Remove using namespace NeoML from public headers (#1025)

Signed-off-by: Kirill Golikov <kirill.golikov@abbyy.com>
Co-authored-by: Stanislav Angeliuk <59917951+SAngeliuk@users.noreply.github.com>

NeoML/include/NeoML/NeoML.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2023 ABBYY
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -149,6 +149,3 @@ limitations under the License.
 #endif //!NEOML_COMPACT
 #include <NeoML/ArchiveFile.h>
 
-#ifndef NO_NEOML_NAMESPACE
-using namespace NeoML;
-#endif

NeoML/test/src/LAMBSolverTest.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2021 ABBYY Production LLC
+/* Copyright © 2021-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -18,6 +18,8 @@ limitations under the License.
 
 #include <TestFixture.h>
 
+using namespace NeoML;
+
 static NeoML::CFullyConnectedLayer* createSimpleNetwork( NeoML::CDnn& dnn )
 {
     // Single FC architecture

NeoML/test/src/TestFixture.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2023 ABBYY
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -20,6 +20,7 @@ limitations under the License.
 #include <cmath>
 
 namespace NeoMLTest {
+using namespace NeoML;
 
 CString GetTestDataFilePath( const CString& relativePath, const CString& fileName );
 

NeoOnnx/include/NeoOnnx/NeoOnnxImport.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -37,7 +37,7 @@ struct NEOONNX_API CImportSettings {
 
 	// After the import the net is passed to NeoML::OptimizeDnn
 	// The settings used by OptimizeDnn
-	CDnnOptimizationSettings DnnOptimizationSettings{};
+	NeoML::CDnnOptimizationSettings DnnOptimizationSettings{};
 };
 
 // Information about ONNX optimizations
@@ -68,7 +68,7 @@ struct NEOONNX_API CImportedModelInfo {
 	// 1. ONNX-only optimizations. Mostly they just removed artifacts from ONNX generation. See OnnxOptimizationReport.
 	// 2. NeoML::OptimizeDnn. See OptimizationReport.
 	COnnxOptimizationReport OnnxOptimizationReport;
-	CDnnOptimizationReport OptimizationReport;
+	NeoML::CDnnOptimizationReport OptimizationReport;
 };
 
 // The load functions build CDnn based on ONNX in the following way:

NeoOnnx/include/NeoOnnx/TensorLayout.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -19,6 +19,7 @@ limitations under the License.
 #include <NeoML/NeoML.h>
 
 namespace NeoOnnx {
+using TBlobDim = NeoML::TBlobDim;
 
 // Desribes how the tensor is represented in memory
 // tensorLayout[i] is the blob dimension, where i'th onnx axis is located
@@ -43,6 +44,7 @@ class CTensorLayout: public CFastArray<TBlobDim, 8> {
 
 inline CTensorLayout::CTensorLayout( int dimCount )
 {
+	using namespace NeoML;
 	SetBufferSize( dimCount );
 	// Next dimensions are educated guesses
 	// If they'll match future layers then it will save one transform operation

NeoOnnx/src/AttributeGetters.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -18,6 +18,8 @@ limitations under the License.
 #include "TensorUtils.h"
 
 namespace NeoOnnx {
+using TBlobType = NeoML::TBlobType;
+using CBlobDesc = NeoML::CBlobDesc;
 
 // This file contains getters for different types of onnx attributes
 
@@ -113,7 +115,7 @@ inline void GetAttributeValue<CPtr<CDataTensor>>( const onnx::AttributeProto& at
 	}
 	CPtr<CDnnBlob> resultBlob = CDnnBlob::CreateBlob( value->Data()->GetMathEngine(), resultDataType, desc );
 
-	if( resultDataType == CT_Float ) {
+	if( resultDataType == NeoML::CT_Float ) {
 		LoadBlobData<float>( attribute.t(), *resultBlob );
 	} else {
 		LoadBlobData<int>( attribute.t(), *resultBlob );

NeoOnnx/src/GraphInput.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -22,6 +22,8 @@ limitations under the License.
 #include "TensorUtils.h"
 #include "NeoOnnxCheck.h"
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 CGraphInput::CGraphInput( const onnx::ValueInfoProto& input ) :

NeoOnnx/src/GraphInput.h

@@ -38,7 +38,7 @@ class CGraphInput {
 	// Adds corresponding source layer to the dnn and returns its output as a user tensor
 	// If layout is given, it will be used as a layout for this tensor
 	// If layout is not given then CTensorLayout::IOLayout( dimCount ) is used
-	CPtr<const CUserTensor> AddSourceLayer( CDnn& dnn, const CTensorLayout* layout ) const;
+	CPtr<const CUserTensor> AddSourceLayer( NeoML::CDnn& dnn, const CTensorLayout* layout ) const;
 
 private:
 	// Input name

NeoOnnx/src/Operators/ActivationOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2021 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -21,6 +21,8 @@ limitations under the License.
 #include "ActivationOperator.h"
 #include "NeoOnnxCheck.h"
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 CActivationOperatorBase::CActivationOperatorBase( const onnx::NodeProto& onnxNode, int opsetVersion,

NeoOnnx/src/Operators/ActivationOperator.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2021 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -23,15 +23,15 @@ namespace NeoOnnx {
 class CActivationOperatorBase : public CLayerOperator {
 public:
 	CActivationOperatorBase( const onnx::NodeProto& onnxNode, int opsetVersion,
-		TActivationFunction activation );
+		NeoML::TActivationFunction activation );
 
 protected:
 	// CLayerOperator methods
 	void AddLayers( const CTensorArray& inputs, CDnn& dnn, CTensorArray& outputs ) const override;
 
 private:
 	// Activation function which is applied to the input by this operator
-	const TActivationFunction activation;
+	const NeoML::TActivationFunction activation;
 };
 
 //---------------------------------------------------------------------------------------------------------------------

NeoOnnx/src/Operators/ConvOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -22,6 +22,8 @@ limitations under the License.
 #include "NeoOnnxCheck.h"
 #include "TensorUtils.h"
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 // Gets kernel shape

NeoOnnx/src/Operators/EltwiseOperator.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -22,6 +22,7 @@ limitations under the License.
 #include <NeoML/Dnn/Layers/Onnx/OnnxEltwiseLayer.h>
 
 namespace NeoOnnx {
+using COnnxEltwiseLayer = NeoML::COnnxEltwiseLayer;
 
 // Base class for operators which perform eltwise operations
 template<COnnxEltwiseLayer::TOperation Operation>

NeoOnnx/src/Operators/GlobalPoolOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2023 ABBYY
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -21,6 +21,8 @@ limitations under the License.
 
 #include "onnx.pb.h"
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 // Gets the maximum number of inputs in the given opset version

NeoOnnx/src/Operators/OneHotOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2022 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -23,6 +23,8 @@ limitations under the License.
 
 #include <NeoML/Dnn/Layers/Onnx/OnnxOneHotLayer.h>
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 COneHotOperator::COneHotOperator( const onnx::NodeProto& oneHot, int opsetVersion ) :

NeoOnnx/src/Operators/PadOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2023 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -22,6 +22,8 @@ limitations under the License.
 #include "NeoOnnxCheck.h"
 #include "TensorUtils.h"
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 CPadOperator::CPadOperator( const onnx::NodeProto& pad, int opsetVersion ) :

NeoOnnx/src/Operators/PoolOperator.h

@@ -30,7 +30,7 @@ class CPoolOperatorBase : public CLayerOperator {
 	// AddLayers implementation for the given padding value and pooling layer
 	// The derivatives should call this method from their AddLayers
 	void AddLayersImpl( const CTensorArray& inputs, float padValue,
-		CPoolingLayer& layer, CDnn& dnn, CTensorArray& outputs ) const;
+		NeoML::CPoolingLayer& layer, CDnn& dnn, CTensorArray& outputs ) const;
 
 private:
 	// Padding mode

NeoOnnx/src/Operators/ResizeOperator.h

@@ -29,8 +29,8 @@ class CResizeOperator : public CLayerOperator {
 	void AddLayers( const CTensorArray& input, CDnn& dnn, CTensorArray& outputs ) const override;
 
 private:
-	TInterpolationCoords getInterpolationCoords() const;
-	TInterpolationRound getInterpolationRound() const;
+	NeoML::TInterpolationCoords getInterpolationCoords() const;
+	NeoML::TInterpolationRound getInterpolationRound() const;
 };
 
 } // namespace NeoOnnx

NeoOnnx/src/Operators/SliceOperator.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -26,6 +26,8 @@ limitations under the License.
 
 #include <NeoML/Dnn/Layers/Onnx/OnnxSliceLayer.h>
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 CSliceOperator::CSliceOperator( const onnx::NodeProto& slice, int opsetVersion ) :

NeoOnnx/src/Optimization/GELUOptimizer.cpp

@@ -1,4 +1,4 @@
-/* Copyright © 2023 ABBYY
+/* Copyright © 2023-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -22,6 +22,8 @@ limitations under the License.
 #include "GELUOptimizer.h"
 #include <NeoML/Dnn/Layers/Onnx/OnnxEltwiseLayer.h>
 
+using namespace NeoML;
+
 namespace NeoOnnx {
 
 namespace optimization {

NeoOnnx/src/Optimization/Graph.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2023 ABBYY
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -23,9 +23,9 @@ namespace optimization {
 
 // NeoOnnx::optimization aliases for NeoML::optimization
 using CGraph = NeoML::optimization::CGraph;
-template<typename TLayer = CBaseLayer>
+template<typename TLayer = NeoML::CBaseLayer>
 using CLayerInput = NeoML::optimization::CLayerInput<TLayer>;
-template<typename TLayer = CBaseLayer>
+template<typename TLayer = NeoML::CBaseLayer>
 using CLayerOutput = NeoML::optimization::CLayerOutput<TLayer>;
 
 } // namespace optimization

NeoOnnx/src/Tensor.h

@@ -1,4 +1,4 @@
-/* Copyright © 2017-2020 ABBYY Production LLC
+/* Copyright © 2017-2024 ABBYY
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -18,6 +18,9 @@ limitations under the License.
 #include <NeoOnnx/TensorLayout.h>
 
 namespace NeoOnnx {
+using IMathEngine = NeoML::IMathEngine;
+using CBaseLayer = NeoML::CBaseLayer;
+using CDnnBlob = NeoML::CDnnBlob;
 
 // Tensor shape
 typedef CFastArray<int, 8> CTensorShape;
@@ -95,7 +98,7 @@ inline bool CTensorBase::checkTensorLayout() const
 	// Check that every dimension is valid and used only once
 	int mask = 0;
 	for( int dimIndex = 0; dimIndex < layout.Size(); ++dimIndex ) {
-		if( layout[dimIndex] < BD_BatchLength || layout[dimIndex] > BD_Count
+		if( layout[dimIndex] < NeoML::BD_BatchLength || layout[dimIndex] > NeoML::BD_Count
 			|| ( mask & ( 1 << layout[dimIndex] ) ) != 0 )
 		{
 			return false;
@@ -188,7 +191,7 @@ class CDataTensor : public CTensorBase {
 
 inline CDataTensor::CDataTensor( IMathEngine& mathEngine ) :
 	CTensorBase( CTensorLayout(), TTensorType::Data ),
-	data( CDnnBlob::CreateVector( mathEngine, CT_Float, 1 ) )
+	data( CDnnBlob::CreateVector( mathEngine, NeoML::CT_Float, 1 ) )
 {
 	NeoPresume( checkTensorLayout() );
 }
@@ -205,7 +208,7 @@ inline CDataTensor::CDataTensor( const CTensorLayout& layout, const CDnnBlob& _d
 inline bool CDataTensor::checkTensorLayout() const
 {
 	// Checking that shape, layout and CDnnBlob are matching
-	for( TBlobDim i = BD_BatchLength; i < BD_Count; ++i ) {
+	for( TBlobDim i = NeoML::BD_BatchLength; i < NeoML::BD_Count; ++i ) {
 		const int index = Layout().Find( i );
 		if( index == NotFound && data->DimSize( i ) != 1 ) {
 			return false;