diff options
Diffstat (limited to 'src/armnn/layers/Convolution2dLayer.cpp')
-rw-r--r-- | src/armnn/layers/Convolution2dLayer.cpp | 38 |
1 files changed, 30 insertions, 8 deletions
diff --git a/src/armnn/layers/Convolution2dLayer.cpp b/src/armnn/layers/Convolution2dLayer.cpp index df971a517d..2fcc4aa755 100644 --- a/src/armnn/layers/Convolution2dLayer.cpp +++ b/src/armnn/layers/Convolution2dLayer.cpp @@ -1,5 +1,5 @@ // -// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved. +// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // @@ -63,15 +63,30 @@ Convolution2dLayer* Convolution2dLayer::Clone(Graph& graph) const std::vector<TensorShape> Convolution2dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const { - ARMNN_ASSERT(inputShapes.size() == 2); + if (inputShapes.size() != 2) + { + throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) + + "\" - should be \"2\"."); + } + const TensorShape& inputShape = inputShapes[0]; const TensorShape filterShape = inputShapes[1]; // If we support multiple batch dimensions in the future, then this assert will need to change. - ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input."); + if (inputShape.GetNumDimensions() != 4) + { + throw armnn::Exception("Convolutions will always have 4D input."); + } + + if (m_Param.m_StrideX == 0) + { + throw armnn::Exception("m_StrideX cannot be 0."); + } - ARMNN_ASSERT( m_Param.m_StrideX > 0); - ARMNN_ASSERT( m_Param.m_StrideY > 0); + if (m_Param.m_StrideY == 0) + { + throw armnn::Exception("m_StrideY cannot be 0."); + } DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout); @@ -107,14 +122,21 @@ void Convolution2dLayer::ValidateTensorShapesFromInputs() VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); - ARMNN_ASSERT_MSG(GetInputSlot(1).GetConnection(), - "Convolution2dLayer: Weights should be connected to input slot 1."); + if (!GetInputSlot(1).GetConnection()) + { + throw armnn::NullPointerException("Convolution2dLayer: Weights should be connected to input slot 1."); + } std::vector<TensorShape> inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape(), GetInputSlot(1).GetTensorInfo().GetShape() }); - ARMNN_ASSERT(inferredShapes.size() == 1); + if (inferredShapes.size() != 1) + { + throw armnn::Exception("inferredShapes has " + + std::to_string(inferredShapes.size()) + + " elements - should only have 1."); + } ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Convolution2dLayer"); } |