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Silenced a few compilation warnings

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Generalized a TensorMap constructor
This commit is contained in:
Benoit Steiner 2014-10-16 14:52:50 -07:00
parent 94e47798f4
commit ae697b471c
13 changed files with 24 additions and 22 deletions
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1
unsupported/Eigen/CXX11/src/Tensor/Tensor.h
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@ -1,6 +1,7 @@
// This file is part of Eigen, a lightweight C++ template library // This file is part of Eigen, a lightweight C++ template library
// for linear algebra. // for linear algebra.
// //
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
// Copyright (C) 2013 Christian Seiler <christian@iwakd.de> // Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
// //
// This Source Code Form is subject to the terms of the Mozilla // This Source Code Form is subject to the terms of the Mozilla

2
unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
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@ -114,7 +114,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
m_impl.evalSubExprsIfNeeded(NULL); m_impl.evalSubExprsIfNeeded(NULL);
return true; return true;
} }

2
unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
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@ -136,7 +136,7 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
m_impl.evalSubExprsIfNeeded(NULL); m_impl.evalSubExprsIfNeeded(NULL);
return true; return true;
} }

4
unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
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@ -140,7 +140,7 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
// TODO(phli): Add short-circuit memcpy evaluation if underlying data are linear? // TODO(phli): Add short-circuit memcpy evaluation if underlying data are linear?
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/)
{ {
m_leftImpl.evalSubExprsIfNeeded(NULL); m_leftImpl.evalSubExprsIfNeeded(NULL);
m_rightImpl.evalSubExprsIfNeeded(NULL); m_rightImpl.evalSubExprsIfNeeded(NULL);
@ -202,13 +202,13 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
Scalar* data() const { return NULL; } Scalar* data() const { return NULL; }
protected: protected:
const Axis m_axis;
Dimensions m_dimensions; Dimensions m_dimensions;
array<Index, NumDims> m_outputStrides; array<Index, NumDims> m_outputStrides;
array<Index, NumDims> m_leftStrides; array<Index, NumDims> m_leftStrides;
array<Index, NumDims> m_rightStrides; array<Index, NumDims> m_rightStrides;
TensorEvaluator<LeftArgType, Device> m_leftImpl; TensorEvaluator<LeftArgType, Device> m_leftImpl;
TensorEvaluator<RightArgType, Device> m_rightImpl; TensorEvaluator<RightArgType, Device> m_rightImpl;
const Axis m_axis;
}; };

4
unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
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@ -671,10 +671,10 @@ struct TensorContractionEvaluatorBase
Index m_j_size; Index m_j_size;
Index m_k_size; Index m_k_size;
const Device& m_device;
Scalar* m_result;
TensorEvaluator<LeftArgType, Device> m_leftImpl; TensorEvaluator<LeftArgType, Device> m_leftImpl;
TensorEvaluator<RightArgType, Device> m_rightImpl; TensorEvaluator<RightArgType, Device> m_rightImpl;
const Device& m_device;
Scalar* m_result;
}; };

2
unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
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@ -230,7 +230,7 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr
}; };
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_kernel(NULL), m_kernelArg(op.kernelExpression()), m_local_kernel(false), m_device(device) : m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_kernelArg(op.kernelExpression()), m_kernel(NULL), m_local_kernel(false), m_device(device)
{ {
const typename TensorEvaluator<InputArgType, Device>::Dimensions& input_dims = m_inputImpl.dimensions(); const typename TensorEvaluator<InputArgType, Device>::Dimensions& input_dims = m_inputImpl.dimensions();
const typename TensorEvaluator<KernelArgType, Device>::Dimensions& kernel_dims = m_kernelImpl.dimensions(); const typename TensorEvaluator<KernelArgType, Device>::Dimensions& kernel_dims = m_kernelImpl.dimensions();

3
unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
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@ -64,7 +64,8 @@ template<typename PlainObjectType, int Options_> class TensorMap : public Tensor
} }
#endif #endif
inline TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions) template <typename Dimensions>
inline TensorMap(PointerArgType dataPtr, const Dimensions& dimensions)
: m_data(dataPtr), m_dimensions(dimensions) : m_data(dataPtr), m_dimensions(dimensions)
{ } { }

6
unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
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@ -130,8 +130,8 @@ struct TensorEvaluator<const TensorReshapingOp<NewDimensions, ArgType>, Device>
Scalar* data() const { return m_impl.data(); } Scalar* data() const { return m_impl.data(); }
protected: protected:
NewDimensions m_dimensions;
TensorEvaluator<ArgType, Device> m_impl; TensorEvaluator<ArgType, Device> m_impl;
NewDimensions m_dimensions;
}; };
@ -381,13 +381,13 @@ struct TensorEvaluator<const TensorSlicingOp<StartIndices, Sizes, ArgType>, Devi
return inputIndex; return inputIndex;
} }
Dimensions m_dimensions;
array<Index, NumDims> m_outputStrides; array<Index, NumDims> m_outputStrides;
array<internal::TensorIntDivisor<Index>, NumDims> m_fastOutputStrides; array<internal::TensorIntDivisor<Index>, NumDims> m_fastOutputStrides;
array<Index, NumDims> m_inputStrides; array<Index, NumDims> m_inputStrides;
const StartIndices m_offsets;
TensorEvaluator<ArgType, Device> m_impl; TensorEvaluator<ArgType, Device> m_impl;
const Device& m_device; const Device& m_device;
Dimensions m_dimensions;
const StartIndices m_offsets;
}; };

2
unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
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@ -215,11 +215,11 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
return rslt; return rslt;
} }
PaddingDimensions m_padding;
Dimensions m_dimensions; Dimensions m_dimensions;
array<Index, NumDims+1> m_outputStrides; array<Index, NumDims+1> m_outputStrides;
array<Index, NumDims> m_inputStrides; array<Index, NumDims> m_inputStrides;
TensorEvaluator<ArgType, Device> m_impl; TensorEvaluator<ArgType, Device> m_impl;
PaddingDimensions m_padding;
}; };

2
unsupported/Eigen/CXX11/src/Tensor/TensorPatch.h
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@ -120,7 +120,7 @@ struct TensorEvaluator<const TensorPatchOp<PatchDim, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
m_impl.evalSubExprsIfNeeded(NULL); m_impl.evalSubExprsIfNeeded(NULL);
return true; return true;
} }

4
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
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@ -152,7 +152,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
m_impl.evalSubExprsIfNeeded(NULL); m_impl.evalSubExprsIfNeeded(NULL);
return true; return true;
} }
@ -217,8 +217,8 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
array<Index, NumDims> m_preservedStrides; array<Index, NumDims> m_preservedStrides;
array<Index, NumReducedDims> m_reducedStrides; array<Index, NumReducedDims> m_reducedStrides;
array<Index, NumReducedDims> m_reducedDims; array<Index, NumReducedDims> m_reducedDims;
Op m_reducer;
TensorEvaluator<ArgType, Device> m_impl; TensorEvaluator<ArgType, Device> m_impl;
Op m_reducer;
}; };
} // end namespace Eigen } // end namespace Eigen

2
unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
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@ -131,7 +131,7 @@ struct TensorEvaluator<const TensorShufflingOp<Shuffle, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) { EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
m_impl.evalSubExprsIfNeeded(NULL); m_impl.evalSubExprsIfNeeded(NULL);
return true; return true;
} }

10
unsupported/test/cxx11_tensor_fixed_size.cpp
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@ -32,10 +32,10 @@ static void test_1d()
vec1(5) = 42.0; vec2(5) = 5.0; vec1(5) = 42.0; vec2(5) = 5.0;
float data3[6]; float data3[6];
TensorMap<TensorFixedSize<float, Sizes<6> > > vec3(data3, 6); TensorMap<TensorFixedSize<float, Sizes<6> > > vec3(data3, Sizes<6>());
vec3 = vec1.sqrt(); vec3 = vec1.sqrt();
float data4[6]; float data4[6];
TensorMap<TensorFixedSize<float, Sizes<6>, RowMajor> > vec4(data4, 6); TensorMap<TensorFixedSize<float, Sizes<6>, RowMajor> > vec4(data4, Sizes<6>());
vec4 = vec2.sqrt(); vec4 = vec2.sqrt();
VERIFY_IS_EQUAL((vec3.size()), 6); VERIFY_IS_EQUAL((vec3.size()), 6);
@ -68,9 +68,9 @@ static void test_1d()
static void test_2d() static void test_2d()
{ {
float data1[6]; float data1[6];
TensorMap<TensorFixedSize<float, Sizes<2, 3> >> mat1(data1,2,3); TensorMap<TensorFixedSize<float, Sizes<2, 3> >> mat1(data1, Sizes<2, 3>());
float data2[6]; float data2[6];
TensorMap<TensorFixedSize<float, Sizes<2, 3>, RowMajor>> mat2(data2,2,3); TensorMap<TensorFixedSize<float, Sizes<2, 3>, RowMajor>> mat2(data2, Sizes<2, 3>());
VERIFY_IS_EQUAL((mat1.size()), 2*3); VERIFY_IS_EQUAL((mat1.size()), 2*3);
// VERIFY_IS_EQUAL((mat1.dimension(0)), 2); // VERIFY_IS_EQUAL((mat1.dimension(0)), 2);
@ -166,7 +166,7 @@ static void test_array()
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) { for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) { for (int k = 0; k < 7; ++k) {
mat1(array<ptrdiff_t, 3>(i,j,k)) = val; mat1(array<ptrdiff_t, 3>{{i,j,k}}) = val;
val += 1.0; val += 1.0;
} }
} }