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author | Cathal Corbett <cathal.corbett@arm.com> | 2021-10-22 11:12:07 +0100 |
---|---|---|
committer | David Monahan <david.monahan@arm.com> | 2021-11-08 19:05:11 +0000 |
commit | 5b8093c17044e8eaaaa42d96ba4902dee5791be4 (patch) | |
tree | 7f49f91e76f171041fe51c2c078b9271aa220b48 /src/armnn/test/ShapeInferenceTests.cpp | |
parent | d69cb904415621b066599dc20164bdb71558dc14 (diff) | |
download | armnn-5b8093c17044e8eaaaa42d96ba4902dee5791be4.tar.gz |
IVGCVSW-6420: Constant flag in tensor info is not set correctly
!android-nn-driver:6532
!armnn-internal-tests:372451
* Made fix to 2 out of 3 ConstTensor() constructors in Tensor.hpp to
throw InvalidArgumentException when TensorInfo isConstant parameter
is false.
* Added new ConstTensor() constructor in Tensor.cpp to accept vector<>.data()
using template<typename MemoryType>.
* Fixed runtime->GetOutputTensorInfo()/GetInputTensorInfo() methods and
called submethods to return TensorInfo& rather than TensorInfo.
* Fixed all failing unit tests for CpuRef/CpuAcc/GpuAcc to ensure any
ConstTensor created has it's TensorInfo isConstant set to true.
* Added unit tests in TensorTest.cpp to ensure ConstTensor constructors
throw InvalidArgumentException when TensorInfo isConstat parameter is
false.
* Added unit test to ensure an empty ConstTensor constructor will set
TensorInfo isConatant to true.
* Indentation fixes.
* Fix to arm_tensor.i to add isConstant parameter to TensorInfo
constructor. Added methods IsConstant() and SetConstant().
* Fix to const_tensor.py to throw ValueError when TensorInfo
isConstant is set to false when constructing a ConstTensor.
* Fixed PyArmnn unit tests to set TensorInfo isConstant to
True when ConstTensor is used.
* Added unit tests in test_const_tensor.py to ensure ConstTensor
constructors throw ValueError when TensorInfo isConstat parameter
is false.
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I44e440dd0422c366d31bbdbc77ad2b4db0bde148
Diffstat (limited to 'src/armnn/test/ShapeInferenceTests.cpp')
-rw-r--r-- | src/armnn/test/ShapeInferenceTests.cpp | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/src/armnn/test/ShapeInferenceTests.cpp b/src/armnn/test/ShapeInferenceTests.cpp index d3c928fec1..f808a0e349 100644 --- a/src/armnn/test/ShapeInferenceTests.cpp +++ b/src/armnn/test/ShapeInferenceTests.cpp @@ -233,14 +233,14 @@ TEST_CASE("ConcatTest") CreateGraphAndRunTest<ConcatLayer>({{ 1, 2, 1 }, { 1, 2, 1 }}, {{ 2, 2, 1 }}, descriptor, "concat"); } -TEST_CASE("ConstantTesst") +TEST_CASE("ConstantTest") { Graph graph; TensorShape outputShape{ 1, 1, 3, 3 }; auto layer = BuildGraph<ConstantLayer>(&graph, {}, "constant"); const float Datum = 0.0f; - ConstTensor output0({outputShape, DataType::Float32}, &Datum); + ConstTensor output0({outputShape, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_LayerOutput = std::make_unique<ScopedTensorHandle>(output0); layer->GetOutputSlot(0).SetTensorInfo({{1, 1, 3, 3}, DataType::Float32}); @@ -294,7 +294,7 @@ TEST_CASE("Convolution2dTest") "conv2d"); const float Datum = 0.0f; - ConstTensor weights({{1, 1, 3, 3}, DataType::Float32}, &Datum); + ConstTensor weights({{1, 1, 3, 3}, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_Weight = std::make_unique<ScopedTensorHandle>(weights); RunShapeInferenceTest<Convolution2dLayer>(layer, {{ 1, 1, 4, 4 }}); @@ -339,7 +339,7 @@ TEST_CASE("DepthwiseConvolutionTest") "depthwiseconv2d"); const float Datum = 0.0f; - ConstTensor weights({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum); + ConstTensor weights({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_Weight = std::make_unique<ScopedTensorHandle>(weights); RunShapeInferenceTest<DepthwiseConvolution2dLayer>(layer, {{ 8, 18, 1, 2 }}); @@ -371,7 +371,7 @@ TEST_CASE("DetectionPostProcessTest") descriptor.m_ScaleW = 5.0; const float Datum = 0.0f; - ConstTensor anchorsTensor({{1, 1, 3, 3}, DataType::Float32}, &Datum); + ConstTensor anchorsTensor({{1, 1, 3, 3}, DataType::Float32, 0.0f, 0, true}, &Datum); Graph graph; @@ -460,7 +460,7 @@ TEST_CASE("LstmTest") auto layer = BuildGraph<LstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, "lstm"); float Datum = 0.0f; - ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum); + ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor); layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor); @@ -548,7 +548,7 @@ TEST_CASE("QLstmTest") auto layer = BuildGraph<QLstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, "qlstm"); float Datum = 0.0f; - ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum); + ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor); layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor); @@ -576,7 +576,7 @@ TEST_CASE("QuantizedLstmTest") auto layer = BuildGraph<QuantizedLstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, "quatizedlstm"); float Datum = 0.0f; - ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum); + ConstTensor constTensor({{ 2, 5, 3, 2 }, DataType::Float32, 0.0f, 0, true}, &Datum); layer->m_QuantizedLstmParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(constTensor); layer->m_QuantizedLstmParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(constTensor); |