GitHub-Proxy/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-08-12 11:49:02 +08:00
Code Issues Packages Projects Releases Wiki Activity

Improved partial reductions in more cases

Browse Source
This commit is contained in:
Benoit Steiner 2016-07-22 17:18:20 -07:00
parent 32d95e86c9
commit c6b0de2c21
2 changed files with 46 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
View File

@ -492,7 +492,7 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
} }
// Attempt to use an optimized reduction. // Attempt to use an optimized reduction.
else if (RunningOnGPU && data && (m_device.majorDeviceVersion() >= 3)) { else if (RunningOnGPU && (m_device.majorDeviceVersion() >= 3)) {
bool reducing_inner_dims = true; bool reducing_inner_dims = true;
for (int i = 0; i < NumReducedDims; ++i) { for (int i = 0; i < NumReducedDims; ++i) {
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
@ -505,8 +505,12 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
(reducing_inner_dims || ReducingInnerMostDims)) { (reducing_inner_dims || ReducingInnerMostDims)) {
const Index num_values_to_reduce = internal::array_prod(m_reducedDims); const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions); const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions);
if (!data && num_coeffs_to_preserve < 1024 && num_values_to_reduce > num_coeffs_to_preserve) {
data = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType) * num_coeffs_to_preserve));
m_result = data;
}
Op reducer(m_reducer); Op reducer(m_reducer);
return internal::InnerReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve); return internal::InnerReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve) || (m_result != NULL);
} }
bool preserving_inner_dims = true; bool preserving_inner_dims = true;
@ -521,8 +525,12 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
preserving_inner_dims) { preserving_inner_dims) {
const Index num_values_to_reduce = internal::array_prod(m_reducedDims); const Index num_values_to_reduce = internal::array_prod(m_reducedDims);
const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions); const Index num_coeffs_to_preserve = internal::array_prod(m_dimensions);
if (!data && num_coeffs_to_preserve < 1024 && num_values_to_reduce > num_coeffs_to_preserve) {
data = static_cast<CoeffReturnType*>(m_device.allocate(sizeof(CoeffReturnType) * num_coeffs_to_preserve));
m_result = data;
}
Op reducer(m_reducer); Op reducer(m_reducer);
return internal::OuterReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve); return internal::OuterReducer<Self, Op, Device>::run(*this, reducer, m_device, data, num_values_to_reduce, num_coeffs_to_preserve) || (m_result != NULL);
} }
} }
return true; return true;
@ -537,8 +545,8 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
{ {
if (RunningFullReduction && m_result) { if ((RunningFullReduction || RunningOnGPU) && m_result) {
return *m_result; return *(m_result + index);
} }
Op reducer(m_reducer); Op reducer(m_reducer);
if (ReducingInnerMostDims || RunningFullReduction) { if (ReducingInnerMostDims || RunningFullReduction) {
@ -560,6 +568,10 @@ struct TensorEvaluator<const TensorReductionOp<Op, Dims, ArgType>, Device>
EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index + PacketSize - 1 < Index(internal::array_prod(dimensions()))); eigen_assert(index + PacketSize - 1 < Index(internal::array_prod(dimensions())));
if (RunningOnGPU && m_result) {
return internal::pload<PacketReturnType>(m_result + index);
}
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize]; EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
if (ReducingInnerMostDims) { if (ReducingInnerMostDims) {
const Index num_values_to_reduce = const Index num_values_to_reduce =

29
unsupported/test/cxx11_tensor_reduction.cpp
View File

@ -239,6 +239,33 @@ static void test_simple_reductions() {
} }
} }
template <int DataLayout>
static void test_reductions_in_expr() {
Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
tensor.setRandom();
array<ptrdiff_t, 2> reduction_axis2;
reduction_axis2[0] = 1;
reduction_axis2[1] = 3;
Tensor<float, 2, DataLayout> result(2, 5);
result = result.constant(1.0f) - tensor.sum(reduction_axis2);
VERIFY_IS_EQUAL(result.dimension(0), 2);
VERIFY_IS_EQUAL(result.dimension(1), 5);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 5; ++j) {
float sum = 0.0f;
for (int k = 0; k < 3; ++k) {
for (int l = 0; l < 7; ++l) {
sum += tensor(i, k, j, l);
}
}
VERIFY_IS_APPROX(result(i, j), 1.0f - sum);
}
}
}
template <int DataLayout> template <int DataLayout>
static void test_full_reductions() { static void test_full_reductions() {
Tensor<float, 2, DataLayout> tensor(2, 3); Tensor<float, 2, DataLayout> tensor(2, 3);
@ -462,6 +489,8 @@ void test_cxx11_tensor_reduction() {
CALL_SUBTEST(test_trivial_reductions<RowMajor>()); CALL_SUBTEST(test_trivial_reductions<RowMajor>());
CALL_SUBTEST(test_simple_reductions<ColMajor>()); CALL_SUBTEST(test_simple_reductions<ColMajor>());
CALL_SUBTEST(test_simple_reductions<RowMajor>()); CALL_SUBTEST(test_simple_reductions<RowMajor>());
CALL_SUBTEST(test_reductions_in_expr<ColMajor>());
CALL_SUBTEST(test_reductions_in_expr<RowMajor>());
CALL_SUBTEST(test_full_reductions<ColMajor>()); CALL_SUBTEST(test_full_reductions<ColMajor>());
CALL_SUBTEST(test_full_reductions<RowMajor>()); CALL_SUBTEST(test_full_reductions<RowMajor>());
CALL_SUBTEST(test_user_defined_reductions<ColMajor>()); CALL_SUBTEST(test_user_defined_reductions<ColMajor>());