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authorCathal Corbett <cathal.corbett@arm.com>2021-10-22 11:12:07 +0100
committerDavid Monahan <david.monahan@arm.com>2021-11-08 19:05:11 +0000
commit5b8093c17044e8eaaaa42d96ba4902dee5791be4 (patch)
tree7f49f91e76f171041fe51c2c078b9271aa220b48 /src/armnn/test/ShapeInferenceTests.cpp
parentd69cb904415621b066599dc20164bdb71558dc14 (diff)
downloadarmnn-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.cpp16
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);