COMPMID-915: Create ResNet50 example

ResidualLayer node (COMPMID-916) also created as required for the ResNet
architecture.

Change-Id: I4fb4d2e08a8d3ce206f96f7946f5afc3e244676a
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/121185
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

4 files changed, 258 insertions, 2 deletions

diff --git a/src/graph/Graph.cpp b/src/graph/Graph.cpp
index 98d95904dc..b6c6822c36 100644
--- a/src/graph/Graph.cpp
+++ b/src/graph/Graph.cpp
@@ -77,6 +77,7 @@ Graph::~Graph() //NOLINT
 Graph::Graph()
     : _pimpl{ new Private() }
 {
+    graph_init();
 }
 
 void Graph::graph_init(const bool use_cl_tuner)
diff --git a/src/graph/nodes/ResidualLayer.cpp b/src/graph/nodes/ResidualLayer.cpp
new file mode 100644
index 0000000000..87404f9e1f
--- /dev/null
+++ b/src/graph/nodes/ResidualLayer.cpp
@@ -0,0 +1,199 @@
+/*
+ * 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/nodes/ResidualLayer.h"
+
+#include "arm_compute/graph/Error.h"
+#include "arm_compute/graph/Graph.h"
+#include "arm_compute/graph/NodeContext.h"
+#include "arm_compute/graph/OperationRegistry.h"
+#include "arm_compute/graph/SubGraph.h"
+#include "arm_compute/graph/Tensor.h"
+#include "arm_compute/runtime/IFunction.h"
+#include "support/ToolchainSupport.h"
+#include "utils/Utils.h"
+
+#include <memory>
+#include <tuple>
+#include <vector>
+
+using namespace arm_compute::graph;
+
+/** Residual function */
+class ResidualFunction final : public arm_compute::IFunction
+{
+public:
+    /** Default Constructor */
+    ResidualFunction(GraphContext &ctx, ITensorObject *output)
+        : _ctx(ctx), _input(nullptr), _output(output), _func(nullptr), _graphs(), _graph_outputs()
+    {
+    }
+
+    /** Prevent instances from being copy constructed */
+    ResidualFunction(const ResidualFunction &) = delete;
+    /** Prevent instances from being copy assigned */
+    const ResidualFunction &operator=(const ResidualFunction &) = delete;
+    /** Prevent instances from being move constructed */
+    ResidualFunction(ResidualFunction &&) = delete;
+    /** Prevent instances from being move assigned */
+    ResidualFunction &operator=(ResidualFunction &&) = delete;
+    /** Default destructor */
+    ~ResidualFunction() override = default;
+
+    /** Set the input (when using only one sub graph)
+     *
+     * @param[in] input Input to set
+     */
+    void set_input(std::unique_ptr<ITensorObject> input)
+    {
+        _input = std::move(input);
+    }
+
+    /** Registers graph to be executed by the residual function
+     *
+     * @param[in] graph  Graph to register
+     * @param[in] output Output to register
+     */
+    void register_graph(std::unique_ptr<Graph> graph, std::unique_ptr<ITensorObject> output)
+    {
+        _graphs.push_back(std::move(graph));
+        _graph_outputs.push_back(std::move(output));
+    }
+
+    /** Configure the function */
+    void configure()
+    {
+        ARM_COMPUTE_ERROR_ON(_graphs.size() < 1 || _graphs.size() > 2);
+        TargetHint target_hint = _ctx.hints().target_hint();
+
+        // Create node context
+        NodeContext node_ctx(OperationType::ArithmeticAddition);
+        node_ctx.set_target(target_hint);
+
+        if(_graphs.size() == 1)
+        {
+            arm_compute::ITensor *in = _input->tensor();
+            node_ctx.add_input(in);
+        }
+
+        for(auto &o : _graph_outputs)
+        {
+            arm_compute::ITensor *in = o->tensor();
+            node_ctx.add_input(in);
+        }
+
+        arm_compute::ITensor *out = _output->tensor();
+        auto_init_if_empty(*out->info(), *_graph_outputs[0]->tensor()->info());
+        node_ctx.add_output(out);
+
+        _func = OperationRegistry::get().find_operation(OperationType::ArithmeticAddition, target_hint)->configure(node_ctx);
+
+        for(auto &o : _graph_outputs)
+        {
+            o->allocate();
+        }
+    }
+
+    // Inherited methods overriden:
+    void run() override
+    {
+        ARM_COMPUTE_ERROR_ON(_graphs.size() < 1 || _graphs.size() > 2);
+
+        for(auto &g : _graphs)
+        {
+            ARM_COMPUTE_ERROR_ON(g.get() == nullptr);
+            g->run();
+        }
+
+        _func->run();
+    }
+
+private:
+    GraphContext                                _ctx;
+    std::unique_ptr<ITensorObject>              _input;
+    ITensorObject                              *_output;
+    std::unique_ptr<arm_compute::IFunction>     _func;
+    std::vector<std::unique_ptr<Graph>>         _graphs;
+    std::vector<std::unique_ptr<ITensorObject>> _graph_outputs;
+};
+
+std::unique_ptr<arm_compute::IFunction> ResidualLayer::instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output)
+{
+    ARM_COMPUTE_ERROR_ON_UNALLOCATED_TENSOR_OBJECT(input, output);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<Tensor *>(input) == nullptr);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<Tensor *>(output) == nullptr);
+
+    // Create residual function
+    auto func = arm_compute::support::cpp14::make_unique<ResidualFunction>(ctx, output);
+
+    if(_sub_graphs.size() == 1)
+    {
+        std::unique_ptr<ITensorObject> original_in;
+        original_in = arm_compute::support::cpp14::make_unique<SubTensor>(*dynamic_cast<Tensor *>(input),
+                                                                          input->tensor()->info()->tensor_shape(),
+                                                                          Coordinates());
+        func->set_input(std::move(original_in));
+    }
+
+    // Constuct all sub-graphs given the input/output
+    for(auto &sg : _sub_graphs)
+    {
+        ARM_COMPUTE_ERROR_ON(sg.get() == nullptr);
+
+        // IO buffers
+        std::unique_ptr<ITensorObject> in;
+        std::unique_ptr<ITensorObject> out;
+        std::unique_ptr<ITensorObject> func_in;
+
+        // Create input sub-tensor
+        if(!sg->has_input())
+        {
+            in = arm_compute::support::cpp14::make_unique<SubTensor>(*dynamic_cast<Tensor *>(input),
+                                                                     input->tensor()->info()->tensor_shape(),
+                                                                     Coordinates());
+        }
+
+        // Create output sub-tensor
+        if(!sg->has_output())
+        {
+            ITensorInfo *info = input->tensor()->info();
+            func_in           = arm_compute::support::cpp14::make_unique<Tensor>(TensorInfo(info->num_channels(), info->data_type(), info->fixed_point_position()));
+            func_in->set_target(ctx.hints().target_hint());
+            out = arm_compute::support::cpp14::make_unique<SubTensor>(func_in->tensor(),
+                                                                      TensorShape(),
+                                                                      Coordinates(0, 0, 0),
+                                                                      func_in->target(),
+                                                                      true);
+        }
+
+        // Construct sub_graph
+        auto g = sg->construct(ctx, std::move(in), std::move(out));
+
+        // Register graph to function
+        func->register_graph(std::move(g), std::move(func_in));
+    }
+
+    func->configure();
+
+    return std::move(func);
+}
diff --git a/src/graph/operations/CLSimpleOperations.cpp b/src/graph/operations/CLSimpleOperations.cpp
index 94e3fe15f7..fe56122009 100644
--- a/src/graph/operations/CLSimpleOperations.cpp
+++ b/src/graph/operations/CLSimpleOperations.cpp
@@ -66,6 +66,34 @@ REGISTER_SIMPLE_OPERATION(CLActivationLayerOperation, OPENCL, OperationType::Act
     return std::move(activation);
 }
 
+/* Arithmetic addition */
+REGISTER_SIMPLE_OPERATION(CLArithmeticAdditionOperation, OPENCL, OperationType::ArithmeticAddition)
+{
+    ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2);
+    ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0)) == nullptr);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1)) == nullptr);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+    // Extract IO and info
+    auto *in1 = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+    auto *in2 = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1));
+    auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+    auto addition = arm_compute::support::cpp14::make_unique<arm_compute::CLArithmeticAddition>();
+    addition->configure(in1, in2, out, ConvertPolicy::SATURATE);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLArithmeticAddition"
+                               << " Data Type: " << in1->info()->data_type()
+                               << " Input 1 shape: " << in1->info()->tensor_shape()
+                               << " Input 2 shape: " << in2->info()->tensor_shape()
+                               << " Output shape: " << out->info()->tensor_shape()
+                               << std::endl);
+
+    return std::move(addition);
+}
+
 /* Batch Normalization Layer */
 REGISTER_SIMPLE_OPERATION(CLBatchNormalizationLayerOperation, OPENCL, OperationType::BatchNormalizationLayer)
 {
@@ -464,4 +492,4 @@ REGISTER_SIMPLE_OPERATION(CLSoftmaxLayerOperation, OPENCL, OperationType::Softma
                                << std::endl);
 
     return std::move(smx);
-}
\ No newline at end of file
+}
diff --git a/src/graph/operations/NESimpleOperations.cpp b/src/graph/operations/NESimpleOperations.cpp
index 265bed6b7a..4154b9a59c 100644
--- a/src/graph/operations/NESimpleOperations.cpp
+++ b/src/graph/operations/NESimpleOperations.cpp
@@ -66,6 +66,34 @@ REGISTER_SIMPLE_OPERATION(NEActivationLayerOperation, NEON, OperationType::Activ
     return std::move(activation);
 }
 
+/* Arithmetic addition */
+REGISTER_SIMPLE_OPERATION(NEArithmeticAdditionOperation, NEON, OperationType::ArithmeticAddition)
+{
+    ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 2);
+    ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(1)) == nullptr);
+    ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr);
+
+    // Extract IO and info
+    auto *in1 = dynamic_cast<arm_compute::ITensor *>(ctx.input(0));
+    auto *in2 = dynamic_cast<arm_compute::ITensor *>(ctx.input(1));
+    auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0));
+
+    auto addition = arm_compute::support::cpp14::make_unique<arm_compute::NEArithmeticAddition>();
+    addition->configure(in1, in2, out, ConvertPolicy::SATURATE);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEArithmeticAddition"
+                               << " Data Type: " << in1->info()->data_type()
+                               << " Input 1 shape: " << in1->info()->tensor_shape()
+                               << " Input 2 shape: " << in2->info()->tensor_shape()
+                               << " Output shape: " << out->info()->tensor_shape()
+                               << std::endl);
+
+    return std::move(addition);
+}
+
 /* Batch Normalization Layer */
 REGISTER_SIMPLE_OPERATION(NEBatchNormalizationLayerOperation, NEON, OperationType::BatchNormalizationLayer)
 {
@@ -464,4 +492,4 @@ REGISTER_SIMPLE_OPERATION(NESoftmaxLayerOperation, NEON, OperationType::SoftmaxL
                                << std::endl);
 
     return std::move(smx);
-}
\ No newline at end of file
+}