From 7bfd38a721360183f3392f9ab35db18a0dd7fef8 Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Fri, 19 Aug 2022 15:23:36 +0100 Subject: Update Doxygen for 22.08 Release Signed-off-by: Nikhil Raj Change-Id: I4789fe868e0492839be1482e5cee3642ed90d756 --- ...onvert_constants_half_to_float_tests_8cpp.xhtml | 169 +++++++++++++++++++++ 1 file changed, 169 insertions(+) create mode 100644 22.08/_convert_constants_half_to_float_tests_8cpp.xhtml (limited to '22.08/_convert_constants_half_to_float_tests_8cpp.xhtml') diff --git a/22.08/_convert_constants_half_to_float_tests_8cpp.xhtml b/22.08/_convert_constants_half_to_float_tests_8cpp.xhtml new file mode 100644 index 0000000000..8e1d4878e4 --- /dev/null +++ b/22.08/_convert_constants_half_to_float_tests_8cpp.xhtml @@ -0,0 +1,169 @@ + + + + + + + + + + + + + +ArmNN: src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp File Reference + + + + + + + + + + + + + + + + +
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ConvertConstantsHalfToFloatTests.cpp File Reference
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#include <TestUtils.hpp>
+#include <Optimizer.hpp>
+#include <doctest/doctest.h>
+
+

Go to the source code of this file.

+ + + + +

+Functions

 TEST_SUITE ("Optimizer")
 
+

Function Documentation

+ +

◆ TEST_SUITE()

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+ + + + + + + + +
TEST_SUITE ("Optimizer" )
+
+ +

Definition at line 12 of file ConvertConstantsHalfToFloatTests.cpp.

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References Graph::AddLayer(), OutputSlot::Connect(), FloatingPointConverter::ConvertFloat32To16(), armnn::Float16, armnn::Float32, Layer::GetOutputSlot(), FullyConnectedLayer::m_Weight, armnn::MakeOptimizations(), Optimizer::Pass(), and OutputSlot::SetTensorInfo().

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13 {
14 using namespace armnn::optimizations;
15 
16 TEST_CASE("ConvertConstantsHalfToFloatTest")
17 {
18  armnn::Graph graph;
19 
20  const armnn::TensorInfo info({ 1, 1, 1, 2 }, armnn::DataType::Float32);
21 
22  // Create the half precision input data
23  unsigned int dims[] = { 4, 1, 1, 1 };
24  std::vector<float> convWeightsData{ 1.f, 2.f, 3.f, 4.f };
25  std::vector<uint16_t> halfWeights(4);
26  armnnUtils::FloatingPointConverter::ConvertFloat32To16(convWeightsData.data(), convWeightsData.size(),
27  halfWeights.data());
28  armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float16, 0.0f, 0, true), halfWeights);
29 
30  //Create the simple test network
31  auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
32  input->GetOutputSlot().SetTensorInfo(info);
33 
34  auto fc = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
35  fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
36  fc->GetOutputSlot().SetTensorInfo(info);
37 
38  auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
39 
40  //Connect up the layers
41  input->GetOutputSlot().Connect(fc->GetInputSlot(0));
42  fc->GetOutputSlot().Connect(output->GetInputSlot(0));
43 
44  //Test the tensor info is correct.
45  CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float16);
46 
47  // Run the optimizer
48  armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsHalfToFloat()));
49 
50  //Test the tensor info is correct.
51  CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
52 
53  // Now test the data matches float32 data
54  const float* data = fc->m_Weight->GetConstTensor<float>();
55  CHECK(1.0f == data[0]);
56  CHECK(2.0f == data[1]);
57  CHECK(3.0f == data[2]);
58  CHECK(4.0f == data[3]);
59 }
60 
61 }
armnn::MakeOptimizations
Optimizer::Optimizations MakeOptimizations(Args &&... args)
Definition: Optimizer.hpp:43
+ + +
armnn::Graph::AddLayer
LayerT * AddLayer(Args &&... args)
Adds a new layer, of type LayerType, to the graph constructed with the arguments passed.
Definition: Graph.hpp:456
+
armnn::OutputSlot::Connect
int Connect(InputSlot &destination)
Definition: Layer.cpp:112
+
armnn::Optimizer::Pass
static void Pass(Graph &graph, const Optimizations &optimizations)
Definition: Optimizer.cpp:16
+
armnn::OutputLayer
A layer user-provided data can be bound to (e.g. inputs, outputs).
Definition: OutputLayer.hpp:13
+
armnn::FullyConnectedLayer
This layer represents a fully connected operation.
Definition: FullyConnectedLayer.hpp:15
+
armnn::FullyConnectedLayer::m_Weight
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store Weight values.
Definition: FullyConnectedLayer.hpp:20
+
armnn::FullyConnectedDescriptor
A FullyConnectedDescriptor for the FullyConnectedLayer.
Definition: Descriptors.hpp:468
+
armnnUtils::FloatingPointConverter::ConvertFloat32To16
static void ConvertFloat32To16(const float *srcFloat32Buffer, size_t numElements, void *dstFloat16Buffer)
Converts a buffer of FP32 values to FP16, and stores in the given dstFloat16Buffer.
Definition: FloatingPointConverter.cpp:16
+
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:327
+ + +
armnn::optimizations::ConvertConstantsHalfToFloat
ConvertConstants< Float16ToFloat32, IsFloat32Layer > ConvertConstantsHalfToFloat
Definition: ConvertConstants.hpp:152
+ +
armnn::InputLayer
A layer user-provided data can be bound to (e.g. inputs, outputs).
Definition: InputLayer.hpp:13
+
armnn::OutputSlot::SetTensorInfo
void SetTensorInfo(const TensorInfo &tensorInfo) override
Definition: Layer.cpp:87
+
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:326
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