// // Copyright © 2017 Arm Ltd. All rights reserved. // See LICENSE file in the project root for full license information. // #include "FakeQuantizationLayer.hpp" #include "LayerCloneBase.hpp" #include #include #include namespace armnn { FakeQuantizationLayer::FakeQuantizationLayer(const FakeQuantizationDescriptor& param, const char* name) : LayerWithParameters(1, 1, LayerType::FakeQuantization, param, name) { } std::unique_ptr FakeQuantizationLayer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const { FakeQuantizationQueueDescriptor descriptor; return factory.CreateFakeQuantization(descriptor, PrepInfoAndDesc(descriptor, graph) ); } FakeQuantizationLayer* FakeQuantizationLayer::Clone(Graph& graph) const { return CloneBase(graph, m_Param, GetName()); } void FakeQuantizationLayer::ValidateTensorShapesFromInputs() { ConditionalThrow(GetInputSlot(0).GetConnection() != nullptr, "FakeQuantizationLayer: InputSlot must be connected to an OutputSlot"); ConditionalThrow(GetInputSlot(0).GetConnection()->IsTensorInfoSet(), "FakeQuantizationLayer: TensorInfo must be set on connected OutputSlot."); IOutputSlot* input = GetInputSlot(0).GetConnection(); // input and output shapes are the same TensorShape const& outShape = input->GetTensorInfo().GetShape(); ConditionalThrowIfNotEqual( "FakeQuantizationLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", GetOutputSlot(0).GetTensorInfo().GetShape(), outShape); } } // namespace armnn