IVGCVSW-4375 Add support for Transpose to optimizations

 * Changed some existing Permutation specific optimizations to also support Transpose
 * Added MoveTransposeUp optimization
 * Added TransposeAsReshape optimization
 * Added tests for Transpose optimizations
 * Added missing layer tests for Transpose

Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I20d099b284861402ae94aaa5dbf34907327a485f

1 files changed, 93 insertions, 0 deletions

diff --git a/src/armnn/test/optimizations/MoveTransposeUpTests.cpp b/src/armnn/test/optimizations/MoveTransposeUpTests.cpp
new file mode 100644
index 0000000000..e2fb3abffb
--- /dev/null
+++ b/src/armnn/test/optimizations/MoveTransposeUpTests.cpp
@@ -0,0 +1,93 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "../TestUtils.hpp"
+
+#include <Optimizer.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+BOOST_AUTO_TEST_SUITE(Optimizer)
+using namespace armnn::optimizations;
+
+BOOST_AUTO_TEST_CASE(MoveTransposeUpTest)
+{
+    const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);
+    const armnn::TensorInfo transposed({ 1, 3, 5, 2 }, armnn::DataType::Float32);
+
+    armnn::Graph graph;
+
+    armnn::LayerBindingId inputId = 0;
+
+    armnn::Layer* head = graph.AddLayer<armnn::OutputLayer>(0, "output");
+
+    std::string transposeLayerName = "original_transpose";
+
+    // Insert transpose
+    head = graph.InsertNewLayer<armnn::TransposeLayer>(head->GetInputSlot(0),
+                                                       armnn::TransposeDescriptor({ 0, 3, 1, 2 }),
+                                                       transposeLayerName.c_str());
+
+    head->GetOutputHandler().SetTensorInfo(transposed);
+
+    // Inserts layers that don't care about data format.
+    head = graph.InsertNewLayer<armnn::ActivationLayer>(head->GetInputSlot(0), armnn::ActivationDescriptor{}, "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    head = graph.InsertNewLayer<armnn::AdditionLayer>(head->GetInputSlot(0), "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    // Inserts input for 2nd input of Addition.
+    graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(1), inputId++, "")
+        ->GetOutputHandler()
+        .SetTensorInfo(info);
+
+    head = graph.InsertNewLayer<armnn::FakeQuantizationLayer>(head->GetInputSlot(0),
+                                                              armnn::FakeQuantizationDescriptor{}, "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    head = graph.InsertNewLayer<armnn::FloorLayer>(head->GetInputSlot(0), "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    head = graph.InsertNewLayer<armnn::MemCopyLayer>(head->GetInputSlot(0), "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    head = graph.InsertNewLayer<armnn::MultiplicationLayer>(head->GetInputSlot(0), "");
+    head->GetOutputHandler().SetTensorInfo(info);
+
+    // Inserts input for 2nd input of Multiplication.
+    graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(1), inputId++, "")
+        ->GetOutputHandler()
+        .SetTensorInfo(info);
+
+    // Inserts input.
+    graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(0), inputId++, "")
+        ->GetOutputHandler()
+        .SetTensorInfo(info);
+
+    BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+                             &IsLayerOfType<armnn::InputLayer>, &IsLayerOfType<armnn::InputLayer>,
+                             &IsLayerOfType<armnn::MultiplicationLayer>, &IsLayerOfType<armnn::MemCopyLayer>,
+                             &IsLayerOfType<armnn::FloorLayer>, &IsLayerOfType<armnn::FakeQuantizationLayer>,
+                             &IsLayerOfType<armnn::AdditionLayer>, &IsLayerOfType<armnn::ActivationLayer>,
+                             &IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::OutputLayer>));
+
+    armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(MoveTransposeUp()));
+
+    // The transpose is moved to the top. New transposes for layers with multiple inputs.
+    BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
+                             &IsLayerOfType<armnn::InputLayer>, &IsLayerOfType<armnn::InputLayer>,
+                             &IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::TransposeLayer>,
+                             &IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::MultiplicationLayer>,
+                             &IsLayerOfType<armnn::MemCopyLayer>, &IsLayerOfType<armnn::FloorLayer>,
+                             &IsLayerOfType<armnn::FakeQuantizationLayer>, &IsLayerOfType<armnn::AdditionLayer>,
+                             &IsLayerOfType<armnn::ActivationLayer>, &IsLayerOfType<armnn::OutputLayer>));
+
+    std::list<std::string> testRelatedLayers = { transposeLayerName };
+
+    BOOST_TEST(CheckRelatedLayers<armnn::TransposeLayer>(graph, testRelatedLayers));
+}
+
+BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file