| // |
| // Copyright © 2020 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ConvertFp32ToBf16Layer.hpp" |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| |
| #include <backendsCommon/WorkloadData.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| ConvertFp32ToBf16Layer::ConvertFp32ToBf16Layer(const char* name) |
| : Layer(1, 1, LayerType::ConvertFp32ToBf16, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> ConvertFp32ToBf16Layer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| ConvertFp32ToBf16QueueDescriptor descriptor; |
| return factory.CreateConvertFp32ToBf16(descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| ConvertFp32ToBf16Layer* ConvertFp32ToBf16Layer::Clone(Graph& graph) const |
| { |
| return CloneBase<ConvertFp32ToBf16Layer>(graph, GetName()); |
| } |
| |
| void ConvertFp32ToBf16Layer::ValidateTensorShapesFromInputs(ShapeInferenceMethod shapeInferenceMethod) |
| { |
| IgnoreUnused(shapeInferenceMethod); |
| |
| VerifyLayerConnections(1, CHECK_LOCATION()); |
| |
| auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() }); |
| |
| ARMNN_ASSERT(inferredShapes.size() == 1); |
| |
| ConditionalThrowIfNotEqual<LayerValidationException>( |
| "ConvertFp32ToBf16Layer: TensorShape set on OutputSlot[0] does not match the inferred shape.", |
| GetOutputSlot(0).GetTensorInfo().GetShape(), |
| inferredShapes[0]); |
| } |
| |
| void ConvertFp32ToBf16Layer::Accept(ILayerVisitor& visitor) const |
| { |
| // these conversion layers are only inserted by the |
| // optimizer and so will never be in an input graph. |
| IgnoreUnused(visitor); |
| throw armnn::Exception("ConvertFp32ToBf16Layer should never appear in an input graph"); |
| } |
| |
| } // namespace armnn |