IVGCVSW-3639 Add 5d tensor support
* Increased MaxNumOfTensorDimensions and fixed issues related to its use
* Fixed issues caused by assuming 5d tensors are invalid
* Updated ArmComputeTensorUtils for 5d tensors
* Added 5d tensor unit tests for add, mul, stack and reshape (needed by IVGCVSW-3527)
Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Change-Id: I5bcd64942d0d04efcc6c5acb240ad4b88e010743
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index 6754106..2201499 100644
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -2641,6 +2641,103 @@
return ret;
}
+LayerTestResult<float, 5> Addition5dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ unsigned int depth = 2;
+ unsigned int batchSize = 2;
+ unsigned int channels = 2;
+ unsigned int height = 2;
+ unsigned int width = 3;
+
+ armnn::TensorInfo inputTensorInfo1, inputTensorInfo2;
+ armnn::TensorInfo outputTensorInfo;
+
+ unsigned int shape[] = {depth, batchSize, channels, height, width};
+
+ inputTensorInfo1 = armnn::TensorInfo(5, shape, armnn::DataType::Float32);
+ inputTensorInfo2 = armnn::TensorInfo(5, shape, armnn::DataType::Float32);
+ outputTensorInfo = armnn::TensorInfo(5, shape, armnn::DataType::Float32);
+
+
+ auto input1 = MakeTensor<float, 5>(inputTensorInfo1, std::vector<float>(
+ {
+ 2.6f, 4.0f, 4.4f, 2.7f, 4.6f, 2.8f,
+ 2.3f, 1.9f, 3.4f, 2.9f, 2.2f, 4.5f,
+
+ 2.8f, 1.9f, 2.3f, 2.6f, 4.7f, 3.5f,
+ 0.4f, 1.5f, 2.1f, 0.7f, 5.0f, 1.1f,
+
+
+ 1.0f, 2.7f, 0.0f, 0.6f, 0.8f, 0.9f,
+ 1.0f, 2.6f, 0.4f, 3.8f, 0.4f, 0.8f,
+
+ 0.5f, 4.3f, 3.1f, 4.4f, 0.7f, 1.4f,
+ 0.4f, 4.4f, 0.7f, 0.6f, 4.7f, 1.2f,
+
+ }));
+
+ auto input2 = MakeTensor<float, 5>(inputTensorInfo2, std::vector<float>(
+ {
+ 4.4f, 3.0f, 1.0f, 0.0f, 3.9f, 3.1f,
+ 1.7f, 2.9f, 1.3f, 0.4f, 0.4f, 4.3f,
+
+ 4.5f, 0.2f, 2.2f, 4.1f, 3.9f, 3.0f,
+ 0.1f, 2.5f, 4.1f, 4.6f, 1.5f, 0.0f,
+
+
+ 0.5f, 4.9f, 2.5f, 1.5f, 3.4f, 4.5f,
+ 2.0f, 3.0f, 4.9f, 1.6f, 2.4f, 3.4f,
+
+ 3.6f, 1.8f, 1.3f, 2.6f, 2.1f, 4.8f,
+ 2.0f, 4.3f, 4.0f, 0.2f, 0.6f, 4.4f,
+ }));
+
+ LayerTestResult<float, 5> ret(outputTensorInfo);
+ ret.outputExpected = MakeTensor<float, 5>(outputTensorInfo, std::vector<float>(
+ {
+ 7.0f, 7.0f, 5.4f, 2.7f, 8.5f, 5.9f,
+ 4.0f, 4.8f, 4.7f, 3.3f, 2.6f, 8.8f,
+
+ 7.3f, 2.1f, 4.5f, 6.7f, 8.6f, 6.5f,
+ 0.5f, 4.0f, 6.2f, 5.3f, 6.5f, 1.1f,
+
+
+ 1.5f, 7.6f, 2.5f, 2.1f, 4.2f, 5.4f,
+ 3.0f, 5.6f, 5.3f, 5.4f, 2.8f, 4.2f,
+
+ 4.1f, 6.1f, 4.4f, 7.0f, 2.8f, 6.2f,
+ 2.4f, 8.7f, 4.7f, 0.8f, 5.3f, 5.6f,
+ }));
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1);
+ std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::AdditionQueueDescriptor data;
+ armnn::WorkloadInfo info;
+ AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());
+ AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info);
+
+ inputHandle1->Allocate();
+ inputHandle2->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0][0]);
+ CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0][0]);
+
+ workload->PostAllocationConfigure();
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&ret.output[0][0][0][0][0], outputHandle.get());
+
+ return ret;
+}
+
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> AdditionBroadcastTestImpl(
armnn::IWorkloadFactory& workloadFactory,
@@ -4103,25 +4200,25 @@
}
namespace {
-LayerTestResult<float,4> MultiplicationTestHelper(
+template<std::size_t NumDims>
+LayerTestResult<float,NumDims> MultiplicationTestHelper(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const unsigned int shape0[4],
+ const unsigned int shape0[NumDims],
const std::vector<float> & values0,
- const unsigned int shape1[4],
+ const unsigned int shape1[NumDims],
const std::vector<float> & values1,
- const unsigned int outShape[4],
+ const unsigned int outShape[NumDims],
const std::vector<float> & outValues)
{
- const uint32_t dimensionCount = 4;
- armnn::TensorInfo inputTensorInfo0{dimensionCount, shape0, armnn::DataType::Float32};
- armnn::TensorInfo inputTensorInfo1{dimensionCount, shape1, armnn::DataType::Float32};
- armnn::TensorInfo outputTensorInfo{dimensionCount, outShape, armnn::DataType::Float32};
+ armnn::TensorInfo inputTensorInfo0{NumDims, shape0, armnn::DataType::Float32};
+ armnn::TensorInfo inputTensorInfo1{NumDims, shape1, armnn::DataType::Float32};
+ armnn::TensorInfo outputTensorInfo{NumDims, outShape, armnn::DataType::Float32};
- auto input0 = MakeTensor<float, 4>(inputTensorInfo0, values0);
- auto input1 = MakeTensor<float, 4>(inputTensorInfo1, values1);
+ auto input0 = MakeTensor<float, NumDims>(inputTensorInfo0, values0);
+ auto input1 = MakeTensor<float, NumDims>(inputTensorInfo1, values1);
- LayerTestResult<float,4> ret(outputTensorInfo);
+ LayerTestResult<float,NumDims> ret(outputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0);
std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1);
@@ -4139,15 +4236,15 @@
inputHandle1->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]);
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]);
+ CopyDataToITensorHandle(inputHandle0.get(), input0.origin());
+ CopyDataToITensorHandle(inputHandle1.get(), input1.origin());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(ret.output.origin(), outputHandle.get());
- ret.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outValues);
+ ret.outputExpected = MakeTensor<float, NumDims>(outputTensorInfo, outValues);
return ret;
}
} // anonymous namespace
@@ -4176,14 +4273,81 @@
2, 2, 2, 2, 6, 6, 6, 6,
12, 12, 12, 12, 20, 20, 20, 20 });
- return MultiplicationTestHelper(workloadFactory,
- memoryManager,
- shape,
- input0,
- shape,
- input1,
- shape,
- output);
+ return MultiplicationTestHelper<4>(workloadFactory,
+ memoryManager,
+ shape,
+ input0,
+ shape,
+ input1,
+ shape,
+ output);
+}
+
+LayerTestResult<float,5> Multiplication5dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ const unsigned int width = 3;
+ const unsigned int height = 2;
+ const unsigned int channelCount = 2;
+ const unsigned int batchSize = 2;
+ const unsigned int depth = 2;
+
+ unsigned int shape[] = { depth, batchSize, channelCount, height, width };
+
+ std::vector<float> input0({
+ 1.80f, 0.20f, 2.30f, 1.30f, 2.10f, 1.00f,
+ 2.60f, 0.60f, 2.10f, 2.30f, 2.30f, 2.00f,
+
+ 2.50f, 1.00f, 2.90f, 3.10f, 1.50f, 2.40f,
+ 2.80f, 1.10f, 1.00f, 3.20f, 1.00f, 2.30f,
+
+
+ 0.30f, 2.20f, 1.00f, 0.20f, 1.60f, 1.40f,
+ 0.80f, 3.20f, 0.10f, 0.10f, 3.10f, 2.10f,
+
+ 1.50f, 2.40f, 1.40f, 0.70f, 2.40f, 1.40f,
+ 1.60f, 1.20f, 1.90f, 0.80f, 0.00f, 0.10f,
+ });
+
+ std::vector<float> input1({
+ 0.70f, 1.00f, 2.90f, 2.20f, 3.10f, 2.80f,
+ 1.80f, 2.00f, 0.50f, 2.30f, 1.20f, 2.70f,
+
+ 2.40f, 0.20f, 3.20f, 1.60f, 0.20f, 2.50f,
+ 2.30f, 0.70f, 2.70f, 1.80f, 2.90f, 2.70f,
+
+
+ 3.20f, 3.20f, 0.70f, 1.90f, 2.70f, 2.50f,
+ 2.40f, 0.90f, 2.30f, 1.80f, 2.50f, 2.00f,
+
+ 1.60f, 2.20f, 1.60f, 2.00f, 0.30f, 3.20f,
+ 0.40f, 3.00f, 2.60f, 0.30f, 0.00f, 2.50f,
+ });
+
+ std::vector<float> output({
+ 1.26f, 0.20f, 6.67f, 2.86f, 6.51f, 2.80f,
+ 4.68f, 1.20f, 1.05f, 5.29f, 2.76f, 5.40f,
+
+ 6.00f, 0.20f, 9.28f, 4.96f, 0.30f, 6.00f,
+ 6.44f, 0.77f, 2.70f, 5.76f, 2.90f, 6.21f,
+
+
+ 0.96f, 7.04f, 0.70f, 0.38f, 4.32f, 3.50f,
+ 1.92f, 2.88f, 0.23f, 0.18f, 7.75f, 4.20f,
+
+ 2.40f, 5.28f, 2.24f, 1.40f, 0.72f, 4.48f,
+ 0.64f, 3.60f, 4.94f, 0.24f, 0.00f, 0.25f,
+ });
+
+ return MultiplicationTestHelper<5>(workloadFactory,
+ memoryManager,
+ shape,
+ input0,
+ shape,
+ input1,
+ shape,
+ output);
}
LayerTestResult<float, 4> MultiplicationBroadcast1ElementTest(
@@ -4198,14 +4362,14 @@
std::vector<float> output({ 2, 4, 6, 8, 10, 12, 14, 16});
- return MultiplicationTestHelper(workloadFactory,
- memoryManager,
- shape0,
- input0,
- shape1,
- input1,
- shape0,
- output);
+ return MultiplicationTestHelper<4>(workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
}
LayerTestResult<float, 4> MultiplicationBroadcast1DVectorTest(
@@ -4226,14 +4390,14 @@
7, 16, 9, 20, 11, 24,
13, 28, 15, 32, 17, 36});
- return MultiplicationTestHelper(workloadFactory,
- memoryManager,
- shape0,
- input0,
- shape1,
- input1,
- shape0,
- output);
+ return MultiplicationTestHelper<4>(workloadFactory,
+ memoryManager,
+ shape0,
+ input0,
+ shape1,
+ input1,
+ shape0,
+ output);
}
LayerTestResult<float,4> CompareMultiplicationTest(