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Misc api improvements and cleanups

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This commit is contained in:
Benoit Steiner 2014-08-23 14:35:41 -07:00
parent fb5c1e9097
commit 36fffe48f7
4 changed files with 55 additions and 19 deletions
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9
unsupported/Eigen/CXX11/src/Tensor/TensorDeviceType.h
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@ -27,6 +27,10 @@ struct DefaultDevice {
EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const { EIGEN_STRONG_INLINE void memset(void* buffer, int c, size_t n) const {
::memset(buffer, c, n); ::memset(buffer, c, n);
} }
EIGEN_STRONG_INLINE size_t numThreads() const {
return 1;
}
}; };
@ -115,6 +119,11 @@ struct GpuDevice {
cudaMemsetAsync(buffer, c, n, *stream_); cudaMemsetAsync(buffer, c, n, *stream_);
} }
EIGEN_STRONG_INLINE size_t numThreads() const {
// Fixme:
return 32;
}
private: private:
// TODO: multigpu. // TODO: multigpu.
const cudaStream_t* stream_; const cudaStream_t* stream_;

26
unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
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@ -195,6 +195,32 @@ struct DSizes : array<DenseIndex, NumDims> {
} }
EIGEN_DEVICE_FUNC explicit DSizes(const array<DenseIndex, NumDims>& a) : Base(a) { } EIGEN_DEVICE_FUNC explicit DSizes(const array<DenseIndex, NumDims>& a) : Base(a) { }
EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0) {
(*this)[0] = i0;
}
EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0, const DenseIndex i1) {
(*this)[0] = i0;
(*this)[1] = i1;
}
EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2) {
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
}
EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3) {
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
(*this)[3] = i3;
}
EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3, const DenseIndex i4) {
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
(*this)[3] = i3;
(*this)[4] = i4;
}
DSizes& operator = (const array<DenseIndex, NumDims>& other) { DSizes& operator = (const array<DenseIndex, NumDims>& other) {
*static_cast<Base*>(this) = other; *static_cast<Base*>(this) = other;
return *this; return *this;

2
unsupported/test/CMakeLists.txt
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@ -110,7 +110,7 @@ if(EIGEN_TEST_CXX11)
ei_add_test(cxx11_tensor_lvalue "-std=c++0x") ei_add_test(cxx11_tensor_lvalue "-std=c++0x")
ei_add_test(cxx11_tensor_map "-std=c++0x") ei_add_test(cxx11_tensor_map "-std=c++0x")
ei_add_test(cxx11_tensor_broadcasting "-std=c++0x") ei_add_test(cxx11_tensor_broadcasting "-std=c++0x")
# ei_add_test(cxx11_tensor_morphing "-std=c++0x") ei_add_test(cxx11_tensor_morphing "-std=c++0x")
ei_add_test(cxx11_tensor_padding "-std=c++0x") ei_add_test(cxx11_tensor_padding "-std=c++0x")
# ei_add_test(cxx11_tensor_shuffling "-std=c++0x") # ei_add_test(cxx11_tensor_shuffling "-std=c++0x")
ei_add_test(cxx11_tensor_striding "-std=c++0x") ei_add_test(cxx11_tensor_striding "-std=c++0x")

37
unsupported/test/cxx11_tensor_morphing.cpp
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@ -52,7 +52,7 @@ static void test_reshape_in_expr() {
TensorMap<Tensor<float, 5>> tensor2(m2.data(), 3,5,7,11,13); TensorMap<Tensor<float, 5>> tensor2(m2.data(), 3,5,7,11,13);
Tensor<float, 2>::Dimensions newDims1{{2,3*5*7*11}}; Tensor<float, 2>::Dimensions newDims1{{2,3*5*7*11}};
Tensor<float, 2>::Dimensions newDims2{{3*5*7*11,13}}; Tensor<float, 2>::Dimensions newDims2{{3*5*7*11,13}};
array<Tensor<float, 1>::DimensionPair, 1> contract_along{{1, 0}}; array<Tensor<float, 1>::DimensionPair, 1> contract_along{{std::make_pair(1, 0)}};
Tensor<float, 2> tensor3(2,13); Tensor<float, 2> tensor3(2,13);
tensor3 = tensor1.reshape(newDims1).contract(tensor2.reshape(newDims2), contract_along); tensor3 = tensor1.reshape(newDims1).contract(tensor2.reshape(newDims2), contract_along);
@ -74,7 +74,8 @@ static void test_reshape_as_lvalue()
Tensor<float, 3>::Dimensions dim{{2,3,7}}; Tensor<float, 3>::Dimensions dim{{2,3,7}};
tensor2d.reshape(dim) = tensor; tensor2d.reshape(dim) = tensor;
Tensor<float, 5> tensor5d(2,3,1,7,1); float scratch[2*3*1*7*1];
TensorMap<Tensor<float, 5>> tensor5d(scratch, 2,3,1,7,1);
tensor5d.reshape(dim).device(Eigen::DefaultDevice()) = tensor; tensor5d.reshape(dim).device(Eigen::DefaultDevice()) = tensor;
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {
@ -94,14 +95,14 @@ static void test_simple_slice()
tensor.setRandom(); tensor.setRandom();
Tensor<float, 5> slice1(1,1,1,1,1); Tensor<float, 5> slice1(1,1,1,1,1);
Eigen::DSizes<ptrdiff_t, 5> indices(Eigen::array<ptrdiff_t, 5>(1,2,3,4,5)); Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5);
Eigen::DSizes<ptrdiff_t, 5> sizes(Eigen::array<ptrdiff_t, 5>(1,1,1,1,1)); Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1);
slice1 = tensor.slice(indices, sizes); slice1 = tensor.slice(indices, sizes);
VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5)); VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
Tensor<float, 5> slice2(1,1,2,2,3); Tensor<float, 5> slice2(1,1,2,2,3);
Eigen::DSizes<ptrdiff_t, 5> indices2(Eigen::array<ptrdiff_t, 5>(1,1,3,4,5)); Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
Eigen::DSizes<ptrdiff_t, 5> sizes2(Eigen::array<ptrdiff_t, 5>(1,1,2,2,3)); Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
slice2 = tensor.slice(indices2, sizes2); slice2 = tensor.slice(indices2, sizes2);
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 2; ++j) { for (int j = 0; j < 2; ++j) {
@ -124,12 +125,12 @@ static void test_slice_in_expr() {
TensorMap<Tensor<float, 2>> tensor1(m1.data(), 7, 7); TensorMap<Tensor<float, 2>> tensor1(m1.data(), 7, 7);
TensorMap<Tensor<float, 2>> tensor2(m2.data(), 3, 3); TensorMap<Tensor<float, 2>> tensor2(m2.data(), 3, 3);
Tensor<float, 2> tensor3(3,1); Tensor<float, 2> tensor3(3,1);
array<Tensor<float, 1>::DimensionPair, 1> contract_along{{1, 0}}; array<Tensor<float, 1>::DimensionPair, 1> contract_along{{std::make_pair(1, 0)}};
Eigen::DSizes<ptrdiff_t, 2> indices1(Eigen::array<ptrdiff_t, 2>(1,2)); Eigen::DSizes<ptrdiff_t, 2> indices1(1,2);
Eigen::DSizes<ptrdiff_t, 2> sizes1(Eigen::array<ptrdiff_t, 2>(3,3)); Eigen::DSizes<ptrdiff_t, 2> sizes1(3,3);
Eigen::DSizes<ptrdiff_t, 2> indices2(Eigen::array<ptrdiff_t, 2>(0,2)); Eigen::DSizes<ptrdiff_t, 2> indices2(0,2);
Eigen::DSizes<ptrdiff_t, 2> sizes2(Eigen::array<ptrdiff_t, 2>(3,1)); Eigen::DSizes<ptrdiff_t, 2> sizes2(3,1);
tensor3 = tensor1.slice(indices1, sizes1).contract(tensor2.slice(indices2, sizes2), contract_along); tensor3 = tensor1.slice(indices1, sizes1).contract(tensor2.slice(indices2, sizes2), contract_along);
Map<MatrixXf> res(tensor3.data(), 3, 1); Map<MatrixXf> res(tensor3.data(), 3, 1);
@ -153,18 +154,18 @@ static void test_slice_as_lvalue()
tensor4.setRandom(); tensor4.setRandom();
Tensor<float, 3> result(4,5,7); Tensor<float, 3> result(4,5,7);
Eigen::DSizes<ptrdiff_t, 3> sizes12(Eigen::array<ptrdiff_t, 3>(2,2,7)); Eigen::DSizes<ptrdiff_t, 3> sizes12(2,2,7);
Eigen::DSizes<ptrdiff_t, 3> first_slice(Eigen::array<ptrdiff_t, 3>(0,0,0)); Eigen::DSizes<ptrdiff_t, 3> first_slice(0,0,0);
result.slice(first_slice, sizes12) = tensor1; result.slice(first_slice, sizes12) = tensor1;
Eigen::DSizes<ptrdiff_t, 3> second_slice(Eigen::array<ptrdiff_t, 3>(2,0,0)); Eigen::DSizes<ptrdiff_t, 3> second_slice(2,0,0);
result.slice(second_slice, sizes12).device(Eigen::DefaultDevice()) = tensor2; result.slice(second_slice, sizes12).device(Eigen::DefaultDevice()) = tensor2;
Eigen::DSizes<ptrdiff_t, 3> sizes3(Eigen::array<ptrdiff_t, 3>(4,3,5)); Eigen::DSizes<ptrdiff_t, 3> sizes3(4,3,5);
Eigen::DSizes<ptrdiff_t, 3> third_slice(Eigen::array<ptrdiff_t, 3>(0,2,0)); Eigen::DSizes<ptrdiff_t, 3> third_slice(0,2,0);
result.slice(third_slice, sizes3) = tensor3; result.slice(third_slice, sizes3) = tensor3;
Eigen::DSizes<ptrdiff_t, 3> sizes4(Eigen::array<ptrdiff_t, 3>(4,3,2)); Eigen::DSizes<ptrdiff_t, 3> sizes4(4,3,2);
Eigen::DSizes<ptrdiff_t, 3> fourth_slice(Eigen::array<ptrdiff_t, 3>(0,2,5)); Eigen::DSizes<ptrdiff_t, 3> fourth_slice(0,2,5);
result.slice(fourth_slice, sizes4) = tensor4; result.slice(fourth_slice, sizes4) = tensor4;
for (int j = 0; j < 2; ++j) { for (int j = 0; j < 2; ++j) {