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nGraph: Fix TopK output sorting by index (#3092)

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Tomasz Jankowski 2020-11-18 14:14:33 +01:00 committed by GitHub
parent f90e7b7443
commit c36aaf8621
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5 changed files with 108 additions and 43 deletions
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12
docs/ops/sort/TopK_1.md
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@ -10,7 +10,7 @@
* *axis*
* **Description**: Specifies the axis along which
* **Description**: Specifies the axis along which the values are retrieved.
* **Range of values**: An integer. Negative value means counting dimension from the end.
* **Type**: `int`
* **Default value**: None
@ -50,7 +50,15 @@ Output tensor is populated by values computes in the following way:
output[i1, ..., i(axis-1), j, i(axis+1) ..., iN] = top_k(input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]), k, sort, mode)
So for each slice `input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]` which represents 1D array, top_k value is computed individually. Sorting and minimum/maximum are controlled by `sort` and `mode` attributes.
So for each slice `input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]` which represents 1D array, top_k value is computed individually.
Sorting and minimum/maximum are controlled by `sort` and `mode` attributes:
* *mode*=`max`, *sort*=`value` - descending by value
* *mode*=`max`, *sort*=`index` - ascending by index
* *mode*=`max`, *sort*=`none` - undefined
* *mode*=`min`, *sort*=`value` - ascending by value
* *mode*=`min`, *sort*=`index` - ascending by index
* *mode*=`min`, *sort*=`none` - undefined
**Example**

12
docs/ops/sort/TopK_3.md
View File

@ -10,7 +10,7 @@
* *axis*
* **Description**: Specifies the axis along which
* **Description**: Specifies the axis along which the values are retrieved.
* **Range of values**: An integer. Negative value means counting dimension from the end.
* **Type**: `int`
* **Default value**: None
@ -65,7 +65,15 @@ Output tensor is populated by values computes in the following way:
output[i1, ..., i(axis-1), j, i(axis+1) ..., iN] = top_k(input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]), k, sort, mode)
So for each slice `input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]` which represents 1D array, *TopK* value is computed individually. Sorting and minimum/maximum are controlled by `sort` and `mode` attributes.
So for each slice `input[i1, ...., i(axis-1), :, i(axis+1), ..., iN]` which represents 1D array, *TopK* value is computed individually.
Sorting and minimum/maximum are controlled by `sort` and `mode` attributes:
* *mode*=`max`, *sort*=`value` - descending by value
* *mode*=`max`, *sort*=`index` - ascending by index
* *mode*=`max`, *sort*=`none` - undefined
* *mode*=`min`, *sort*=`value` - ascending by value
* *mode*=`min`, *sort*=`index` - ascending by index
* *mode*=`min`, *sort*=`none` - undefined
**Example**

3
inference-engine/tests/functional/plugin/cpu/shared_tests_instances/skip_tests_config.cpp
View File

@ -51,8 +51,7 @@ std::vector<std::string> disabledTestPatterns() {
// TODO: Issue: 37862
R"(.*ReverseSequenceLayerTest.*netPRC=(I8|U8).*)",
// TODO: Issue: 38841
R"(.*TopKLayerTest.*k=10.*mode=min.*sort=index.*)",
R"(.*TopKLayerTest.*k=5.*sort=(none|index).*)",
R"(.*TopKLayerTest.*k=5.*sort=none.*)",
// TODO: Issue: 43314
R"(.*Broadcast.*mode=BIDIRECTIONAL.*inNPrec=BOOL.*)",
// TODO: Issue 43417 sporadic issue, looks like an issue in test, reproducible only on Windows platform

44
ngraph/core/reference/include/ngraph/runtime/reference/topk.hpp
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@ -58,17 +58,10 @@ namespace ngraph
return a < b;
}
template <typename T, typename U>
inline bool sort_indices_descending(const std::tuple<T, U>& a,
const std::tuple<T, U>& b)
{
return std::get<1>(a) < std::get<1>(b);
}
template <typename T, typename U>
inline bool sort_indices_ascending(const std::tuple<T, U>& a, const std::tuple<T, U>& b)
{
return std::get<1>(a) > std::get<1>(b);
return std::get<1>(a) < std::get<1>(b);
}
template <typename T, typename U>
@ -133,35 +126,18 @@ namespace ngraph
compare_min<T, U>);
}
// Write temp vector to output
if (compute_max)
switch (sort)
{
switch (sort)
{
case op::v1::TopK::SortType::NONE: break;
case op::v1::TopK::SortType::SORT_INDICES:
std::sort(workspace.begin(),
workspace.begin() + k,
sort_indices_descending<T, U>);
break;
case op::v1::TopK::SortType::SORT_VALUES:
case op::v1::TopK::SortType::NONE: break;
case op::v1::TopK::SortType::SORT_INDICES:
std::sort(
workspace.begin(), workspace.begin() + k, sort_indices_ascending<T, U>);
break;
case op::v1::TopK::SortType::SORT_VALUES:
if (compute_max)
std::sort(workspace.begin(), workspace.begin() + k, compare_max<T, U>);
break;
}
}
else
{
switch (sort)
{
case op::v1::TopK::SortType::NONE: break;
case op::v1::TopK::SortType::SORT_INDICES:
std::sort(workspace.begin(),
workspace.begin() + k,
sort_indices_ascending<T, U>);
break;
case op::v1::TopK::SortType::SORT_VALUES:
else
std::sort(workspace.begin(), workspace.begin() + k, compare_min<T, U>);
break;
}
}
for (size_t j = 0; j < k; j++)
{

74
ngraph/test/backend/topk.in.cpp
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@ -30,6 +30,8 @@
#include "ngraph/runtime/tensor.hpp"
#include "runtime/backend.hpp"
#include "util/all_close_f.hpp"
#include "util/engine/test_engines.hpp"
#include "util/test_case.hpp"
#include "util/test_control.hpp"
#include "util/test_tools.hpp"
@ -37,6 +39,7 @@ using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});
template <typename T>
bool compare_set(const vector<T>& a, vector<T> b)
@ -1265,3 +1268,74 @@ NGRAPH_TEST(${BACKEND_NAME}, topk_v1_invalid_k)
const auto k_negative = op::Constant::create(element::i8, Shape{}, {-1});
EXPECT_THROW(op::v1::TopK(data, k_negative, 0, "max", "index"), ngraph::NodeValidationFailure);
}
template <typename T>
class topk_backend : public ::testing::Test
{
};
TYPED_TEST_CASE_P(topk_backend);
template <typename Mode, typename SortType>
struct TopkSortTestOutputs
{
Mode mode;
SortType sort_type;
std::vector<float> output0;
std::vector<int32_t> output1;
TopkSortTestOutputs(Mode mode,
SortType sort_type,
std::vector<float>&& output0,
std::vector<int32_t>&& output1)
: mode(mode)
, sort_type(sort_type)
, output0(std::move(output0))
, output1(std::move(output1))
{
}
};
TYPED_TEST_P(topk_backend, topk_mode_sort_order)
{
const Shape shape{5};
const Shape rshape{3};
const auto data = make_shared<op::Parameter>(element::f32, shape);
const auto k = op::Constant::create(element::i64, {}, {3});
const int64_t axis = 0;
// helpers to reduce code verbosity
using m = typename TypeParam::Mode;
using st = typename TypeParam::SortType;
using v_f = std::vector<float>;
using v_i = std::vector<int32_t>;
const std::vector<float> input{3, 1, 2, 5, 4};
std::vector<TopkSortTestOutputs<m, st>> valid_outputs;
valid_outputs.emplace_back(m::MAX, st::SORT_VALUES, v_f{5, 4, 3}, v_i{3, 4, 0});
valid_outputs.emplace_back(m::MAX, st::SORT_INDICES, v_f{3, 5, 4}, v_i{0, 3, 4});
valid_outputs.emplace_back(m::MIN, st::SORT_VALUES, v_f{1, 2, 3}, v_i{1, 2, 0});
valid_outputs.emplace_back(m::MIN, st::SORT_INDICES, v_f{3, 1, 2}, v_i{0, 1, 2});
for (const auto& v : valid_outputs)
{
auto topk = make_shared<TypeParam>(data, k, axis, v.mode, v.sort_type);
auto f0 = make_shared<Function>(OutputVector{topk->output(0)}, ParameterVector{data});
auto f1 = make_shared<Function>(OutputVector{topk->output(1)}, ParameterVector{data});
auto test_case0 = test::TestCase<TestEngine>(f0);
test_case0.add_input<float>(input);
test_case0.add_expected_output<float>(rshape, v.output0);
test_case0.run();
auto test_case1 = test::TestCase<TestEngine>(f1);
test_case1.add_input<float>(input);
test_case1.add_expected_output<int32_t>(rshape, v.output1);
test_case1.run();
}
}
REGISTER_TYPED_TEST_CASE_P(topk_backend, topk_mode_sort_order);
typedef ::testing::Types<op::v1::TopK, op::v3::TopK> TopKTypes;
INSTANTIATE_TYPED_TEST_CASE_P(${BACKEND_NAME}, topk_backend, TopKTypes);