-
Notifications
You must be signed in to change notification settings - Fork 3.5k
[DML EP] Add SkipLayerNormalization #13849
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Merged
Merged
Changes from all commits
Commits
Show all changes
3 commits
Select commit
Hold shift + click to select a range
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
164 changes: 164 additions & 0 deletions
164
...re/providers/dml/DmlExecutionProvider/src/Operators/DmlOperatorSkipLayerNormalization.cpp
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,164 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
|
|
||
| #include "precomp.h" | ||
|
|
||
| namespace Dml | ||
| { | ||
|
|
||
| class DmlOperatorSkipLayerNormalization : public DmlOperator | ||
| { | ||
| public: | ||
| DmlOperatorSkipLayerNormalization(const MLOperatorKernelCreationContext& kernelCreationContext) | ||
| : DmlOperator(kernelCreationContext) | ||
| { | ||
| std::vector<std::optional<uint32_t>> kernelInputIndices = {0, 1, 2, 3, 4}; | ||
|
|
||
| DmlOperator::Initialize( | ||
| kernelCreationContext, | ||
| kernelInputIndices, | ||
| std::nullopt, | ||
| kernelCreationContext.GetTensorShapeDescription().GetInputTensorShape(0), | ||
| std::nullopt, | ||
| kernelCreationContext.GetTensorShapeDescription().GetInputTensorDimensionCount(0)); | ||
|
|
||
| const float epsilon = kernelCreationContext.GetOptionalAttribute<float>(AttrName::Epsilon, DefaultEpsilon); | ||
|
|
||
| int32_t onnxAxis = kernelCreationContext.GetOptionalAttribute<int32_t>(AttrName::Axis, -1); | ||
| uint32_t inputDimCount = kernelCreationContext.GetTensorShapeDescription().GetInputTensorDimensionCount(0); | ||
| onnxAxis = OperatorHelper::HandleNegativeAxis(onnxAxis, inputDimCount); | ||
| std::vector<uint32_t> onnxAxes(inputDimCount - onnxAxis); | ||
| std::iota(onnxAxes.begin(), onnxAxes.end(), onnxAxis); | ||
|
|
||
| assert(m_inputTensorDescs.size() == 5); | ||
| assert(m_outputTensorDescs.size() == 1); | ||
|
|
||
| auto inputDesc = m_inputTensorDescs[0].GetDmlDesc(); | ||
| auto skipDesc = m_inputTensorDescs[1].GetDmlDesc(); | ||
| auto gammaDesc = m_inputTensorDescs[2].GetDmlDesc(); | ||
| auto betaDesc = m_inputTensorDescs[3].GetDmlDesc(); | ||
| auto biasDesc = m_inputTensorDescs[4].GetDmlDesc(); | ||
| auto outputDesc = m_outputTensorDescs[0].GetDmlDesc(); | ||
|
|
||
| TensorDesc inputSkipBiasTensorDesc(m_inputTensorDescs[0].GetDmlDataType(), m_inputTensorDescs[0].GetSizes()); | ||
| DML_TENSOR_DESC inputSkipBiasDmlTensorDesc = inputSkipBiasTensorDesc.GetDmlDesc(); | ||
|
|
||
| DML_ELEMENT_WISE_ADD_OPERATOR_DESC inputSkipAddDesc = {}; | ||
| inputSkipAddDesc.ATensor = &inputDesc; | ||
| inputSkipAddDesc.BTensor = &skipDesc; | ||
| inputSkipAddDesc.OutputTensor = &inputSkipBiasDmlTensorDesc; | ||
| DML_OPERATOR_DESC inputSkipAddOpDesc = { DML_OPERATOR_ELEMENT_WISE_ADD, &inputSkipAddDesc }; | ||
|
|
||
| DML_ELEMENT_WISE_ADD_OPERATOR_DESC inputSkipBiasAddDesc = {}; | ||
| inputSkipBiasAddDesc.ATensor = &inputSkipBiasDmlTensorDesc; | ||
| inputSkipBiasAddDesc.BTensor = &biasDesc; | ||
| inputSkipBiasAddDesc.OutputTensor = &inputSkipBiasDmlTensorDesc; | ||
| DML_OPERATOR_DESC inputSkipBiasAddOpDesc = { DML_OPERATOR_ELEMENT_WISE_ADD, &inputSkipBiasAddDesc }; | ||
|
|
||
| DML_MEAN_VARIANCE_NORMALIZATION1_OPERATOR_DESC mvnDesc = {}; | ||
| mvnDesc.InputTensor = &inputSkipBiasDmlTensorDesc; | ||
| mvnDesc.ScaleTensor = &gammaDesc; | ||
| mvnDesc.BiasTensor = betaDesc.Desc ? &betaDesc : nullptr; | ||
| mvnDesc.OutputTensor = &outputDesc; | ||
| mvnDesc.Axes = onnxAxes.data(); | ||
| mvnDesc.AxisCount = gsl::narrow_cast<uint32_t>(onnxAxes.size()); | ||
| mvnDesc.NormalizeVariance = true; | ||
| mvnDesc.Epsilon = epsilon; | ||
| mvnDesc.FusedActivation = nullptr; | ||
| DML_OPERATOR_DESC mvnOpDesc = { DML_OPERATOR_MEAN_VARIANCE_NORMALIZATION1, &mvnDesc }; | ||
|
|
||
| // Construct the graph | ||
| std::vector<const DML_OPERATOR_DESC*> opDescs; | ||
| opDescs.reserve(3); | ||
|
|
||
| std::vector<DML_INPUT_GRAPH_EDGE_DESC> inputEdges; | ||
| inputEdges.reserve(5); | ||
|
|
||
| std::vector<DML_INTERMEDIATE_GRAPH_EDGE_DESC> intermediateEdges; | ||
| intermediateEdges.reserve(2); | ||
|
|
||
| std::vector<DML_OUTPUT_GRAPH_EDGE_DESC> outputEdges; | ||
| outputEdges.reserve(1); | ||
|
|
||
| // Insert the Input + Skip operation into the graph | ||
| opDescs.push_back(&inputSkipAddOpDesc); | ||
|
|
||
| DML_INPUT_GRAPH_EDGE_DESC dataInputEdge = {}; | ||
| dataInputEdge.GraphInputIndex = 0; | ||
| dataInputEdge.ToNodeIndex = 0; | ||
| dataInputEdge.ToNodeInputIndex = 0; | ||
| inputEdges.push_back(std::move(dataInputEdge)); | ||
|
|
||
| DML_INPUT_GRAPH_EDGE_DESC skipInputEdge = {}; | ||
| skipInputEdge.GraphInputIndex = 1; | ||
| skipInputEdge.ToNodeIndex = 0; | ||
| skipInputEdge.ToNodeInputIndex = 1; | ||
| inputEdges.push_back(std::move(skipInputEdge)); | ||
|
|
||
| // Insert the InputSkip + Bias operation into the graph | ||
| if (biasDesc.Desc) | ||
| { | ||
| opDescs.push_back(&inputSkipBiasAddOpDesc); | ||
|
|
||
| DML_INTERMEDIATE_GRAPH_EDGE_DESC intermediateEdge = {}; | ||
| intermediateEdge.FromNodeIndex = 0; | ||
| intermediateEdge.FromNodeOutputIndex = 0; | ||
| intermediateEdge.ToNodeIndex = 1; | ||
| intermediateEdge.ToNodeInputIndex = 0; | ||
| intermediateEdges.push_back(std::move(intermediateEdge)); | ||
|
|
||
| DML_INPUT_GRAPH_EDGE_DESC biasInputEdge = {}; | ||
| biasInputEdge.GraphInputIndex = 4; | ||
| biasInputEdge.ToNodeIndex = 1; | ||
| biasInputEdge.ToNodeInputIndex = 1; | ||
| inputEdges.push_back(std::move(biasInputEdge)); | ||
| } | ||
|
|
||
| // Insert the MVN operation into the graph | ||
| opDescs.push_back(&mvnOpDesc); | ||
|
|
||
| DML_INTERMEDIATE_GRAPH_EDGE_DESC intermediateEdge = {}; | ||
| intermediateEdge.FromNodeIndex = biasDesc.Desc ? 1 : 0; | ||
| intermediateEdge.FromNodeOutputIndex = 0; | ||
| intermediateEdge.ToNodeIndex = biasDesc.Desc ? 2 : 1; | ||
| intermediateEdge.ToNodeInputIndex = 0; | ||
| intermediateEdges.push_back(std::move(intermediateEdge)); | ||
|
|
||
| DML_INPUT_GRAPH_EDGE_DESC gammaInputEdge = {}; | ||
| gammaInputEdge.GraphInputIndex = 2; | ||
| gammaInputEdge.ToNodeIndex = biasDesc.Desc ? 2 : 1; | ||
| gammaInputEdge.ToNodeInputIndex = 1; | ||
| inputEdges.push_back(std::move(gammaInputEdge)); | ||
|
|
||
| if (betaDesc.Desc) | ||
| { | ||
| DML_INPUT_GRAPH_EDGE_DESC betaInputEdge = {}; | ||
| betaInputEdge.GraphInputIndex = 3; | ||
| betaInputEdge.ToNodeIndex = biasDesc.Desc ? 2 : 1; | ||
| betaInputEdge.ToNodeInputIndex = 2; | ||
| inputEdges.push_back(std::move(betaInputEdge)); | ||
| } | ||
|
|
||
| DML_OUTPUT_GRAPH_EDGE_DESC outputEdge = {}; | ||
| outputEdge.GraphOutputIndex = 0; | ||
| outputEdge.FromNodeIndex = biasDesc.Desc ? 2 : 1; | ||
| outputEdge.FromNodeOutputIndex = 0; | ||
| outputEdges.push_back(std::move(outputEdge)); | ||
|
|
||
| MLOperatorGraphDesc operatorGraphDesc = {}; | ||
| operatorGraphDesc.inputEdgeCount = gsl::narrow_cast<uint32_t>(inputEdges.size()); | ||
| operatorGraphDesc.inputEdges = inputEdges.data(); | ||
| operatorGraphDesc.intermediateEdgeCount = gsl::narrow_cast<uint32_t>(intermediateEdges.size()); | ||
| operatorGraphDesc.intermediateEdges = intermediateEdges.data(); | ||
| operatorGraphDesc.outputEdgeCount = gsl::narrow_cast<uint32_t>(outputEdges.size()); | ||
| operatorGraphDesc.outputEdges = outputEdges.data(); | ||
| operatorGraphDesc.nodeCount = gsl::narrow_cast<uint32_t>(opDescs.size()); | ||
| operatorGraphDesc.nodesAsOpDesc = opDescs.data(); | ||
|
|
||
| SetDmlOperatorGraphDesc(std::move(operatorGraphDesc), kernelCreationContext); | ||
| } | ||
| }; | ||
|
|
||
| DML_OP_DEFINE_CREATION_FUNCTION(SkipLayerNormalization, DmlOperatorSkipLayerNormalization); | ||
|
|
||
| } // namespace Dml |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Uh oh!
There was an error while loading. Please reload this page.