IVGCVSW-5962 Remove boost::multi_array
* Replaced all instances of boost::multi_array with flat vectors.
* Updated LayerTestResult struct with new member variables.
* Updated CompareTensor function to compare flat vectors and the shape.
* Removed MakeTensor function from TensorHelpers.hpp.
* Removed GetTensorShapeAsArray function from LayerTestResult.hpp.
* Removed boost::array usage.
* Removed boost::extents usages.
* Removed boost::random usages.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Iccde9d6640b534940292ff048fb80c00b38c4743
diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
index d486bc0..3eca273 100644
--- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
@@ -428,9 +428,9 @@
{
TensorInfo inputTensorInfo({ 3 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 1.0f, 2.0f, 3.0f }, qScale, qOffset));
- auto input1 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 4.0f, 5.0f, 6.0f }, qScale, qOffset));
- auto input2 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>({ 7.0f, 8.0f, 9.0f }, qScale, qOffset));
+ auto input0 = QuantizedVector<T>({ 1.0f, 2.0f, 3.0f }, qScale, qOffset);
+ auto input1 = QuantizedVector<T>({ 4.0f, 5.0f, 6.0f }, qScale, qOffset);
+ auto input2 = QuantizedVector<T>({ 7.0f, 8.0f, 9.0f }, qScale, qOffset);
TensorInfo outputTensorInfo({ 9 }, ArmnnType, qScale, qOffset);
@@ -446,12 +446,12 @@
0,
true);
- result.output = MakeTensor<T, 1>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 1>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -468,7 +468,7 @@
{
TensorInfo inputTensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f,
@@ -476,9 +476,9 @@
// Batch 1
10.0f, 11.0f, 12.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input1 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0
4.0f, 5.0f, 6.0f,
@@ -486,9 +486,9 @@
// Batch 1
13.0f, 14.0f, 15.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input2 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0
7.0f, 8.0f, 9.0f,
@@ -496,7 +496,7 @@
// Batch 1
16.0f, 17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
LayerTestResult<T, 2> result(outputTensorInfo);
@@ -510,7 +510,7 @@
dimension,
true);
- result.output = MakeTensor<T, 2>(outputTensorInfo, output);
+ result.m_ActualData = output;
return result;
}
@@ -527,7 +527,7 @@
LayerTestResult<T, 2> result = Concat2dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 0, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f,
@@ -547,7 +547,7 @@
// Batch 5
16.0f, 17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -565,7 +565,7 @@
LayerTestResult<T, 2> result = Concat2dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 1, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
@@ -573,7 +573,7 @@
// Batch 1
10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -587,7 +587,7 @@
int32_t qOffset)
{
TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f,
@@ -595,10 +595,10 @@
// Batch 1
10.0f, 11.0f, 12.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input1TensorInfo({ 3, 3 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0
4.0f, 5.0f, 6.0f,
@@ -609,15 +609,15 @@
// Batch 0
7.0f, 8.0f, 9.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input2TensorInfo({ 1, 3 }, ArmnnType, qScale, qOffset);
- auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 1
16.0f, 17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 6, 3 }, ArmnnType, qScale, qOffset);
LayerTestResult<T, 2> result(outputTensorInfo);
@@ -632,8 +632,8 @@
0,
true);
- result.output = MakeTensor<T, 2>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f,
@@ -653,7 +653,7 @@
// Batch 5
16.0f, 17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -667,7 +667,7 @@
int32_t qOffset)
{
TensorInfo input0TensorInfo({ 2, 3 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f,
@@ -675,10 +675,10 @@
// Batch 1
10.0f, 11.0f, 12.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input1TensorInfo({ 2, 5 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0
4.0f, 5.0f, 6.0f, 7.0f, 8.0f,
@@ -686,10 +686,10 @@
// Batch 1
13.0f, 14.0f, 15.0f, 16.0f, 17.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input2TensorInfo({ 2, 1 }, ArmnnType, qScale, qOffset);
- auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0
9.0f,
@@ -697,7 +697,7 @@
// Batch 1
18.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 2, 9 }, ArmnnType, qScale, qOffset);
LayerTestResult<T, 2> result(outputTensorInfo);
@@ -712,8 +712,8 @@
1,
true);
- result.output = MakeTensor<T, 2>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0
1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
@@ -721,7 +721,7 @@
// Batch 1
10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -739,7 +739,7 @@
{
TensorInfo inputTensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -759,9 +759,9 @@
// Batch 1, Channel 2
23.0f, 24.0f
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input1 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0, Channel 0
7.0f, 8.0f,
@@ -781,9 +781,9 @@
// Batch 1, Channel 2
29.0f, 30.0f
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input2 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0, Channel 0
13.0f, 14.0f,
@@ -803,7 +803,7 @@
// Batch 1, Channel 2
35.0f, 36.0f
},
- qScale, qOffset));
+ qScale, qOffset);
LayerTestResult<T, 3> result(outputTensorInfo);
@@ -817,7 +817,7 @@
dimension,
useSubtensor);
- result.output = MakeTensor<T, 3>(outputTensorInfo, output);
+ result.m_ActualData = output;
return result;
}
@@ -834,7 +834,7 @@
LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 0, true, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -890,7 +890,7 @@
// Batch 5, Channel 2
35.0f, 36.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -908,7 +908,7 @@
LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 1, true, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -964,7 +964,7 @@
// Batch 1, Channel 8
35.0f, 36.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -983,7 +983,7 @@
LayerTestResult<T, 3> result = Concat3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 2, useSubtensor, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f, 7.0f, 8.0f, 13.0f, 14.0f,
@@ -1003,7 +1003,7 @@
// Batch 1, Channel 2
23.0f, 24.0f, 29.0f, 30.0f, 35.0f, 36.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1017,7 +1017,7 @@
int32_t qOffset)
{
TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType);
- auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -1037,10 +1037,10 @@
// Batch 1, Channel 2
23.0f, 24.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input1TensorInfo({ 1, 3, 2 }, ArmnnType);
- auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0, Channel 0
7.0f, 8.0f,
@@ -1051,10 +1051,10 @@
// Batch 0, Channel 2
11.0f, 12.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input2TensorInfo({ 3, 3, 2 }, ArmnnType);
- auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0, Channel 0
25.0f, 26.0f,
@@ -1083,7 +1083,7 @@
// Batch 2, Channel 2
35.0f, 36.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 6, 3, 2 }, ArmnnType);
LayerTestResult<T, 3> result(outputTensorInfo);
@@ -1098,8 +1098,8 @@
0,
true);
- result.output = MakeTensor<T, 3>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -1155,7 +1155,7 @@
// Batch 5, Channel 2
35.0f, 36.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1169,7 +1169,7 @@
int32_t qOffset)
{
TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -1189,10 +1189,10 @@
// Batch 1, Channel 2
23.0f, 24.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input1TensorInfo({ 2, 4, 2 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0, Channel 0
7.0f, 8.0f,
@@ -1218,10 +1218,10 @@
// Batch 1, Channel 3
15.0f, 16.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input2TensorInfo({ 2, 1, 2 }, ArmnnType, qScale, qOffset);
- auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0, Channel 0
17.0f, 18.0f,
@@ -1229,7 +1229,7 @@
// Batch 1, Channel 0
31.0f, 32.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 2, 8, 2 }, ArmnnType, qScale, qOffset);
LayerTestResult<T, 3> result(outputTensorInfo);
@@ -1244,8 +1244,8 @@
1,
true);
- result.output = MakeTensor<T, 3>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -1295,7 +1295,7 @@
// Batch 1, Channel 7
31.0f, 32.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1310,7 +1310,7 @@
int32_t qOffset)
{
TensorInfo input0TensorInfo({ 2, 3, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f,
@@ -1330,10 +1330,10 @@
// Batch 1, Channel 2
23.0f, 24.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input1TensorInfo({ 2, 3, 1 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
// Batch 0, Channel 0
7.0f,
@@ -1353,10 +1353,10 @@
// Batch 1, Channel 2
29.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo input2TensorInfo({ 2, 3, 3 }, ArmnnType, qScale, qOffset);
- auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
// Batch 0, Channel 0
13.0f, 14.0f, 50.0f,
@@ -1376,7 +1376,7 @@
// Batch 1, Channel 2
35.0f, 36.0f, 55.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 2, 3, 6 }, ArmnnType, qScale, qOffset);
LayerTestResult<T, 3> result(outputTensorInfo);
@@ -1391,8 +1391,8 @@
2,
useSubtensor);
- result.output = MakeTensor<T, 3>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
// Batch 0, Channel 0
1.0f, 2.0f, 7.0f, 13.0f, 14.0f, 50.0f,
@@ -1412,7 +1412,7 @@
// Batch 1, Channel 2
23.0f, 24.0f, 29.0f, 35.0f, 36.0f, 55.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1430,7 +1430,7 @@
{
TensorInfo inputTensorInfo({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1439,9 +1439,9 @@
9.0f, 10.0f,
11.0f, 12.0f
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input1 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
11.0f, 12.0f,
13.0f, 14.0f,
@@ -1450,9 +1450,9 @@
19.0f, 20.0f,
21.0f, 22.0f
},
- qScale, qOffset));
+ qScale, qOffset);
- auto input2 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(
+ auto input2 = QuantizedVector<T>(
{
21.0f, 22.0f,
23.0f, 24.0f,
@@ -1461,7 +1461,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
LayerTestResult<T, 4> result(outputTensorInfo);
@@ -1478,7 +1478,7 @@
dimension,
useSubtensor);
- result.output = MakeTensor<T, 4>(outputTensorInfo, output);
+ result.m_ActualData = output;
return result;
}
@@ -1495,7 +1495,7 @@
LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 0, true, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1518,7 +1518,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1536,7 +1536,7 @@
LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 1, true, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1559,7 +1559,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1577,7 +1577,7 @@
LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 2, true, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1600,7 +1600,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1619,7 +1619,7 @@
LayerTestResult<T, 4> result = Concat4dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, outputTensorInfo, 3, useSubtensor, qScale, qOffset);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
11.0f, 12.0f,
@@ -1642,7 +1642,7 @@
21.0f, 22.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1658,7 +1658,7 @@
constexpr unsigned int dimension = 0u;
TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1667,11 +1667,11 @@
9.0f, 10.0f,
11.0f, 12.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo inputTensorInfo1({ 2, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
11.0f, 12.0f,
13.0f, 14.0f,
@@ -1687,7 +1687,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, ArmnnType, qScale, qOffset);
@@ -1705,8 +1705,8 @@
dimension,
true);
- result.output = MakeTensor<T, 4>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1729,7 +1729,7 @@
29.0f, 30.0f,
31.0f, 32.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1745,7 +1745,7 @@
constexpr unsigned int dimension = 1u;
TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1754,18 +1754,18 @@
9.0f, 10.0f,
11.0f, 12.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
11.0f, 12.0f,
13.0f, 14.0f,
15.0f, 16.0f,
17.0f, 18.0f,
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 1, 5, 2, 2 }, ArmnnType, qScale, qOffset);
@@ -1783,8 +1783,8 @@
dimension,
true);
- result.output = MakeTensor<T, 4>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1797,7 +1797,7 @@
15.0f, 16.0f,
17.0f, 18.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1813,7 +1813,7 @@
constexpr unsigned int dimension = 2u;
TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1822,10 +1822,10 @@
9.0f, 10.0f,
11.0f, 12.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo inputTensorInfo1({ 1, 3, 3, 2 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
11.0f, 12.0f,
13.0f, 14.0f,
@@ -1837,7 +1837,7 @@
25.0f, 26.0f,
27.0f, 28.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 1, 3, 5, 2 }, ArmnnType, qScale, qOffset);
LayerTestResult<T, 4> result(outputTensorInfo);
@@ -1854,8 +1854,8 @@
dimension,
true);
- result.output = MakeTensor<T, 4>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1875,7 +1875,7 @@
25.0f, 26.0f,
27.0f, 28.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1892,7 +1892,7 @@
constexpr unsigned int dimension = 3u;
TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, ArmnnType, qScale, qOffset);
- auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(
+ auto input0 = QuantizedVector<T>(
{
1.0f, 2.0f,
3.0f, 4.0f,
@@ -1901,10 +1901,10 @@
9.0f, 10.0f,
11.0f, 12.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo inputTensorInfo1({ 1, 3, 2, 3 }, ArmnnType, qScale, qOffset);
- auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(
+ auto input1 = QuantizedVector<T>(
{
11.0f, 12.0f, 13.0f,
14.0f, 15.0f, 16.0f,
@@ -1915,7 +1915,7 @@
23.0f, 24.0f, 25.0f,
26.0f, 27.0f, 28.0f
},
- qScale, qOffset));
+ qScale, qOffset);
TensorInfo outputTensorInfo({ 1, 3, 2, 5 }, ArmnnType, qScale, qOffset);
@@ -1933,8 +1933,8 @@
dimension,
useSubtensor);
- result.output = MakeTensor<T, 4>(outputTensorInfo, output);
- result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(
+ result.m_ActualData = output;
+ result.m_ExpectedData = QuantizedVector<T>(
{
1.0f, 2.0f, 11.0f, 12.0f, 13.0f,
3.0f, 4.0f, 14.0f, 15.0f, 16.0f,
@@ -1943,7 +1943,7 @@
9.0f, 10.0f, 23.0f, 24.0f, 25.0f,
11.0f, 12.0f, 26.0f, 27.0f, 28.0f
},
- qScale, qOffset));
+ qScale, qOffset);
return result;
}
@@ -1968,7 +1968,7 @@
const float inputScale1 = 0.5f;
const int32_t inputOffset1 = 5;
- auto input1 = MakeTensor<T, 3>(inputTensorInfo1, std::vector<T>(
+ std::vector<T> input1 =
{
1, 2, 3,
4, 5, 6,
@@ -1983,13 +1983,13 @@
28, 29, 30,
31, 32, 33,
34, 35, 36
- }));
+ };
// Quatized input2 tensor.
const float inputScale2 = 0.2f;
const int32_t inputOffset2 = 10;
- auto input2 = MakeTensor<T, 3>(inputTensorInfo2, std::vector<T>(
+ std::vector<T> input2 =
{
37, 38, 39,
40, 41, 42,
@@ -1997,15 +1997,15 @@
46, 47, 48,
49, 50, 51,
52, 53, 54
- }));
+ };
// Quantized output tensor.
const float outputScale = 0.1f;
const int32_t outputOffset = 20;
- LayerTestResult<T, 3> ret(outputTensorInfo);
+ std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
- ret.outputExpected = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(
+ std::vector<T> expectedOutput =
{
0, 5, 74,
10, 15, 76,
@@ -2027,7 +2027,7 @@
150, 155, 104,
160, 165, 106,
170, 175, 108
- }));
+ };
outputTensorInfo.SetQuantizationScale(outputScale);
outputTensorInfo.SetQuantizationOffset(outputOffset);
@@ -2075,15 +2075,18 @@
inputHandle2->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
- CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+ CopyDataToITensorHandle(inputHandle1.get(), input1.data());
+ CopyDataToITensorHandle(inputHandle2.get(), input2.data());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
- return ret;
+ return LayerTestResult<T, 3>(actualOutput,
+ expectedOutput,
+ outputHandle->GetShape(),
+ outputTensorInfo.GetShape());
}
//
@@ -2132,61 +2135,58 @@
TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, DataType::Float32);
TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, DataType::Float32);
- LayerTestResult<float,3> ret(outputTensorInfo);
+ std::vector<float> actualOutput(outputTensorInfo.GetNumElements());
- ret.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float>(
+ std::vector<float> expectedOutput =
{
- 1.0f, 2.0f, 3.0f,
- 4.0f, 5.0f, 6.0f,
- 7.0f, 8.0f, 9.0f,
- 10.0f, 11.0f, 12.0f,
- 13.0f, 14.0f, 15.0f,
- 16.0f, 17.0f, 18.0f,
+ 1.0f, 2.0f, 3.0f,
+ 4.0f, 5.0f, 6.0f,
+ 7.0f, 8.0f, 9.0f,
+ 10.0f, 11.0f, 12.0f,
+ 13.0f, 14.0f, 15.0f,
+ 16.0f, 17.0f, 18.0f,
- 19.0f, 20.0f, 21.0f,
- 22.0f, 23.0f, 24.0f,
- 25.0f, 26.0f, 27.0f,
- 28.0f, 29.0f, 30.0f,
- 31.0f, 32.0f, 33.0f,
- 34.0f, 35.0f, 36.0f,
+ 19.0f, 20.0f, 21.0f,
+ 22.0f, 23.0f, 24.0f,
+ 25.0f, 26.0f, 27.0f,
+ 28.0f, 29.0f, 30.0f,
+ 31.0f, 32.0f, 33.0f,
+ 34.0f, 35.0f, 36.0f,
- 37.0f, 38.0f, 39.0f,
- 40.0f, 41.0f, 42.0f,
- 43.0f, 44.0f, 45.0f,
- 46.0f, 47.0f, 48.0f,
- 49.0f, 50.0f, 51.0f,
- 52.0f, 53.0f, 54.0f,
- })
- );
+ 37.0f, 38.0f, 39.0f,
+ 40.0f, 41.0f, 42.0f,
+ 43.0f, 44.0f, 45.0f,
+ 46.0f, 47.0f, 48.0f,
+ 49.0f, 50.0f, 51.0f,
+ 52.0f, 53.0f, 54.0f
+ };
- auto input1 = MakeTensor<float, 3>(inputTensorInfo1, std::vector<float>(
- {
- 1.0f, 2.0f, 3.0f,
- 4.0f, 5.0f, 6.0f,
- 7.0f, 8.0f, 9.0f,
- 10.0f, 11.0f, 12.0f,
- 13.0f, 14.0f, 15.0f,
- 16.0f, 17.0f, 18.0f,
+ std::vector<float> input1 =
+ {
+ 1.0f, 2.0f, 3.0f,
+ 4.0f, 5.0f, 6.0f,
+ 7.0f, 8.0f, 9.0f,
+ 10.0f, 11.0f, 12.0f,
+ 13.0f, 14.0f, 15.0f,
+ 16.0f, 17.0f, 18.0f,
- 19.0f, 20.0f, 21.0f,
- 22.0f, 23.0f, 24.0f,
- 25.0f, 26.0f, 27.0f,
- 28.0f, 29.0f, 30.0f,
- 31.0f, 32.0f, 33.0f,
- 34.0f, 35.0f, 36.0f,
- })
- );
+ 19.0f, 20.0f, 21.0f,
+ 22.0f, 23.0f, 24.0f,
+ 25.0f, 26.0f, 27.0f,
+ 28.0f, 29.0f, 30.0f,
+ 31.0f, 32.0f, 33.0f,
+ 34.0f, 35.0f, 36.0f
+ };
- auto input2 = MakeTensor<float, 3>(inputTensorInfo2, std::vector<float>(
- {
- 37.0f, 38.0f, 39.0f,
- 40.0f, 41.0f, 42.0f,
- 43.0f, 44.0f, 45.0f,
- 46.0f, 47.0f, 48.0f,
- 49.0f, 50.0f, 51.0f,
- 52.0f, 53.0f, 54.0f,
- })
- );
+ std::vector<float> input2 =
+ {
+ 37.0f, 38.0f, 39.0f,
+ 40.0f, 41.0f, 42.0f,
+ 43.0f, 44.0f, 45.0f,
+ 46.0f, 47.0f, 48.0f,
+ 49.0f, 50.0f, 51.0f,
+ 52.0f, 53.0f, 54.0f,
+ };
std::vector<unsigned int> wOrigin1 = {0, 0, 0}; //Extent of the window is defined by size of input[0].
ConcatQueueDescriptor::ViewOrigin window1(wOrigin1);
@@ -2223,15 +2223,18 @@
inputHandle2->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
- CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+ CopyDataToITensorHandle(inputHandle1.get(), input1.data());
+ CopyDataToITensorHandle(inputHandle2.get(), input2.data());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
- return ret;
+ return LayerTestResult<float, 3>(actualOutput,
+ expectedOutput,
+ outputHandle->GetShape(),
+ outputTensorInfo.GetShape());
}
LayerTestResult<float, 1> Concat1dTest(
@@ -2448,7 +2451,7 @@
const float inputScale1 = 0.015686f;
const int32_t inputOffset1 = 192;
- auto input1 = MakeTensor<uint8_t, 3>(inputTensorInfo1, std::vector<uint8_t>(
+ std::vector<uint8_t> input1 =
{
1, 2, 3,
4, 5, 6,
@@ -2462,33 +2465,31 @@
25, 26, 27,
28, 29, 30,
31, 32, 33,
- 34, 35, 36,
- })
- );
+ 34, 35, 36
+ };
// Quatized input2 tensor. Range [-1, 4]
const float inputScale2 = 0.019608f;
const int32_t inputOffset2 = 50;
- auto input2 = MakeTensor<uint8_t, 3>(inputTensorInfo2, std::vector<uint8_t>(
+ std::vector<uint8_t> input2 =
{
37, 38, 39,
40, 41, 42,
43, 44, 45,
46, 47, 48,
49, 50, 51,
- 52, 53, 54,
- })
- );
+ 52, 53, 54
+ };
// Output has the same quantization parameters than input1,
// so that only the requantization of input2 is required
const float outputScale = 0.015686f;
const int32_t outputOffset = 192;
- LayerTestResult<uint8_t, 3> ret(outputTensorInfo);
+ std::vector<uint8_t> actualOutput(outputTensorInfo.GetNumElements());
- ret.outputExpected = MakeTensor<uint8_t, 3>(outputTensorInfo, std::vector<uint8_t>(
+ std::vector<uint8_t> expectedOutput =
{
1, 2, 3,
4, 5, 6,
@@ -2509,9 +2510,8 @@
183, 184, 186,
187, 188, 189,
191, 192, 193,
- 195, 196, 197,
- })
- );
+ 195, 196, 197
+ };
outputTensorInfo.SetQuantizationScale(outputScale);
outputTensorInfo.SetQuantizationOffset(outputOffset);
@@ -2555,15 +2555,18 @@
inputHandle2->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
- CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+ CopyDataToITensorHandle(inputHandle1.get(), input1.data());
+ CopyDataToITensorHandle(inputHandle2.get(), input2.data());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
- return ret;
+ return LayerTestResult<uint8_t, 3>(actualOutput,
+ expectedOutput,
+ outputHandle->GetShape(),
+ outputTensorInfo.GetShape());
}
LayerTestResult<uint8_t, 3> ConcatUint8Test(
@@ -2601,34 +2604,9 @@
inputTensorInfo2.SetQuantizationScale(scale);
inputTensorInfo2.SetQuantizationOffset(offset);
- LayerTestResult<uint8_t, 3> ret(outputTensorInfo);
+ std::vector<uint8_t> actualOutput(outputTensorInfo.GetNumElements());
- ret.outputExpected = MakeTensor<uint8_t, 3>(outputTensorInfo, std::vector<uint8_t>(
- {
- 1, 2, 3,
- 4, 5, 6,
- 7, 8, 9,
- 10, 11, 12,
- 13, 14, 15,
- 16, 17, 18,
-
- 19, 20, 21,
- 22, 23, 24,
- 25, 26, 27,
- 28, 29, 30,
- 31, 32, 33,
- 34, 35, 36,
-
- 37, 38, 39,
- 40, 41, 42,
- 43, 44, 45,
- 46, 47, 48,
- 49, 50, 51,
- 52, 53, 54,
- })
- );
-
- auto input1 = MakeTensor<uint8_t, 3>(inputTensorInfo1, std::vector<uint8_t>(
+ std::vector<uint8_t> expectedOutput =
{
1, 2, 3,
4, 5, 6,
@@ -2643,19 +2621,41 @@
28, 29, 30,
31, 32, 33,
34, 35, 36,
- })
- );
- auto input2 = MakeTensor<uint8_t, 3>(inputTensorInfo2, std::vector<uint8_t>(
+ 37, 38, 39,
+ 40, 41, 42,
+ 43, 44, 45,
+ 46, 47, 48,
+ 49, 50, 51,
+ 52, 53, 54
+ };
+
+ std::vector<uint8_t> input1 =
+ {
+ 1, 2, 3,
+ 4, 5, 6,
+ 7, 8, 9,
+ 10, 11, 12,
+ 13, 14, 15,
+ 16, 17, 18,
+
+ 19, 20, 21,
+ 22, 23, 24,
+ 25, 26, 27,
+ 28, 29, 30,
+ 31, 32, 33,
+ 34, 35, 36
+ };
+
+ std::vector<uint8_t> input2 =
{
37, 38, 39,
40, 41, 42,
43, 44, 45,
46, 47, 48,
49, 50, 51,
- 52, 53, 54,
- })
- );
+ 52, 53, 54
+ };
std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0].
ConcatQueueDescriptor::ViewOrigin window1(wOrigin1);
@@ -2693,15 +2693,18 @@
inputHandle2->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
- CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+ CopyDataToITensorHandle(inputHandle1.get(), input1.data());
+ CopyDataToITensorHandle(inputHandle2.get(), input2.data());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
- return ret;
+ return LayerTestResult<uint8_t, 3>(actualOutput,
+ expectedOutput,
+ outputHandle->GetShape(),
+ outputTensorInfo.GetShape());
}
LayerTestResult<uint16_t, 3> ConcatUint16Test(
@@ -2739,9 +2742,9 @@
inputTensorInfo2.SetQuantizationScale(scale);
inputTensorInfo2.SetQuantizationOffset(offset);
- LayerTestResult<uint16_t, 3> ret(outputTensorInfo);
+ std::vector<uint16_t> actualOutput(outputTensorInfo.GetNumElements());
- ret.outputExpected = MakeTensor<uint16_t, 3>(outputTensorInfo, std::vector<uint16_t>(
+ std::vector<uint16_t> expectedOutput =
{
1, 2, 3,
4, 5, 6,
@@ -2762,10 +2765,10 @@
43, 44, 45,
46, 47, 48,
49, 50, 51,
- 52, 53, 54,
- }));
+ 52, 53, 54
+ };
- auto input1 = MakeTensor<uint16_t, 3>(inputTensorInfo1, std::vector<uint16_t>(
+ std::vector<uint16_t> input1 =
{
1, 2, 3,
4, 5, 6,
@@ -2780,9 +2783,9 @@
28, 29, 30,
31, 32, 33,
34, 35, 36,
- }));
+ };
- auto input2 = MakeTensor<uint16_t, 3>(inputTensorInfo2, std::vector<uint16_t>(
+ std::vector<uint16_t> input2 =
{
37, 38, 39,
40, 41, 42,
@@ -2790,7 +2793,7 @@
46, 47, 48,
49, 50, 51,
52, 53, 54,
- }));
+ };
std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0].
ConcatQueueDescriptor::ViewOrigin window1(wOrigin1);
@@ -2829,15 +2832,18 @@
inputHandle2->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
- CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+ CopyDataToITensorHandle(inputHandle1.get(), input1.data());
+ CopyDataToITensorHandle(inputHandle2.get(), input2.data());
workload->PostAllocationConfigure();
workload->Execute();
- CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
- return ret;
+ return LayerTestResult<uint16_t, 3>(actualOutput,
+ expectedOutput,
+ outputHandle->GetShape(),
+ outputTensorInfo.GetShape());
}
LayerTestResult<uint8_t, 1> Concat1dUint8Test(