };
+    arm_compute::DataLayout          data_layout{ DataLayout::NCHW };
+    bool                             enable_tuner{ false };
+    arm_compute::graph::FastMathHint fast_math_hint{ arm_compute::graph::FastMathHint::DISABLED };
+    std::string                      data_path{};
+    std::string                      image{};
+    std::string                      labels{};
+    std::string                      validation_file{};
+    std::string                      validation_path{};
+    unsigned int                     validation_range_start{ 0 };
+    unsigned int                     validation_range_end{ std::numeric_limits<unsigned int>::max() };
+};
+
+/** Formatted output of the CommonGraphParams type
+ *
+ * @param[out] os            Output stream.
+ * @param[in]  common_params Common parameters to output
+ *
+ * @return Modified output stream.
+ */
+::std::ostream &operator<<(::std::ostream &os, const CommonGraphParams &common_params);
+
+/** Common command line options used to configure the graph examples
+ *
+ * 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 CommonGraphOptions
+{
+public:
+    /** Constructor
+     *
+     * @param[in,out] parser A parser on which "parse()" hasn't been called yet.
+     */
+    CommonGraphOptions(CommandLineParser &parser);
+    /** Prevent instances of this class from being copy constructed */
+    CommonGraphOptions(const CommonGraphOptions &) = delete;
+    /** Prevent instances of this class from being copied */
+    CommonGraphOptions &operator=(const CommonGraphOptions &) = delete;
+
+    ToggleOption                           *help;             /**< Show help option */
+    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 */
+    EnumOption<arm_compute::DataLayout>    *data_layout;      /**< Graph data layout */
+    ToggleOption                           *enable_tuner;     /**< Enable tuner */
+    ToggleOption                           *fast_math_hint;   /**< Fast math hint */
+    SimpleOption<std::string>              *data_path;        /**< Trainable parameters path */
+    SimpleOption<std::string>              *image;            /**< Image */
+    SimpleOption<std::string>              *labels;           /**< Labels */
+    SimpleOption<std::string>              *validation_file;  /**< Validation file */
+    SimpleOption<std::string>              *validation_path;  /**< Validation data path */
+    SimpleOption<std::string>              *validation_range; /**< Validation range */
+};
+
+/** Consumes the common graph options and creates a structure containing any information
+ *
+ * @param[in] options Options to consume
+ *
+ * @return Structure containing the commnon graph parameters
+ */
+CommonGraphParams consume_common_graph_parameters(CommonGraphOptions &options);
+} // namespace utils
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_EXAMPLES_UTILS_COMMON_GRAPH_OPTIONS */
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index d94dcb0d86..5c1fda5ca6 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -26,11 +26,13 @@
 
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/Types.h"
+#include "arm_compute/graph/Logger.h"
 #include "arm_compute/runtime/SubTensor.h"
 #include "utils/ImageLoader.h"
 #include "utils/Utils.h"
 
 #include <iomanip>
+#include <limits>
 
 using namespace arm_compute::graph_utils;
 
@@ -169,17 +171,18 @@ bool NumPyAccessor::access_tensor(ITensor &tensor)
     return false;
 }
 
-PPMAccessor::PPMAccessor(std::string ppm_path, bool bgr, std::unique_ptr<IPreprocessor> preprocessor)
-    : _ppm_path(std::move(ppm_path)), _bgr(bgr), _preprocessor(std::move(preprocessor))
+ImageAccessor::ImageAccessor(std::string filename, bool bgr, std::unique_ptr<IPreprocessor> preprocessor)
+    : _filename(std::move(filename)), _bgr(bgr), _preprocessor(std::move(preprocessor))
 {
 }
 
-bool PPMAccessor::access_tensor(ITensor &tensor)
+bool ImageAccessor::access_tensor(ITensor &tensor)
 {
-    utils::PPMLoader ppm;
+    auto image_loader = utils::ImageLoaderFactory::create(_filename);
+    ARM_COMPUTE_ERROR_ON_MSG(image_loader == nullptr, "Unsupported image type");
 
-    // Open PPM file
-    ppm.open(_ppm_path);
+    // Open image file
+    image_loader->open(_filename);
 
     // Get permutated shape and permutation parameters
     TensorShape                    permuted_shape = tensor.info()->tensor_shape();
@@ -188,11 +191,12 @@ bool PPMAccessor::access_tensor(ITensor &tensor)
     {
         std::tie(permuted_shape, perm) = compute_permutation_paramaters(tensor.info()->tensor_shape(), tensor.info()->data_layout());
     }
-    ARM_COMPUTE_ERROR_ON_MSG(ppm.width() != permuted_shape.x() || ppm.height() != permuted_shape.y(),
-                             "Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].", ppm.width(), ppm.height(), permuted_shape.x(), permuted_shape.y());
+    ARM_COMPUTE_ERROR_ON_MSG(image_loader->width() != permuted_shape.x() || image_loader->height() != permuted_shape.y(),
+                             "Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].",
+                             image_loader->width(), image_loader->height(), permuted_shape.x(), permuted_shape.y());
 
     // Fill the tensor with the PPM content (BGR)
-    ppm.fill_planar_tensor(tensor, _bgr);
+    image_loader->fill_planar_tensor(tensor, _bgr);
 
     // Preprocess tensor
     if(_preprocessor)
@@ -203,12 +207,13 @@ bool PPMAccessor::access_tensor(ITensor &tensor)
     return true;
 }
 
-ValidationInputAccessor::ValidationInputAccessor(const std::string &image_list,
-                                                 std::string        images_path,
-                                                 bool               bgr,
-                                                 unsigned int       start,
-                                                 unsigned int       end)
-    : _path(std::move(images_path)), _images(), _bgr(bgr), _offset(0)
+ValidationInputAccessor::ValidationInputAccessor(const std::string             &image_list,
+                                                 std::string                    images_path,
+                                                 std::unique_ptr<IPreprocessor> preprocessor,
+                                                 bool                           bgr,
+                                                 unsigned int                   start,
+                                                 unsigned int                   end)
+    : _path(std::move(images_path)), _images(), _preprocessor(std::move(preprocessor)), _bgr(bgr), _offset(0)
 {
     ARM_COMPUTE_ERROR_ON_MSG(start > end, "Invalid validation range!");
 
@@ -247,7 +252,9 @@ bool ValidationInputAccessor::access_tensor(arm_compute::ITensor &tensor)
         utils::JPEGLoader jpeg;
 
         // Open JPEG file
-        jpeg.open(_path + _images[_offset++]);
+        std::string image_name = _path + _images[_offset++];
+        jpeg.open(image_name);
+        ARM_COMPUTE_LOG_GRAPH_INFO("Validating " << image_name << std::endl);
 
         // Get permutated shape and permutation parameters
         TensorShape                    permuted_shape = tensor.info()->tensor_shape();
@@ -261,22 +268,26 @@ bool ValidationInputAccessor::access_tensor(arm_compute::ITensor &tensor)
                                  "Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].",
                                  jpeg.width(), jpeg.height(), permuted_shape.x(), permuted_shape.y());
 
-        // Fill the tensor with the PPM content (BGR)
+        // Fill the tensor with the JPEG content (BGR)
         jpeg.fill_planar_tensor(tensor, _bgr);
+
+        // Preprocess tensor
+        if(_preprocessor)
+        {
+            _preprocessor->preprocess(tensor);
+        }
     }
 
     return ret;
 }
 
 ValidationOutputAccessor::ValidationOutputAccessor(const std::string &image_list,
-                                                   size_t             top_n,
                                                    std::ostream      &output_stream,
                                                    unsigned int       start,
                                                    unsigned int       end)
-    : _results(), _output_stream(output_stream), _top_n(top_n), _offset(0), _positive_samples(0)
+    : _results(), _output_stream(output_stream), _offset(0), _positive_samples_top1(0), _positive_samples_top5(0)
 {
     ARM_COMPUTE_ERROR_ON_MSG(start > end, "Invalid validation range!");
-    ARM_COMPUTE_ERROR_ON(top_n == 0);
 
     std::ifstream ifs;
     try
@@ -308,13 +319,15 @@ ValidationOutputAccessor::ValidationOutputAccessor(const std::string &image_list
 
 void ValidationOutputAccessor::reset()
 {
-    _offset           = 0;
-    _positive_samples = 0;
+    _offset                = 0;
+    _positive_samples_top1 = 0;
+    _positive_samples_top5 = 0;
 }
 
 bool ValidationOutputAccessor::access_tensor(arm_compute::ITensor &tensor)
 {
-    if(_offset < _results.size())
+    bool ret = _offset < _results.size();
+    if(ret)
     {
         // Get results
         std::vector<size_t> tensor_results;
@@ -332,30 +345,16 @@ bool ValidationOutputAccessor::access_tensor(arm_compute::ITensor &tensor)
 
         // Check if tensor results are within top-n accuracy
         size_t correct_label = _results[_offset++];
-        auto is_valid_label  = [&](size_t label)
-        {
-            return label == correct_label;
-        };
 
-        if(std::any_of(std::begin(tensor_results), std::begin(tensor_results) + _top_n - 1, is_valid_label))
-        {
-            ++_positive_samples;
-        }
+        aggregate_sample(tensor_results, _positive_samples_top1, 1, correct_label);
+        aggregate_sample(tensor_results, _positive_samples_top5, 5, correct_label);
     }
 
     // Report top_n accuracy
-    bool ret = _offset >= _results.size();
-    if(ret)
+    if(_offset >= _results.size())
     {
-        size_t total_samples    = _results.size();
-        size_t negative_samples = total_samples - _positive_samples;
-        float  accuracy         = _positive_samples / static_cast<float>(total_samples);
-
-        _output_stream << "----------Top " << _top_n << " accuracy ----------" << std::endl
-                       << std::endl;
-        _output_stream << "Positive samples : " << _positive_samples << std::endl;
-        _output_stream << "Negative samples : " << negative_samples << std::endl;
-        _output_stream << "Accuracy : " << accuracy << std::endl;
+        report_top_n(1, _results.size(), _positive_samples_top1);
+        report_top_n(5, _results.size(), _positive_samples_top5);
     }
 
     return ret;
@@ -383,6 +382,31 @@ std::vector<size_t> ValidationOutputAccessor::access_predictions_tensor(arm_comp
     return index;
 }
 
+void ValidationOutputAccessor::aggregate_sample(const std::vector<size_t> &res, size_t &positive_samples, size_t top_n, size_t correct_label)
+{
+    auto is_valid_label = [correct_label](size_t label)
+    {
+        return label == correct_label;
+    };
+
+    if(std::any_of(std::begin(res), std::begin(res) + top_n, is_valid_label))
+    {
+        ++positive_samples;
+    }
+}
+
+void ValidationOutputAccessor::report_top_n(size_t top_n, size_t total_samples, size_t positive_samples)
+{
+    size_t negative_samples = total_samples - positive_samples;
+    float  accuracy         = positive_samples / static_cast<float>(total_samples);
+
+    _output_stream << "----------Top " << top_n << " accuracy ----------" << std::endl
+                   << std::endl;
+    _output_stream << "Positive samples : " << positive_samples << std::endl;
+    _output_stream << "Negative samples : " << negative_samples << std::endl;
+    _output_stream << "Accuracy : " << accuracy << std::endl;
+}
+
 TopNPredictionsAccessor::TopNPredictionsAccessor(const std::string &labels_path, size_t top_n, std::ostream &output_stream)
     : _labels(), _output_stream(output_stream), _top_n(top_n)
 {
diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h
index 768c608d26..8558b9066c 100644
--- a/utils/GraphUtils.h
+++ b/utils/GraphUtils.h
@@ -31,6 +31,8 @@
 #include "arm_compute/graph/Types.h"
 #include "arm_compute/runtime/Tensor.h"
 
+#include "utils/CommonGraphOptions.h"
+
 #include <array>
 #include <random>
 #include <string>
@@ -150,25 +152,25 @@ private:
     std::ostream     &_output_stream;
 };
 
-/** PPM accessor class */
-class PPMAccessor final : public graph::ITensorAccessor
+/** Image accessor class */
+class ImageAccessor final : public graph::ITensorAccessor
 {
 public:
     /** Constructor
      *
-     * @param[in] ppm_path     Path to PPM file
+     * @param[in] filename     Image file
      * @param[in] bgr          (Optional) Fill the first plane with blue channel (default = false - RGB format)
-     * @param[in] preprocessor (Optional) PPM pre-processing object
+     * @param[in] preprocessor (Optional) Image pre-processing object
      */
-    PPMAccessor(std::string ppm_path, bool bgr = true, std::unique_ptr<IPreprocessor> preprocessor = nullptr);
+    ImageAccessor(std::string filename, bool bgr = true, std::unique_ptr<IPreprocessor> preprocessor = nullptr);
     /** Allow instances of this class to be move constructed */
-    PPMAccessor(PPMAccessor &&) = default;
+    ImageAccessor(ImageAccessor &&) = default;
 
     // Inherited methods overriden:
     bool access_tensor(ITensor &tensor) override;
 
 private:
-    const std::string              _ppm_path;
+    const std::string              _filename;
     const bool                     _bgr;
     std::unique_ptr<IPreprocessor> _preprocessor;
 };
@@ -179,28 +181,31 @@ class ValidationInputAccessor final : public graph::ITensorAccessor
 public:
     /** Constructor
      *
-     * @param[in] image_list  File containing all the images to validate
-     * @param[in] images_path Path to images.
-     * @param[in] bgr         (Optional) Fill the first plane with blue channel (default = false - RGB format)
-     * @param[in] start       (Optional) Start range
-     * @param[in] end         (Optional) End range
+     * @param[in] image_list   File containing all the images to validate
+     * @param[in] images_path  Path to images.
+     * @param[in] bgr          (Optional) Fill the first plane with blue channel (default = false - RGB format)
+     * @param[in] preprocessor (Optional) Image pre-processing object  (default = nullptr)
+     * @param[in] start        (Optional) Start range
+     * @param[in] end          (Optional) End range
      *
      * @note Range is defined as [start, end]
      */
-    ValidationInputAccessor(const std::string &image_list,
-                            std::string        images_path,
-                            bool               bgr   = true,
-                            unsigned int       start = 0,
-                            unsigned int       end   = 0);
+    ValidationInputAccessor(const std::string             &image_list,
+                            std::string                    images_path,
+                            std::unique_ptr<IPreprocessor> preprocessor = nullptr,
+                            bool                           bgr          = true,
+                            unsigned int                   start        = 0,
+                            unsigned int                   end          = 0);
 
     // Inherited methods overriden:
     bool access_tensor(ITensor &tensor) override;
 
 private:
-    std::string              _path;
-    std::vector<std::string> _images;
-    bool                     _bgr;
-    size_t                   _offset;
+    std::string                    _path;
+    std::vector<std::string>       _images;
+    std::unique_ptr<IPreprocessor> _preprocessor;
+    bool                           _bgr;
+    size_t                         _offset;
 };
 
 /** Output Accessor used for network validation */
@@ -210,7 +215,6 @@ public:
     /** Default Constructor
      *
      * @param[in]  image_list    File containing all the images and labels results
-     * @param[in]  top_n         (Optional) Top N accuracy (Defaults to 5)
      * @param[out] output_stream (Optional) Output stream (Defaults to the standard output stream)
      * @param[in]  start         (Optional) Start range
      * @param[in]  end           (Optional) End range
@@ -218,7 +222,6 @@ public:
      * @note Range is defined as [start, end]
      */
     ValidationOutputAccessor(const std::string &image_list,
-                             size_t             top_n         = 5,
                              std::ostream      &output_stream = std::cout,
                              unsigned int       start         = 0,
                              unsigned int       end           = 0);
@@ -237,13 +240,28 @@ private:
      */
     template <typename T>
     std::vector<size_t> access_predictions_tensor(ITensor &tensor);
+    /** Aggregates the results of a sample
+     *
+     * @param[in]     res              Vector containing the results of a graph
+     * @param[in,out] positive_samples Positive samples to be updated
+     * @param[in]     top_n            Top n accuracy to measure
+     * @param[in]     correct_label    Correct label of the current sample
+     */
+    void aggregate_sample(const std::vector<size_t> &res, size_t &positive_samples, size_t top_n, size_t correct_label);
+    /** Reports top N accuracy
+     *
+     * @param[in] top_n            Top N accuracy that is being reported
+     * @param[in] total_samples    Total number of samples
+     * @param[in] positive_samples Positive samples
+     */
+    void report_top_n(size_t top_n, size_t total_samples, size_t positive_samples);
 
 private:
     std::vector<int> _results;
     std::ostream    &_output_stream;
-    size_t           _top_n;
     size_t           _offset;
-    size_t           _positive_samples;
+    size_t           _positive_samples_top1;
+    size_t           _positive_samples_top5;
 };
 
 /** Result accessor class */
@@ -359,56 +377,78 @@ inline std::unique_ptr<graph::ITensorAccessor> get_weights_accessor(const std::s
     }
 }
 
-/** Generates appropriate input accessor according to the specified ppm_path
+/** Generates appropriate input accessor according to the specified graph parameters
  *
- * @note If ppm_path is empty will generate a DummyAccessor else will generate a PPMAccessor
- *
- * @param[in] ppm_path     Path to PPM file
- * @param[in] preprocessor Preproccessor object
- * @param[in] bgr          (Optional) Fill the first plane with blue channel (default = true)
+ * @param[in] graph_parameters Graph parameters
+ * @param[in] preprocessor     (Optional) Preproccessor object
+ * @param[in] bgr              (Optional) Fill the first plane with blue channel (default = true)
  *
  * @return An appropriate tensor accessor
  */
-inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const std::string             &ppm_path,
-                                                                  std::unique_ptr<IPreprocessor> preprocessor = nullptr,
-                                                                  bool                           bgr          = true)
+inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters,
+                                                                  std::unique_ptr<IPreprocessor>               preprocessor = nullptr,
+                                                                  bool                                         bgr          = true)
 {
-    if(ppm_path.empty())
+    if(!graph_parameters.validation_file.empty())
     {
-        return arm_compute::support::cpp14::make_unique<DummyAccessor>();
+        return arm_compute::support::cpp14::make_unique<ValidationInputAccessor>(graph_parameters.validation_file,
+                                                                                 graph_parameters.validation_path,
+                                                                                 std::move(preprocessor),
+                                                                                 bgr,
+                                                                                 graph_parameters.validation_range_start,
+                                                                                 graph_parameters.validation_range_end);
     }
     else
     {
-        if(arm_compute::utility::endswith(ppm_path, ".npy"))
+        const std::string &image_file = graph_parameters.image;
+        if(arm_compute::utility::endswith(image_file, ".npy"))
+        {
+            return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(image_file);
+        }
+        else if(arm_compute::utility::endswith(image_file, ".jpeg")
+                || arm_compute::utility::endswith(image_file, ".jpg")
+                || arm_compute::utility::endswith(image_file, ".ppm"))
         {
-            return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(ppm_path);
+            return arm_compute::support::cpp14::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor));
         }
         else
         {
-            return arm_compute::support::cpp14::make_unique<PPMAccessor>(ppm_path, bgr, std::move(preprocessor));
+            return arm_compute::support::cpp14::make_unique<DummyAccessor>();
         }
     }
 }
 
-/** Generates appropriate output accessor according to the specified labels_path
+/** Generates appropriate output accessor according to the specified graph parameters
  *
- * @note If labels_path is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor
+ * @note If the output accessor is requested to validate the graph then ValidationOutputAccessor is generated
+ *       else if output_accessor_file is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor
  *
- * @param[in]  labels_path   Path to labels text file
- * @param[in]  top_n         (Optional) Number of output classes to print
- * @param[out] output_stream (Optional) Output stream
+ * @param[in]  graph_parameters Graph parameters
+ * @param[in]  top_n            (Optional) Number of output classes to print (default = 5)
+ * @param[in]  is_validation    (Optional) Validation flag (default = false)
+ * @param[out] output_stream    (Optional) Output stream (default = std::cout)
  *
  * @return An appropriate tensor accessor
  */
-inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const std::string &labels_path, size_t top_n = 5, std::ostream &output_stream = std::cout)
+inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters,
+                                                                   size_t                                       top_n         = 5,
+                                                                   bool                                         is_validation = false,
+                                                                   std::ostream                                &output_stream = std::cout)
 {
-    if(labels_path.empty())
+    if(!graph_parameters.validation_file.empty())
+    {
+        return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file,
+                                                                                  output_stream,
+                                                                                  graph_parameters.validation_range_start,
+                                                                                  graph_parameters.validation_range_end);
+    }
+    else if(graph_parameters.labels.empty())
     {
         return arm_compute::support::cpp14::make_unique<DummyAccessor>(0);
     }
     else
     {
-        return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(labels_path, top_n, output_stream);
+        return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream);
     }
 }
 /** Generates appropriate npy output accessor according to the specified npy_path
diff --git a/utils/ImageLoader.h b/utils/ImageLoader.h
index edc89286a2..cc9619d3f1 100644
--- a/utils/ImageLoader.h
+++ b/utils/ImageLoader.h
@@ -486,6 +486,32 @@ private:
     bool _is_loaded;
     std::unique_ptr<uint8_t, malloc_deleter> _data;
 };
+
+/** Factory for generating appropriate image loader**/
+class ImageLoaderFactory final
+{
+public:
+    /** Create an image loader depending on the image type
+     *
+     * @param[in] filename File than needs to be loaded
+     *
+     * @return Image loader
+     */
+    static std::unique_ptr<IImageLoader> create(const std::string &filename)
+    {
+        ImageType type = arm_compute::utils::get_image_type_from_file(filename);
+        switch(type)
+        {
+            case ImageType::PPM:
+                return support::cpp14::make_unique<PPMLoader>();
+            case ImageType::JPEG:
+                return support::cpp14::make_unique<JPEGLoader>();
+            case ImageType::UNKNOWN:
+            default:
+                return nullptr;
+        }
+    }
+};
 } // namespace utils
 } // namespace arm_compute
 #endif /* __UTILS_IMAGE_LOADER_H__*/
diff --git a/utils/Utils.cpp b/utils/Utils.cpp
index a5c6a95a2a..133248e30c 100644
--- a/utils/Utils.cpp
+++ b/utils/Utils.cpp
@@ -74,7 +74,11 @@ int run_example(int argc, char **argv, std::unique_ptr<Example> example)
 
     try
     {
-        example->do_setup(argc, argv);
+        bool status = example->do_setup(argc, argv);
+        if(!status)
+        {
+            return 1;
+        }
         example->do_run();
         example->do_teardown();
 
@@ -141,6 +145,41 @@ void draw_detection_rectangle(ITensor *tensor, const DetectionWindow &rect, uint
     }
 }
 
+ImageType get_image_type_from_file(const std::string &filename)
+{
+    ImageType type = ImageType::UNKNOWN;
+
+    try
+    {
+        // Open file
+        std::ifstream fs;
+        fs.exceptions(std::ifstream::failbit | std::ifstream::badbit);
+        fs.open(filename, std::ios::in | std::ios::binary);
+
+        // Identify type from magic number
+        std::array<unsigned char, 2> magic_number{ { 0 } };
+        fs >> magic_number[0] >> magic_number[1];
+
+        // PPM check
+        if(static_cast<char>(magic_number[0]) == 'P' && static_cast<char>(magic_number[1]) == '6')
+        {
+            type = ImageType::PPM;
+        }
+        else if(magic_number[0] == 0xFF && magic_number[1] == 0xD8)
+        {
+            type = ImageType::JPEG;
+        }
+
+        fs.close();
+    }
+    catch(std::runtime_error &e)
+    {
+        ARM_COMPUTE_ERROR("Accessing %s: %s", filename.c_str(), e.what());
+    }
+
+    return type;
+}
+
 std::tuple<unsigned int, unsigned int, int> parse_ppm_header(std::ifstream &fs)
 {
     // Check the PPM magic number is valid
diff --git a/utils/Utils.h b/utils/Utils.h
index c18ad217a4..ced6b147f1 100644
--- a/utils/Utils.h
+++ b/utils/Utils.h
@@ -55,6 +55,14 @@ namespace arm_compute
 {
 namespace utils
 {
+/** Supported image types */
+enum class ImageType
+{
+    UNKNOWN,
+    PPM,
+    JPEG
+};
+
 /** Abstract Example class.
  *
  * All examples have to inherit from this class.
@@ -66,8 +74,13 @@ public:
      *
      * @param[in] argc Argument count.
      * @param[in] argv Argument values.
+     *
+     * @return True in case of no errors in setup else false
      */
-    virtual void do_setup(int argc, char **argv) {};
+    virtual bool do_setup(int argc, char **argv)
+    {
+        return true;
+    };
     /** Run the example. */
     virtual void do_run() {};
     /** Teardown the example. */
@@ -101,6 +114,14 @@ int run_example(int argc, char **argv)
  */
 void draw_detection_rectangle(arm_compute::ITensor *tensor, const arm_compute::DetectionWindow &rect, uint8_t r, uint8_t g, uint8_t b);
 
+/** Gets image type given a file
+ *
+ * @param[in] filename File to identify its image type
+ *
+ * @return Image type
+ */
+ImageType get_image_type_from_file(const std::string &filename);
+
 /** Parse the ppm header from an input file stream. At the end of the execution,
  *  the file position pointer will be located at the first pixel stored in the ppm file
  *
@@ -167,7 +188,7 @@ inline std::string get_typestring(DataType data_type)
         case DataType::SIZET:
             return endianness + "u" + support::cpp11::to_string(sizeof(size_t));
         default:
-            ARM_COMPUTE_ERROR("NOT SUPPORTED!");
+            ARM_COMPUTE_ERROR("Data type not supported");
     }
 }
 
diff --git a/tests/framework/command_line/CommandLineOptions.h b/utils/command_line/CommandLineOptions.h
index cb4b794a3e..8f82815020 100644
--- a/tests/framework/command_line/CommandLineOptions.h
+++ b/utils/command_line/CommandLineOptions.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_COMMANDLINEOPTIONS
-#define ARM_COMPUTE_TEST_COMMANDLINEOPTIONS
+#ifndef ARM_COMPUTE_UTILS_COMMANDLINEOPTIONS
+#define ARM_COMPUTE_UTILS_COMMANDLINEOPTIONS
 
 #include "EnumListOption.h"
 #include "EnumOption.h"
@@ -30,4 +30,4 @@
 #include "Option.h"
 #include "ToggleOption.h"
 
-#endif /* ARM_COMPUTE_TEST_COMMANDLINEOPTIONS */
+#endif /* ARM_COMPUTE_UTILS_COMMANDLINEOPTIONS */
diff --git a/tests/framework/command_line/CommandLineParser.cpp b/utils/command_line/CommandLineParser.h
index 09b466ce84..06c4bf5e2f 100644
--- a/tests/framework/command_line/CommandLineParser.cpp
+++ b/utils/command_line/CommandLineParser.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,18 +21,99 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#include "CommandLineParser.h"
+#ifndef ARM_COMPUTE_UTILS_COMMANDLINEPARSER
+#define ARM_COMPUTE_UTILS_COMMANDLINEPARSER
+
+#include "Option.h"
+#include "arm_compute/core/utils/misc/Utility.h"
+#include "support/ToolchainSupport.h"
 
 #include <iostream>
+#include <map>
+#include <memory>
 #include <regex>
+#include <string>
+#include <utility>
+#include <vector>
 
 namespace arm_compute
 {
-namespace test
+namespace utils
+{
+/** Class to parse command line arguments. */
+class CommandLineParser final
 {
-namespace framework
+public:
+    /** Default constructor. */
+    CommandLineParser() = default;
+
+    /** Function to add a new option to the parser.
+     *
+     * @param[in] name Name of the option. Will be available under --name=VALUE.
+     * @param[in] args Option specific configuration arguments.
+     *
+     * @return Pointer to the option. The option is owned by the parser.
+     */
+    template <typename T, typename... As>
+    T *add_option(const std::string &name, As &&... args);
+
+    /** Function to add a new positional argument to the parser.
+     *
+     * @param[in] args Option specific configuration arguments.
+     *
+     * @return Pointer to the option. The option is owned by the parser.
+     */
+    template <typename T, typename... As>
+    T *add_positional_option(As &&... args);
+
+    /** Parses the command line arguments and updates the options accordingly.
+     *
+     * @param[in] argc Number of arguments.
+     * @param[in] argv Arguments.
+     */
+    void parse(int argc, char **argv);
+
+    /** Validates the previously parsed command line arguments.
+     *
+     * Validation fails if not all required options are provided. Additionally
+     * warnings are generated for options that have illegal values or unknown
+     * options.
+     *
+     * @return True if all required options have been provided.
+     */
+    bool validate() const;
+
+    /** Prints a help message for all configured options.
+     *
+     * @param[in] program_name Name of the program to be used in the help message.
+     */
+    void print_help(const std::string &program_name) const;
+
+private:
+    using OptionsMap              = std::map<std::string, std::unique_ptr<Option>>;
+    using PositionalOptionsVector = std::vector<std::unique_ptr<Option>>;
+
+    OptionsMap               _options{};
+    PositionalOptionsVector  _positional_options{};
+    std::vector<std::string> _unknown_options{};
+    std::vector<std::string> _invalid_options{};
+};
+
+template <typename T, typename... As>
+inline T *CommandLineParser::add_option(const std::string &name, As &&... args)
 {
-void CommandLineParser::parse(int argc, char **argv)
+    auto result = _options.emplace(name, support::cpp14::make_unique<T>(name, std::forward<As>(args)...));
+    return static_cast<T *>(result.first->second.get());
+}
+
+template <typename T, typename... As>
+inline T *CommandLineParser::add_positional_option(As &&... args)
+{
+    _positional_options.emplace_back(support::cpp14::make_unique<T>(std::forward<As>(args)...));
+    return static_cast<T *>(_positional_options.back().get());
+}
+
+inline void CommandLineParser::parse(int argc, char **argv)
 {
     const std::regex option_regex{ "--((?:no-)?)([^=]+)(?:=(.*))?" };
 
@@ -60,7 +141,7 @@ void CommandLineParser::parse(int argc, char **argv)
         int         equal_sign = mixed_case_opt.find('=');
         int         pos        = (equal_sign == -1) ? strlen(argv[i]) : equal_sign;
 
-        const std::string option = tolower(mixed_case_opt.substr(0, pos)) + mixed_case_opt.substr(pos);
+        const std::string option = arm_compute::utility::tolower(mixed_case_opt.substr(0, pos)) + mixed_case_opt.substr(pos);
         std::smatch       option_matches;
 
         if(std::regex_match(option, option_matches, option_regex))
@@ -98,7 +179,7 @@ void CommandLineParser::parse(int argc, char **argv)
     }
 }
 
-bool CommandLineParser::validate() const
+inline bool CommandLineParser::validate() const
 {
     bool is_valid = true;
 
@@ -133,7 +214,7 @@ bool CommandLineParser::validate() const
     return is_valid;
 }
 
-void CommandLineParser::print_help(const std::string &program_name) const
+inline void CommandLineParser::print_help(const std::string &program_name) const
 {
     std::cout << "usage: " << program_name << " \n";
 
@@ -148,6 +229,6 @@ void CommandLineParser::print_help(const std::string &program_name) const
         std::cout << option->name() << "\n";
     }
 }
-} // namespace framework
-} // namespace test
+} // namespace utils
 } // namespace arm_compute
+#endif /* ARM_COMPUTE_UTILS_COMMANDLINEPARSER */
diff --git a/tests/framework/command_line/EnumListOption.h b/utils/command_line/EnumListOption.h
index 39006d86b9..834becbaef 100644
--- a/tests/framework/command_line/EnumListOption.h
+++ b/utils/command_line/EnumListOption.h
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_ENUMLISTOPTION
-#define ARM_COMPUTE_TEST_ENUMLISTOPTION
+#ifndef ARM_COMPUTE_UTILS_ENUMLISTOPTION
+#define ARM_COMPUTE_UTILS_ENUMLISTOPTION
 
 #include "Option.h"
 
@@ -35,9 +35,7 @@
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Implementation of an option that accepts any number of values from a fixed set. */
 template <typename T>
@@ -147,7 +145,6 @@ inline const std::vector<T> &EnumListOption<T>::value() const
 {
     return _values;
 }
-} // namespace framework
-} // namespace test
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_ENUMLISTOPTION */
+#endif /* ARM_COMPUTE_UTILS_ENUMLISTOPTION */
diff --git a/tests/framework/command_line/EnumOption.h b/utils/command_line/EnumOption.h
index 14d61859ae..b775db23fb 100644
--- a/tests/framework/command_line/EnumOption.h
+++ b/utils/command_line/EnumOption.h
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_ENUMOPTION
-#define ARM_COMPUTE_TEST_ENUMOPTION
+#ifndef ARM_COMPUTE_UTILS_ENUMOPTION
+#define ARM_COMPUTE_UTILS_ENUMOPTION
 
 #include "SimpleOption.h"
 
@@ -33,9 +33,7 @@
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Implementation of a simple option that accepts a value from a fixed set. */
 template <typename T>
@@ -133,7 +131,6 @@ inline const T &EnumOption<T>::value() const
 {
     return this->_value;
 }
-} // namespace framework
-} // namespace test
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_ENUMOPTION */
+#endif /* ARM_COMPUTE_UTILS_ENUMOPTION */
diff --git a/tests/framework/command_line/ListOption.h b/utils/command_line/ListOption.h
index 07184e8e3b..209a85d968 100644
--- a/tests/framework/command_line/ListOption.h
+++ b/utils/command_line/ListOption.h
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_LISTOPTION
-#define ARM_COMPUTE_TEST_LISTOPTION
+#ifndef ARM_COMPUTE_UTILS_LISTOPTION
+#define ARM_COMPUTE_UTILS_LISTOPTION
 
 #include "Option.h"
 
@@ -34,9 +34,7 @@
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Implementation of an option that accepts any number of values. */
 template <typename T>
@@ -115,7 +113,6 @@ inline const std::vector<T> &ListOption<T>::value() const
 {
     return _values;
 }
-} // namespace framework
-} // namespace test
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_LISTOPTION */
+#endif /* ARM_COMPUTE_UTILS_LISTOPTION */
diff --git a/tests/framework/command_line/Option.h b/utils/command_line/Option.h
index 25cf492b86..b9469a5cc3 100644
--- a/tests/framework/command_line/Option.h
+++ b/utils/command_line/Option.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,16 +21,14 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_OPTIONBASE
-#define ARM_COMPUTE_TEST_OPTIONBASE
+#ifndef ARM_COMPUTE_UTILS_OPTIONBASE
+#define ARM_COMPUTE_UTILS_OPTIONBASE
 
 #include <string>
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Abstract base class for a command line option. */
 class Option
@@ -103,7 +101,41 @@ protected:
     bool        _is_set{ false };
     std::string _help{};
 };
-} // namespace framework
-} // namespace test
+
+inline Option::Option(std::string name)
+    : _name{ std::move(name) }
+{
+}
+
+inline Option::Option(std::string name, bool is_required, bool is_set)
+    : _name{ std::move(name) }, _is_required{ is_required }, _is_set{ is_set }
+{
+}
+
+inline std::string Option::name() const
+{
+    return _name;
+}
+
+inline void Option::set_required(bool is_required)
+{
+    _is_required = is_required;
+}
+
+inline void Option::set_help(std::string help)
+{
+    _help = std::move(help);
+}
+
+inline bool Option::is_required() const
+{
+    return _is_required;
+}
+
+inline bool Option::is_set() const
+{
+    return _is_set;
+}
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_OPTIONBASE */
+#endif /* ARM_COMPUTE_UTILS_OPTIONBASE */
diff --git a/tests/framework/command_line/SimpleOption.h b/utils/command_line/SimpleOption.h
index d02778e781..543759259a 100644
--- a/tests/framework/command_line/SimpleOption.h
+++ b/utils/command_line/SimpleOption.h
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_SIMPLEOPTION
-#define ARM_COMPUTE_TEST_SIMPLEOPTION
+#ifndef ARM_COMPUTE_UTILS_SIMPLEOPTION
+#define ARM_COMPUTE_UTILS_SIMPLEOPTION
 
 #include "Option.h"
 
@@ -32,9 +32,7 @@
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Implementation of an option that accepts a single value. */
 template <typename T>
@@ -115,7 +113,6 @@ inline const T &SimpleOption<T>::value() const
 {
     return _value;
 }
-} // namespace framework
-} // namespace test
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_SIMPLEOPTION */
+#endif /* ARM_COMPUTE_UTILS_SIMPLEOPTION */
diff --git a/tests/framework/command_line/ToggleOption.h b/utils/command_line/ToggleOption.h
index c440c0ee87..b1d2a32c64 100644
--- a/tests/framework/command_line/ToggleOption.h
+++ b/utils/command_line/ToggleOption.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -21,8 +21,8 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#ifndef ARM_COMPUTE_TEST_TOGGLEOPTION
-#define ARM_COMPUTE_TEST_TOGGLEOPTION
+#ifndef ARM_COMPUTE_UTILS_TOGGLEOPTION
+#define ARM_COMPUTE_UTILS_TOGGLEOPTION
 
 #include "SimpleOption.h"
 
@@ -30,9 +30,7 @@
 
 namespace arm_compute
 {
-namespace test
-{
-namespace framework
+namespace utils
 {
 /** Implementation of an option that can be either true or false. */
 class ToggleOption : public SimpleOption<bool>
@@ -50,7 +48,35 @@ public:
     bool parse(std::string value) override;
     std::string help() const override;
 };
-} // namespace framework
-} // namespace test
+
+inline ToggleOption::ToggleOption(std::string name, bool default_value)
+    : SimpleOption<bool>
+{
+    std::move(name), default_value
+}
+{
+}
+
+inline bool ToggleOption::parse(std::string value)
+{
+    if(value == "true")
+    {
+        _value  = true;
+        _is_set = true;
+    }
+    else if(value == "false")
+    {
+        _value  = false;
+        _is_set = true;
+    }
+
+    return _is_set;
+}
+
+inline std::string ToggleOption::help() const
+{
+    return "--" + name() + ", --no-" + name() + " - " + _help;
+}
+} // namespace utils
 } // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_TOGGLEOPTION */
+#endif /* ARM_COMPUTE_UTILS_TOGGLEOPTION */