1 //
2 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "ElementwiseBinaryLayer.hpp"
7
8 #include "LayerCloneBase.hpp"
9
10 namespace armnn
11 {
12
ElementwiseBinaryLayer(const ElementwiseBinaryDescriptor & param,const char * name)13 ElementwiseBinaryLayer::ElementwiseBinaryLayer(const ElementwiseBinaryDescriptor& param, const char* name)
14 : LayerWithParameters(2, 1, LayerType::ElementwiseBinary, param, name)
15 {
16 }
17
CreateWorkload(const IWorkloadFactory & factory) const18 std::unique_ptr<IWorkload> ElementwiseBinaryLayer::CreateWorkload(const IWorkloadFactory& factory) const
19 {
20 ElementwiseBinaryQueueDescriptor descriptor;
21 SetAdditionalInfo(descriptor);
22
23 return factory.CreateWorkload(LayerType::ElementwiseBinary, descriptor, PrepInfoAndDesc(descriptor));
24 }
25
Clone(Graph & graph) const26 ElementwiseBinaryLayer* ElementwiseBinaryLayer::Clone(Graph& graph) const
27 {
28 return CloneBase<ElementwiseBinaryLayer>(graph, m_Param, GetName());
29 }
30
InferOutputShapes(const std::vector<TensorShape> & inputShapes) const31 std::vector<TensorShape> ElementwiseBinaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
32 {
33 ARMNN_ASSERT(inputShapes.size() == 2);
34 TensorShape input0 = inputShapes[0];
35 TensorShape input1 = inputShapes[1];
36
37 if (inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
38 {
39 input1 = inputShapes[0];
40 input0 = inputShapes[1];
41 }
42
43 unsigned int numDims = input0.GetNumDimensions();
44 unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
45
46 // Get the max of the inputs.
47 std::vector<unsigned int> dims(numDims);
48 for (unsigned int i = shiftedDims; i < numDims; i++)
49 {
50 unsigned int dim0 = input0[i];
51 unsigned int dim1 = input1[i - shiftedDims];
52
53 // Validate inputs are broadcast compatible.
54 ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,
55 "Dimensions should either match or one should be of size 1.");
56
57 dims[i] = std::max(dim0, dim1);
58 }
59
60 // Fill in the rest of the shifted dimensions.
61 for (unsigned int i = 0; i < shiftedDims; i++)
62 {
63 dims[i] = input0[i];
64 }
65
66 return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
67 }
68
ValidateTensorShapesFromInputs()69 void ElementwiseBinaryLayer::ValidateTensorShapesFromInputs()
70 {
71 VerifyLayerConnections(2, CHECK_LOCATION());
72
73 const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
74
75 VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
76
77 auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
78 GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() });
79
80 ARMNN_ASSERT(inferredShapes.size() == 1);
81
82 ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, GetLayerTypeAsCString(GetType()));
83 }
84
ExecuteStrategy(IStrategy & strategy) const85 void ElementwiseBinaryLayer::ExecuteStrategy(IStrategy& strategy) const
86 {
87 strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
88 }
89 } // namespace armnn
90