diff options
Diffstat (limited to 'src/armnn/layers/TileLayer.cpp')
| -rw-r--r-- | src/armnn/layers/TileLayer.cpp | 15 |
1 files changed, 8 insertions, 7 deletions
diff --git a/src/armnn/layers/TileLayer.cpp b/src/armnn/layers/TileLayer.cpp index 3c313905fe..d3629002e0 100644 --- a/src/armnn/layers/TileLayer.cpp +++ b/src/armnn/layers/TileLayer.cpp @@ -33,24 +33,25 @@ std::vector<TensorShape> TileLayer::InferOutputShapes(const std::vector<TensorSh { ARMNN_ASSERT(inputShapes.size() == 1); const TensorShape& inputShape = inputShapes[0]; - const std::vector<uint32_t> multipleShape = m_Param.m_Multiples; - std::vector<unsigned int> dimSizes; + uint32_t numberOfDimensions = inputShape.GetNumDimensions(); + std::vector<unsigned int> dimensionSizes; + dimensionSizes.reserve(numberOfDimensions); // Check input shape and multiples have same length and multiply them together to get output shape - if(inputShape.GetNumDimensions() == multipleShape.size()) + if(numberOfDimensions == m_Param.m_Multiples.size()) { - for(uint32_t i = 0; i < inputShape.GetNumDimensions(); ++i) + for(uint32_t i = 0; i < numberOfDimensions; ++i) { - dimSizes.insert(dimSizes.begin(), inputShape[i] * multipleShape[i]); + dimensionSizes.emplace_back(inputShape[i] * m_Param.m_Multiples[i]); } } else { - throw LayerValidationException("TileLayer: input rank and length of multiples are different."); + throw LayerValidationException("TileLayer: input rank and multiples length are different."); } - return std::vector<TensorShape>({TensorShape({inputShape.GetNumElements(), dimSizes.data()})}); + return std::vector<TensorShape>({TensorShape({numberOfDimensions, dimensionSizes.data()})}); } void TileLayer::ValidateTensorShapesFromInputs() |