1 //
2 // Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "TransposeOperator.hpp"
7
ConvertTransposeToTosaOperator(const Layer * layer,const std::vector<const TensorInfo * > & inputs,const std::vector<const TensorInfo * > & outputs,const TransposeDescriptor * transposeDescriptor)8 TosaSerializationBasicBlock* ConvertTransposeToTosaOperator(const Layer* layer,
9 const std::vector<const TensorInfo*>& inputs,
10 const std::vector<const TensorInfo*>& outputs,
11 const TransposeDescriptor* transposeDescriptor)
12 {
13 std::string input0Name = std::string("input0_");
14 std::string outputName = std::string("output0_");
15 std::string blockName = std::string("Op_TRANSPOSE_block_") + GetUniqueTosaMappingID();
16
17 // If a layer is present then the block will be used for execution, so input and output names need to be determined
18 // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
19 if(layer != nullptr)
20 {
21 // Get the layers connected to the input slot and determine unique tensor name.
22 Layer& connectedLayer0 = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
23 input0Name = GenerateUniqueName(connectedLayer0, 0);
24
25 // Determine unique output tensor name.
26 outputName = GenerateUniqueOutputName(*layer, 0);
27 }
28
29 std::vector<int32_t> mappings(transposeDescriptor->m_DimMappings.begin(),
30 transposeDescriptor->m_DimMappings.end());
31 TosaTransposeAttribute attribute(mappings);
32
33 auto* op = new TosaSerializationOperator(Op_TRANSPOSE,
34 Attribute_TransposeAttribute,
35 &attribute,
36 {input0Name},
37 {outputName});
38
39
40 std::vector<TosaSerializationTensor*> tensors;
41
42 // Only add input tensors if connected layer is an input layer.
43 // As intermediate or constant tensors will be created separately.
44 // There also can't be duplicate tensor.
45 if(input0Name.find("input0_") != std::string::npos)
46 {
47 std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
48 DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());
49
50 tensors.push_back(new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}));
51 }
52
53 std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape());
54 DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType());
55
56 tensors.push_back(new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));
57
58 // operatorInputNames/operatorOutputNames ends up being the same as
59 // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings
60 return new TosaSerializationBasicBlock(blockName, // name
61 {op}, // operators
62 tensors, // tensors
63 {input0Name}, // inputs
64 {outputName}); // outputs
65 }