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Rename Tuple -> Pair.

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This is to make way for a new `Tuple` class that mimics `std::tuple`,
but can be reliably used on device and with aligned Eigen types.

The existing Tuple has very few references, and is actually an
analogue of `std::pair`.
This commit is contained in:
Antonio Sanchez
2021-08-26 12:25:31 -07:00
committed by Rasmus Munk Larsen
parent 3d4ba855e0
commit 74da2e6821
6 changed files with 117 additions and 115 deletions
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70
unsupported/test/cxx11_tensor_argmax.cpp
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@@ -14,57 +14,57 @@
using Eigen::Tensor;
using Eigen::array;
using Eigen::Tuple;
using Eigen::Pair;
template <int DataLayout>
static void test_simple_index_tuples()
static void test_simple_index_pairs()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
tensor = (tensor + tensor.constant(0.5)).log();
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
index_tuples = tensor.index_tuples();
Tensor<Pair<DenseIndex, float>, 4, DataLayout> index_pairs(2,3,5,7);
index_pairs = tensor.index_pairs();
for (DenseIndex n = 0; n < 2*3*5*7; ++n) {
const Tuple<DenseIndex, float>& v = index_tuples.coeff(n);
const Pair<DenseIndex, float>& v = index_pairs.coeff(n);
VERIFY_IS_EQUAL(v.first, n);
VERIFY_IS_EQUAL(v.second, tensor.coeff(n));
}
}
template <int DataLayout>
static void test_index_tuples_dim()
static void test_index_pairs_dim()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
tensor = (tensor + tensor.constant(0.5)).log();
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
Tensor<Pair<DenseIndex, float>, 4, DataLayout> index_pairs(2,3,5,7);
index_tuples = tensor.index_tuples();
index_pairs = tensor.index_pairs();
for (Eigen::DenseIndex n = 0; n < tensor.size(); ++n) {
const Tuple<DenseIndex, float>& v = index_tuples(n); //(i, j, k, l);
const Pair<DenseIndex, float>& v = index_pairs(n); //(i, j, k, l);
VERIFY_IS_EQUAL(v.first, n);
VERIFY_IS_EQUAL(v.second, tensor(n));
}
}
template <int DataLayout>
static void test_argmax_tuple_reducer()
static void test_argmax_pair_reducer()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
tensor = (tensor + tensor.constant(0.5)).log();
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
index_tuples = tensor.index_tuples();
Tensor<Pair<DenseIndex, float>, 4, DataLayout> index_pairs(2,3,5,7);
index_pairs = tensor.index_pairs();
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
Tensor<Pair<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce(
dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
reduced = index_pairs.reduce(
dims, internal::ArgMaxPairReducer<Pair<DenseIndex, float> >());
Tensor<float, 0, DataLayout> maxi = tensor.maximum();
@@ -72,9 +72,9 @@ static void test_argmax_tuple_reducer()
array<DenseIndex, 3> reduce_dims;
for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_tuples.reduce(
reduce_dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
Tensor<Pair<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_pairs.reduce(
reduce_dims, internal::ArgMaxPairReducer<Pair<DenseIndex, float> >());
Tensor<float, 1, DataLayout> max_by_dims = tensor.maximum(reduce_dims);
@@ -84,19 +84,19 @@ static void test_argmax_tuple_reducer()
}
template <int DataLayout>
static void test_argmin_tuple_reducer()
static void test_argmin_pair_reducer()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
tensor.setRandom();
tensor = (tensor + tensor.constant(0.5)).log();
Tensor<Tuple<DenseIndex, float>, 4, DataLayout> index_tuples(2,3,5,7);
index_tuples = tensor.index_tuples();
Tensor<Pair<DenseIndex, float>, 4, DataLayout> index_pairs(2,3,5,7);
index_pairs = tensor.index_pairs();
Tensor<Tuple<DenseIndex, float>, 0, DataLayout> reduced;
Tensor<Pair<DenseIndex, float>, 0, DataLayout> reduced;
DimensionList<DenseIndex, 4> dims;
reduced = index_tuples.reduce(
dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
reduced = index_pairs.reduce(
dims, internal::ArgMinPairReducer<Pair<DenseIndex, float> >());
Tensor<float, 0, DataLayout> mini = tensor.minimum();
@@ -104,9 +104,9 @@ static void test_argmin_tuple_reducer()
array<DenseIndex, 3> reduce_dims;
for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
Tensor<Tuple<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_tuples.reduce(
reduce_dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
Tensor<Pair<DenseIndex, float>, 1, DataLayout> reduced_by_dims(7);
reduced_by_dims = index_pairs.reduce(
reduce_dims, internal::ArgMinPairReducer<Pair<DenseIndex, float> >());
Tensor<float, 1, DataLayout> min_by_dims = tensor.minimum(reduce_dims);
@@ -275,14 +275,14 @@ static void test_argmin_dim()
EIGEN_DECLARE_TEST(cxx11_tensor_argmax)
{
CALL_SUBTEST(test_simple_index_tuples<RowMajor>());
CALL_SUBTEST(test_simple_index_tuples<ColMajor>());
CALL_SUBTEST(test_index_tuples_dim<RowMajor>());
CALL_SUBTEST(test_index_tuples_dim<ColMajor>());
CALL_SUBTEST(test_argmax_tuple_reducer<RowMajor>());
CALL_SUBTEST(test_argmax_tuple_reducer<ColMajor>());
CALL_SUBTEST(test_argmin_tuple_reducer<RowMajor>());
CALL_SUBTEST(test_argmin_tuple_reducer<ColMajor>());
CALL_SUBTEST(test_simple_index_pairs<RowMajor>());
CALL_SUBTEST(test_simple_index_pairs<ColMajor>());
CALL_SUBTEST(test_index_pairs_dim<RowMajor>());
CALL_SUBTEST(test_index_pairs_dim<ColMajor>());
CALL_SUBTEST(test_argmax_pair_reducer<RowMajor>());
CALL_SUBTEST(test_argmax_pair_reducer<ColMajor>());
CALL_SUBTEST(test_argmin_pair_reducer<RowMajor>());
CALL_SUBTEST(test_argmin_pair_reducer<ColMajor>());
CALL_SUBTEST(test_simple_argmax<RowMajor>());
CALL_SUBTEST(test_simple_argmax<ColMajor>());
CALL_SUBTEST(test_simple_argmin<RowMajor>());