| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "StridedSliceLayer.hpp" |
| |
| #include "LayerCloneBase.hpp" |
| |
| #include <backendsCommon/WorkloadData.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| |
| #include <boost/numeric/conversion/cast.hpp> |
| |
| namespace armnn |
| { |
| |
| StridedSliceLayer::StridedSliceLayer(const armnn::StridedSliceDescriptor& param, const char* name) |
| : LayerWithParameters(1, 1, LayerType::StridedSlice, param, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> StridedSliceLayer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| StridedSliceQueueDescriptor descriptor; |
| |
| descriptor.m_Parameters.m_Begin = m_Param.m_Begin; |
| descriptor.m_Parameters.m_End = m_Param.m_End; |
| descriptor.m_Parameters.m_Stride = m_Param.m_Stride; |
| |
| // Optional parameters |
| descriptor.m_Parameters.m_BeginMask = m_Param.m_BeginMask; |
| descriptor.m_Parameters.m_EndMask = m_Param.m_EndMask; |
| descriptor.m_Parameters.m_EllipsisMask = m_Param.m_EllipsisMask; |
| descriptor.m_Parameters.m_NewAxisMask = m_Param.m_NewAxisMask; |
| descriptor.m_Parameters.m_ShrinkAxisMask = m_Param.m_ShrinkAxisMask; |
| |
| return factory.CreateStridedSlice(descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| StridedSliceLayer* StridedSliceLayer::Clone(Graph& graph) const |
| { |
| return CloneBase<StridedSliceLayer>(graph, m_Param, GetName()); |
| } |
| |
| std::vector<TensorShape> StridedSliceLayer::InferOutputShapes( |
| const std::vector<TensorShape>& inputShapes) const |
| { |
| ARMNN_ASSERT(inputShapes.size() == 1); |
| |
| TensorShape inputShape = inputShapes[0]; |
| std::vector<unsigned int> outputShape; |
| unsigned int amountDimShrunk{0}; |
| |
| for (unsigned int i = 0; i < inputShape.GetNumDimensions(); i++) |
| { |
| int stride = m_Param.m_Stride[i]; |
| int start = m_Param.GetStartForAxis(inputShape, i); |
| int stop = m_Param.GetStopForAxis(inputShape, i, start); |
| |
| if (m_Param.m_ShrinkAxisMask & (1 << i)) |
| { |
| amountDimShrunk+=1; |
| |
| // If the difference between the start point and the end point of the slice on an axis being shrunk |
| // is greater than 1 then throw an error as the output will not be large enough to hold the slice |
| if (((m_Param.m_Begin[i] - m_Param.m_End[i]) > 1) || ((m_Param.m_Begin[i] - m_Param.m_End[i]) < -1)) |
| { |
| throw LayerValidationException( |
| "StridedSlice: Attempting to take a larger slice than can fit in inferred output"); |
| } |
| |
| if (stride < 0) |
| { |
| throw LayerValidationException( |
| "StridedSlice: Stride can not be negative with Shrink Axis Mask set."); |
| } |
| continue; |
| } |
| |
| int newSize = stride > 0 ? ((stop - start) + stride - 1) / stride : |
| ((start - stop) - stride - 1) / -stride; |
| |
| newSize = std::max(0, newSize); |
| |
| outputShape.push_back(boost::numeric_cast<unsigned int>(newSize)); |
| } |
| |
| if (outputShape.size() == 0 && (inputShape.GetNumDimensions() - amountDimShrunk) == 0) |
| { |
| outputShape.push_back(1); |
| } |
| |
| return std::vector<TensorShape>({ |
| TensorShape(boost::numeric_cast<unsigned int>(outputShape.size()), &outputShape[0]) }); |
| } |
| |
| void StridedSliceLayer::ValidateTensorShapesFromInputs(ShapeInferenceMethod shapeInferenceMethod) |
| { |
| IgnoreUnused(shapeInferenceMethod); |
| |
| VerifyLayerConnections(1, CHECK_LOCATION()); |
| |
| auto inferredShapes = InferOutputShapes({GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape()}); |
| |
| ARMNN_ASSERT(inferredShapes.size() == 1); |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "StridedSlice: TensorShape set on OutputSlot[0] does not match the inferred shape.", |
| GetOutputSlot(0).GetTensorInfo().GetShape(), |
| inferredShapes[0]); |
| } |
| |
| void StridedSliceLayer::Accept(ILayerVisitor& visitor) const |
| { |
| visitor.VisitStridedSliceLayer(this, GetParameters(), GetName()); |
| } |
| |
| } // namespace armnn |
