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-rw-r--r--delegate/src/Comparison.hpp23
-rw-r--r--delegate/src/Control.hpp5
-rw-r--r--delegate/src/Convolution.hpp16
-rw-r--r--delegate/src/DelegateUtils.hpp79
-rw-r--r--delegate/src/ElementwiseBinary.hpp15
-rw-r--r--delegate/src/Gather.hpp6
-rw-r--r--delegate/src/GatherNd.hpp6
-rw-r--r--delegate/src/LogicalBinary.hpp22
-rw-r--r--delegate/src/test/ElementwiseBinaryTest.cpp6
-rw-r--r--include/armnnUtils/TensorUtils.hpp2
-rw-r--r--src/armnnUtils/TensorUtils.cpp25
-rw-r--r--src/armnnUtils/test/TensorUtilsTest.cpp85
12 files changed, 158 insertions, 132 deletions
diff --git a/delegate/src/Comparison.hpp b/delegate/src/Comparison.hpp
index 80354e835d..688f90c597 100644
--- a/delegate/src/Comparison.hpp
+++ b/delegate/src/Comparison.hpp
@@ -57,10 +57,17 @@ TfLiteStatus VisitComparisonOperator(DelegateData& delegateData,
return kTfLiteError;
}
- const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
- const armnn::TensorInfo& inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
+ armnn::TensorInfo inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
+ armnn::TensorInfo inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+ // Check if we need to expand the dims of any of the input tensor infos.
+ // This is required for a few of the backends.
+ if(inputTensorInfo0.GetNumDimensions() != inputTensorInfo1.GetNumDimensions())
+ {
+ ExpandTensorRankToEqual(inputTensorInfo0, inputTensorInfo1);
+ }
+
armnn::ComparisonOperation comparisonOperation = armnn::ComparisonOperation::Equal;
switch(tfLiteComparisonOperatorCode)
{
@@ -122,17 +129,7 @@ TfLiteStatus VisitComparisonOperator(DelegateData& delegateData,
return kTfLiteError;
}
- auto reshapeLayer = BroadcastTensor(inputTensorInfo0,
- inputTensorInfo1,
- comparisonLayer,
- tfLiteContext,
- tfLiteNode,
- delegateData);
- if (!reshapeLayer)
- {
- return kTfLiteError;
- }
- return kTfLiteOk;
+ return Connect(comparisonLayer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
diff --git a/delegate/src/Control.hpp b/delegate/src/Control.hpp
index 17f23d81ad..a3ea6e92a7 100644
--- a/delegate/src/Control.hpp
+++ b/delegate/src/Control.hpp
@@ -172,7 +172,10 @@ TfLiteStatus VisitConcatenationOperator(DelegateData& delegateData,
armnn::IOutputSlot& outputSlot = concatenationLayer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
- Connect(concatenationLayer, tfLiteNode, delegateData);
+ if(Connect(concatenationLayer, tfLiteNode, delegateData) != kTfLiteOk)
+ {
+ return kTfLiteError;
+ }
if (activationType == kTfLiteActNone)
{
diff --git a/delegate/src/Convolution.hpp b/delegate/src/Convolution.hpp
index a8559e2548..31cb2ab9ac 100644
--- a/delegate/src/Convolution.hpp
+++ b/delegate/src/Convolution.hpp
@@ -222,7 +222,10 @@ TfLiteStatus VisitConv2dOperator(DelegateData& delegateData,
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
- Connect(layer, tfLiteNode, delegateData);
+ if(Connect(layer, tfLiteNode, delegateData) != kTfLiteOk)
+ {
+ return kTfLiteError;
+ }
if (!tfLiteNodeParameters)
{
@@ -408,7 +411,10 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
- Connect(layer, tfLiteNode, delegateData);
+ if(Connect(layer, tfLiteNode, delegateData) != kTfLiteOk)
+ {
+ return kTfLiteError;
+ }
if (!tfLiteNodeParameters)
{
@@ -624,7 +630,11 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
outputSlot.SetTensorInfo(outputTensorInfo);
- Connect(layer, tfLiteNode, delegateData);
+ if(Connect(layer, tfLiteNode, delegateData) != kTfLiteOk)
+ {
+ return kTfLiteError;
+ }
+
if (!tfLiteNodeParameters)
{
// No Activation
diff --git a/delegate/src/DelegateUtils.hpp b/delegate/src/DelegateUtils.hpp
index 3e74225b15..1aa9029271 100644
--- a/delegate/src/DelegateUtils.hpp
+++ b/delegate/src/DelegateUtils.hpp
@@ -13,6 +13,7 @@
#include <armnn/utility/NumericCast.hpp>
#include <armnnUtils/Permute.hpp>
+#include <armnnUtils/TensorUtils.hpp>
#include <tensorflow/lite/builtin_ops.h>
#include <tensorflow/lite/c/builtin_op_data.h>
@@ -188,91 +189,25 @@ TfLiteStatus Connect(armnn::IConnectableLayer* layer,
return kTfLiteOk;
}
-armnn::IConnectableLayer* BroadcastTensor(const armnn::TensorInfo& inputInfo0,
- const armnn::TensorInfo& inputInfo1,
- armnn::IConnectableLayer* startLayer,
- TfLiteContext* tfLiteContext,
- TfLiteNode* tfLiteNode,
- armnnDelegate::DelegateData& delegateData)
+void ExpandTensorRankToEqual(armnn::TensorInfo& inputInfo0,
+ armnn::TensorInfo& inputInfo1)
{
unsigned int inputDimensions0 = inputInfo0.GetNumDimensions();
unsigned int inputDimensions1 = inputInfo1.GetNumDimensions();
if (inputDimensions0 == inputDimensions1)
{
- auto status = Connect(startLayer, tfLiteNode, delegateData);
- return status == kTfLiteOk ? startLayer : nullptr;
+ return;
}
unsigned int biggerInputDimensions = std::max(inputDimensions0, inputDimensions1);
- unsigned int dimDifference = static_cast<unsigned int>(std::abs(armnn::numeric_cast<int>(inputDimensions0) -
- armnn::numeric_cast<int>(inputDimensions1)));
bool input0IsSmaller = inputDimensions0 < inputDimensions1;
- const armnn::TensorInfo& smallInfo = input0IsSmaller ? inputInfo0 : inputInfo1;
- const armnn::TensorShape& smallShape = smallInfo.GetShape();
-
- std::vector<unsigned int> reshapedDimensions(biggerInputDimensions, 1);
- for (unsigned int i = dimDifference; i < biggerInputDimensions; ++i)
- {
- reshapedDimensions[i] = smallShape[i - dimDifference];
- }
-
- armnn::TensorInfo reshapedInfo = smallInfo;
- reshapedInfo.SetShape(armnn::TensorShape{ armnn::numeric_cast<unsigned int>(reshapedDimensions.size()),
- reshapedDimensions.data() });
-
- armnn::ReshapeDescriptor reshapeDescriptor;
- reshapeDescriptor.m_TargetShape = reshapedInfo.GetShape();
- bool isSupported = false;
- armnn::BackendId setBackend;
- FORWARD_LAYER_SUPPORT_FUNC("RESHAPE",
- tfLiteContext,
- IsReshapeSupported,
- delegateData.m_Backends,
- isSupported,
- setBackend,
- smallInfo,
- reshapedInfo,
- reshapeDescriptor);
- if (!isSupported)
- {
- return nullptr;
- }
+ armnn::TensorInfo& smallInfo = input0IsSmaller ? inputInfo0 : inputInfo1;
+ const armnn::TensorShape& newShape = armnnUtils::ExpandDimsToRank(smallInfo.GetShape(), biggerInputDimensions);
- ARMNN_ASSERT(delegateData.m_Network != nullptr);
- // Add Reshape layer
- armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor);
- reshapeLayer->SetBackendId(setBackend);
- ARMNN_ASSERT(reshapeLayer != nullptr);
- reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedInfo);
+ smallInfo.SetShape(newShape);
- if (input0IsSmaller)
- {
- delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[0])]
- ->Connect(reshapeLayer->GetInputSlot(0));
- reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(0));
- delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[1])]
- ->Connect(startLayer->GetInputSlot(1));
- }
- else
- {
- delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[1])]
- ->Connect(reshapeLayer->GetInputSlot(0));
- reshapeLayer->GetOutputSlot(0).Connect(startLayer->GetInputSlot(1));
- delegateData.m_OutputSlotForNode[static_cast<unsigned long>(tfLiteNode->inputs->data[0])]
- ->Connect(startLayer->GetInputSlot(0));
- }
-
- // Prepare output slots
- for (unsigned int outputIndex = 0; outputIndex < startLayer->GetNumOutputSlots(); ++outputIndex)
- {
- armnn::IOutputSlot& outputSlot = startLayer->GetOutputSlot(outputIndex);
- delegateData.m_OutputSlotForNode
- [static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &outputSlot;
- }
-
- return reshapeLayer;
}
TfLiteStatus FusedActivation(TfLiteContext* tfLiteContext,
diff --git a/delegate/src/ElementwiseBinary.hpp b/delegate/src/ElementwiseBinary.hpp
index 8096acfefb..52c6b2434b 100644
--- a/delegate/src/ElementwiseBinary.hpp
+++ b/delegate/src/ElementwiseBinary.hpp
@@ -254,6 +254,13 @@ TfLiteStatus VisitElementwiseBinaryOperator(DelegateData& delegateData,
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+ // Check if we need to expand the dims of the input tensor infos.
+ // This is required for a few of the backends.
+ if(inputTensorInfo0.GetNumDimensions() != inputTensorInfo1.GetNumDimensions())
+ {
+ ExpandTensorRankToEqual(inputTensorInfo0, inputTensorInfo1);
+ }
+
auto* tfLiteNodeParameters = reinterpret_cast<TfLiteAddParams*>(tfLiteNode->builtin_data);
TfLiteFusedActivation activationType = kTfLiteActNone;
if (tfLiteNodeParameters)
@@ -363,13 +370,7 @@ TfLiteStatus VisitElementwiseBinaryOperator(DelegateData& delegateData,
return inputsTensorsProcess;
}
- auto reshapeLayer = BroadcastTensor(inputTensorInfo0,
- inputTensorInfo1,
- elementwiseBinaryLayer,
- tfLiteContext,
- tfLiteNode,
- delegateData);
- if (!reshapeLayer)
+ if(Connect(elementwiseBinaryLayer, tfLiteNode, delegateData) != kTfLiteOk)
{
return kTfLiteError;
}
diff --git a/delegate/src/Gather.hpp b/delegate/src/Gather.hpp
index 9e98966471..9125997417 100644
--- a/delegate/src/Gather.hpp
+++ b/delegate/src/Gather.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2020,2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2020,2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -101,8 +101,6 @@ TfLiteStatus VisitGatherOperator(DelegateData& delegateData,
return inputsTensorsProcess;
}
- Connect(layer, tfLiteNode, delegateData);
-
- return kTfLiteOk;
+ return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate \ No newline at end of file
diff --git a/delegate/src/GatherNd.hpp b/delegate/src/GatherNd.hpp
index f2192f77c3..cf526e1995 100644
--- a/delegate/src/GatherNd.hpp
+++ b/delegate/src/GatherNd.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -77,8 +77,6 @@ TfLiteStatus VisitGatherNdOperator(DelegateData& delegateData,
return inputsTensorsProcess;
}
- Connect(layer, tfLiteNode, delegateData);
-
- return kTfLiteOk;
+ return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate \ No newline at end of file
diff --git a/delegate/src/LogicalBinary.hpp b/delegate/src/LogicalBinary.hpp
index b6a8f5d5f6..d71618ee9c 100644
--- a/delegate/src/LogicalBinary.hpp
+++ b/delegate/src/LogicalBinary.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -46,6 +46,13 @@ TfLiteStatus VisitLogicalBinaryOperator(DelegateData& delegateData,
armnn::TensorInfo inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+ // Check if we need to expand the dims of any of the input tensor infos.
+ // This is required for a few of the backends.
+ if(inputTensorInfo0.GetNumDimensions() != inputTensorInfo1.GetNumDimensions())
+ {
+ ExpandTensorRankToEqual(inputTensorInfo0, inputTensorInfo1);
+ }
+
// Setup descriptor and assign operation
armnn::LogicalBinaryDescriptor desc;
desc.m_Operation = binaryOperation;
@@ -89,18 +96,7 @@ TfLiteStatus VisitLogicalBinaryOperator(DelegateData& delegateData,
return inputsTensorsProcess;
}
- // LogicalBinary operators support broadcasting
- auto reshapeLayer = BroadcastTensor(inputTensorInfo0,
- inputTensorInfo1,
- logicalBinaryLayer,
- tfLiteContext,
- tfLiteNode,
- delegateData);
- if (!reshapeLayer)
- {
- return kTfLiteError;
- }
- return kTfLiteOk;
+ return Connect(logicalBinaryLayer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
diff --git a/delegate/src/test/ElementwiseBinaryTest.cpp b/delegate/src/test/ElementwiseBinaryTest.cpp
index 9d03204263..8099efebff 100644
--- a/delegate/src/test/ElementwiseBinaryTest.cpp
+++ b/delegate/src/test/ElementwiseBinaryTest.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2020-2021, 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -885,7 +885,7 @@ TEST_CASE ("ADD_Broadcast_CpuAcc_Test")
AddBroadcastTest(backends);
}
-TEST_CASE ("ADD_Actiation_CpuAcc_Test")
+TEST_CASE ("ADD_Activation_CpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
AddActivationTest(backends);
@@ -1017,7 +1017,7 @@ TEST_CASE ("ADD_Constant_Input_CpuRef_Test")
AddConstInputTest(backends);
}
-TEST_CASE ("ADD_Actiation_CpuRef_Test")
+TEST_CASE ("ADD_Activation_CpuRef_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
AddActivationTest(backends);
diff --git a/include/armnnUtils/TensorUtils.hpp b/include/armnnUtils/TensorUtils.hpp
index a2aa9b0a98..7bf41c1ac8 100644
--- a/include/armnnUtils/TensorUtils.hpp
+++ b/include/armnnUtils/TensorUtils.hpp
@@ -48,6 +48,8 @@ armnn::TensorInfo ReduceDims(const armnn::TensorInfo& tensorInfo, unsigned int d
armnn::TensorShape ExpandDims(const armnn::TensorShape& tensorShape, int axis);
+armnn::TensorShape ExpandDimsToRank(const armnn::TensorShape& tensorShape, unsigned int rank);
+
std::vector<unsigned int> SqueezeDims(const armnn::TensorShape& tensorShape);
unsigned int GetNumElementsBetween(const armnn::TensorShape& shape,
diff --git a/src/armnnUtils/TensorUtils.cpp b/src/armnnUtils/TensorUtils.cpp
index 03109e0cee..cb73d92ef8 100644
--- a/src/armnnUtils/TensorUtils.cpp
+++ b/src/armnnUtils/TensorUtils.cpp
@@ -165,6 +165,31 @@ TensorShape ExpandDims(const TensorShape& tensorShape, int axis)
return { outputDim, outputShape.data() };
}
+TensorShape ExpandDimsToRank(const TensorShape& tensorShape, unsigned int rank)
+{
+ // Can't expand if rank is smaller than current shape
+ if (tensorShape.GetNumDimensions() >= rank)
+ {
+ return tensorShape;
+ }
+
+ std::vector<unsigned int> newShape;
+
+ // First add 1s to the beginning of the tensorInfo to fill in the space
+ for (unsigned int i = 0; i < rank - tensorShape.GetNumDimensions(); ++i)
+ {
+ newShape.push_back(1);
+ }
+
+ // Then iterate through the original shape and append it to the new shape with the added 1s
+ for (unsigned int i = 0; i < tensorShape.GetNumDimensions(); ++i)
+ {
+ newShape.push_back(tensorShape[i]);
+ }
+
+ return TensorShape(static_cast<unsigned int>(newShape.size()), newShape.data());
+}
+
std::vector<unsigned int> SqueezeDims(const TensorShape& tensorShape)
{
std::vector<unsigned int> squeezedDims;
diff --git a/src/armnnUtils/test/TensorUtilsTest.cpp b/src/armnnUtils/test/TensorUtilsTest.cpp
index a69a0098ce..ed21bbe93c 100644
--- a/src/armnnUtils/test/TensorUtilsTest.cpp
+++ b/src/armnnUtils/test/TensorUtilsTest.cpp
@@ -126,11 +126,79 @@ TEST_CASE("ExpandDimsInvalidAxisTest")
CHECK_THROWS_AS(ExpandDims(inputShape, 4), armnn::InvalidArgumentException);
}
+TEST_CASE("ExpandDimsInvalidNegativeAxisTest")
+{
+ armnn::TensorShape inputShape({ 2, 3, 4 });
+
+ // Invalid expand dimension -5
+ CHECK_THROWS_AS(ExpandDims(inputShape, -5), armnn::InvalidArgumentException);
+}
+
+TEST_CASE("ExpandDimsBy1Rank")
+{
+ armnn::TensorShape inputShape({ 2, 3, 4 });
+
+ // Expand by 1 dimension
+ armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4);
+ CHECK(outputShape.GetNumDimensions() == 4);
+ CHECK(outputShape[0] == 1);
+ CHECK(outputShape[1] == 2);
+ CHECK(outputShape[2] == 3);
+ CHECK(outputShape[3] == 4);
+}
+
+TEST_CASE("ExpandDimsBy2Ranks")
+{
+ armnn::TensorShape inputShape({ 3, 4 });
+
+ // Expand 2 dimensions
+ armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4);
+ CHECK(outputShape.GetNumDimensions() == 4);
+ CHECK(outputShape[0] == 1);
+ CHECK(outputShape[1] == 1);
+ CHECK(outputShape[2] == 3);
+ CHECK(outputShape[3] == 4);
+}
+
+TEST_CASE("ExpandDimsBy3Ranks")
+{
+ armnn::TensorShape inputShape({ 4 });
+
+ // Expand 3 dimensions
+ armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 4);
+ CHECK(outputShape.GetNumDimensions() == 4);
+ CHECK(outputShape[0] == 1);
+ CHECK(outputShape[1] == 1);
+ CHECK(outputShape[2] == 1);
+ CHECK(outputShape[3] == 4);
+}
+
+TEST_CASE("ExpandDimsInvalidRankAmount")
+{
+ armnn::TensorShape inputShape({ 2, 3, 4 });
+
+ // Don't expand because target rank is smaller than current rank
+ armnn::TensorShape outputShape = ExpandDimsToRank(inputShape, 2);
+ CHECK(outputShape.GetNumDimensions() == 3);
+ CHECK(outputShape[0] == 2);
+ CHECK(outputShape[1] == 3);
+ CHECK(outputShape[2] == 4);
+}
+
+TEST_CASE("ExpandDimsToRankInvalidTensorShape")
+{
+ armnn::TensorShape inputShape({ 2, 3, 4 });
+
+ // Throw exception because rank 6 tensors are unsupported by armnn
+ CHECK_THROWS_AS(ExpandDimsToRank(inputShape, 6), armnn::InvalidArgumentException);
+}
+
+
TEST_CASE("ReduceDimsShapeAll1s")
{
armnn::TensorShape inputShape({ 1, 1, 1 });
- // Invalid expand dimension 4
+ // Reduce dimension 2
armnn::TensorShape outputShape = ReduceDims(inputShape, 2);
CHECK(outputShape.GetNumDimensions() == 2);
CHECK(outputShape[0] == 1);
@@ -141,7 +209,7 @@ TEST_CASE("ReduceDimsShapeNotEnough1s")
{
armnn::TensorShape inputShape({ 1, 2, 1 });
- // Invalid expand dimension 4
+ // Reduce dimension 1
armnn::TensorShape outputShape = ReduceDims(inputShape, 1);
CHECK(outputShape.GetNumDimensions() == 2);
CHECK(outputShape[0] == 2);
@@ -152,7 +220,7 @@ TEST_CASE("ReduceDimsInfoAll1s")
{
armnn::TensorInfo inputInfo({ 1, 1, 1 }, DataType::Float32);
- // Invalid expand dimension 4
+ // Reduce dimension 2
armnn::TensorInfo outputInfo = ReduceDims(inputInfo, 2);
CHECK(outputInfo.GetShape().GetNumDimensions() == 2);
CHECK(outputInfo.GetShape()[0] == 1);
@@ -163,7 +231,7 @@ TEST_CASE("ReduceDimsInfoNotEnough1s")
{
armnn::TensorInfo inputInfo({ 1, 2, 1 }, DataType::Float32);
- // Invalid expand dimension 4
+ // Reduce dimension 1
armnn::TensorInfo outputInfo = ReduceDims(inputInfo, 1);
CHECK(outputInfo.GetNumDimensions() == 2);
CHECK(outputInfo.GetShape()[0] == 2);
@@ -174,7 +242,7 @@ TEST_CASE("ReduceDimsShapeDimensionGreaterThanSize")
{
armnn::TensorShape inputShape({ 1, 1, 1 });
- // Invalid expand dimension 4
+ // Do not reduce because dimension does not exist
armnn::TensorShape outputShape = ReduceDims(inputShape, 4);
CHECK(outputShape.GetNumDimensions() == 3);
CHECK(outputShape[0] == 1);
@@ -182,13 +250,6 @@ TEST_CASE("ReduceDimsShapeDimensionGreaterThanSize")
CHECK(outputShape[2] == 1);
}
-TEST_CASE("ExpandDimsInvalidNegativeAxisTest")
-{
- armnn::TensorShape inputShape({ 2, 3, 4 });
-
- // Invalid expand dimension -5
- CHECK_THROWS_AS(ExpandDims(inputShape, -5), armnn::InvalidArgumentException);
-}
TEST_CASE("ToFloatArrayInvalidDataType")
{
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-10 17:13:39 +0000