diff options
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); |