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Extract Epsilon Attribute from LayerNormalization Subgraph #2639

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Merged
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Dec 12, 2019
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Extract Epsilon Attribute from LayerNormalization Subgraph #2639

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10 changes: 9 additions & 1 deletion onnxruntime/core/optimizer/layer_norm_fusion.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,6 @@ Status LayerNormFusion::ApplyImpl(Graph& graph, bool& modified, int graph_level,
continue;
}
nodes_to_remove.push_back(add2_node);

// Traceback the add node to find reduceMean --> add
const Node* p_reduce_mean2 = nullptr;

Expand Down Expand Up @@ -255,6 +254,15 @@ Status LayerNormFusion::ApplyImpl(Graph& graph, bool& modified, int graph_level,
layer_norm_input_defs,
{}, {}, kOnnxDomain);

// Get constant "epsilon" from "Add2" node if available. Else, default value will be used.
const ONNX_NAMESPACE::TensorProto* tensor_proto = graph_utils::GetConstantInitializer(graph, add2_node.MutableInputDefs()[1]->Name());
if (tensor_proto != nullptr) {
if (tensor_proto->data_type() == ONNX_NAMESPACE::TensorProto_DataType_FLOAT) {
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@tianleiwu tianleiwu Dec 12, 2019

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Might need add FP16 data type support. You can use a FP16 model to test whether it is needed.

const float* val = onnxruntime::make_unique<Initializer>(*tensor_proto)->data<float>();
layer_norm_node.AddAttribute("epsilon", val[0]);
}
}

// Assign provider to this new node. Provider should be same as the provider for old node.
layer_norm_node.SetExecutionProviderType(reduce_mean_node.GetExecutionProviderType());

Expand Down