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xgboost/tests/cpp/data/test_simple_csr_source.cu
Jiaming Yuan 5374f52531
Complete cudf support. (#4850) 
* Handles missing value.
* Accept all floating point and integer types.
* Move to cudf 9.0 API.
* Remove requirement on `null_count`.
* Arbitrary column types support.
2019-09-16 23:52:00 -04:00

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// Copyright (c) 2019 by Contributors
#include <gtest/gtest.h>
#include <xgboost/data.h>
#include <xgboost/json.h>
#include <thrust/device_vector.h>
#include <memory>
#include "../../../src/common/bitfield.h"
#include "../../../src/common/device_helpers.cuh"
#include "../../../src/data/simple_csr_source.h"
#include "../../../src/data/columnar.h"
namespace xgboost {
TEST(ArrayInterfaceHandler, Error) {
constexpr size_t kRows {16};
Json column { Object() };
std::vector<Json> j_shape {Json(Integer(static_cast<Integer::Int>(kRows)))};
column["shape"] = Array(j_shape);
std::vector<Json> j_data {
Json(Integer(reinterpret_cast<Integer::Int>(nullptr))),
Json(Boolean(false))};
auto const& column_obj = get<Object>(column);
// missing version
EXPECT_THROW(ArrayInterfaceHandler::ExtractArray<float>(column_obj), dmlc::Error);
column["version"] = Integer(static_cast<Integer::Int>(1));
// missing data
EXPECT_THROW(ArrayInterfaceHandler::ExtractArray<float>(column_obj), dmlc::Error);
column["data"] = j_data;
// missing typestr
EXPECT_THROW(ArrayInterfaceHandler::ExtractArray<float>(column_obj), dmlc::Error);
column["typestr"] = String("<f4");
// nullptr is not valid
EXPECT_THROW(ArrayInterfaceHandler::ExtractArray<float>(column_obj), dmlc::Error);
thrust::device_vector<float> d_data(kRows);
j_data = {Json(Integer(reinterpret_cast<Integer::Int>(d_data.data().get()))),
Json(Boolean(false))};
column["data"] = j_data;
EXPECT_NO_THROW(ArrayInterfaceHandler::ExtractArray<float>(column_obj));
}
template <typename T>
Json GenerateDenseColumn(std::string const& typestr, size_t kRows,
thrust::device_vector<T>* out_d_data) {
auto& d_data = *out_d_data;
Json column { Object() };
std::vector<Json> j_shape {Json(Integer(static_cast<Integer::Int>(kRows)))};
column["shape"] = Array(j_shape);
column["strides"] = Array(std::vector<Json>{Json(Integer(static_cast<Integer::Int>(4)))});
d_data.resize(kRows);
for (size_t i = 0; i < d_data.size(); ++i) {
d_data[i] = i * 2.0;
}
auto p_d_data = dh::Raw(d_data);
std::vector<Json> j_data {
Json(Integer(reinterpret_cast<Integer::Int>(p_d_data))),
Json(Boolean(false))};
column["data"] = j_data;
column["version"] = Integer(static_cast<Integer::Int>(1));
column["typestr"] = String(typestr);
return column;
}
TEST(SimpleCSRSource, FromColumnarDense) {
constexpr size_t kRows {16};
constexpr size_t kCols {2};
std::vector<Json> columns;
thrust::device_vector<float> d_data_0(kRows);
thrust::device_vector<int32_t> d_data_1(kRows);
columns.emplace_back(GenerateDenseColumn<float>("<f4", kRows, &d_data_0));
columns.emplace_back(GenerateDenseColumn<int32_t>("<i4", kRows, &d_data_1));
Json column_arr {columns};
std::stringstream ss;
Json::Dump(column_arr, &ss);
std::string str = ss.str();
// no missing value
{
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), false);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
for (size_t i = 0; i < kRows; i++) {
auto const idx = i * kCols;
auto const e_0 = data.at(idx);
ASSERT_NEAR(e_0.fvalue, i * 2.0, kRtEps) << "idx: " << idx;
ASSERT_EQ(e_0.index, 0); // feature 0
auto e_1 = data.at(idx+1);
ASSERT_NEAR(e_1.fvalue, i * 2.0, kRtEps);
ASSERT_EQ(e_1.index, 1); // feature 1
}
ASSERT_EQ(offset.back(), kRows * kCols);
for (size_t i = 0; i < kRows + 1; ++i) {
ASSERT_EQ(offset[i], i * kCols);
}
ASSERT_EQ(source->info.num_row_, kRows);
ASSERT_EQ(source->info.num_col_, kCols);
}
// with missing value specified
{
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), true, 4.0);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
ASSERT_EQ(data.size(), kRows * kCols - 2);
ASSERT_NEAR(data[4].fvalue, 6.0, kRtEps); // kCols * 2
ASSERT_EQ(offset.back(), 30);
for (size_t i = 3; i < kRows + 1; ++i) {
ASSERT_EQ(offset[i], (i - 1) * 2);
}
ASSERT_EQ(source->info.num_row_, kRows);
ASSERT_EQ(source->info.num_col_, kCols);
}
{
// no missing value, but has NaN
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
d_data_0[3] = std::numeric_limits<float>::quiet_NaN();
ASSERT_TRUE(std::isnan(d_data_0[3])); // removes 6.0
source->CopyFrom(str.c_str(), false);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
ASSERT_EQ(data.size(), kRows * kCols - 1);
ASSERT_NEAR(data[7].fvalue, 8.0, kRtEps);
ASSERT_EQ(source->info.num_row_, kRows);
ASSERT_EQ(source->info.num_col_, kCols);
}
}
TEST(SimpleCSRSource, FromColumnarWithEmptyRows) {
constexpr size_t kRows = 102;
constexpr size_t kCols = 24;
std::vector<Json> v_columns (kCols);
std::vector<dh::device_vector<float>> columns_data(kCols);
std::vector<dh::device_vector<unsigned char>> column_bitfields(kCols);
unsigned char constexpr kUCOne = 1;
for (size_t i = 0; i < kCols; ++i) {
auto& col = v_columns[i];
col = Object();
auto& data = columns_data[i];
data.resize(kRows);
thrust::sequence(data.begin(), data.end(), 0);
dh::safe_cuda(cudaDeviceSynchronize());
dh::safe_cuda(cudaGetLastError());
ASSERT_EQ(data.size(), kRows);
auto p_d_data = raw_pointer_cast(data.data());
std::vector<Json> j_data {
Json(Integer(reinterpret_cast<Integer::Int>(p_d_data))),
Json(Boolean(false))};
col["data"] = j_data;
std::vector<Json> j_shape {Json(Integer(static_cast<Integer::Int>(kRows)))};
col["shape"] = Array(j_shape);
col["version"] = Integer(static_cast<Integer::Int>(1));
col["typestr"] = String("<f4");
// Construct the mask object.
col["mask"] = Object();
auto& j_mask = col["mask"];
j_mask["version"] = Integer(static_cast<Integer::Int>(1));
auto& mask_storage = column_bitfields[i];
mask_storage.resize(16); // 16 bytes
mask_storage[0] = ~(kUCOne << 2); // 3^th row is missing
mask_storage[1] = ~(kUCOne << 3); // 12^th row is missing
size_t last_ind = 12;
mask_storage[last_ind] = ~(kUCOne << 5);
std::set<size_t> missing_row_index {0, 1, last_ind};
for (size_t i = 0; i < mask_storage.size(); ++i) {
if (missing_row_index.find(i) == missing_row_index.cend()) {
// all other rows are valid
mask_storage[i] = ~0;
}
}
j_mask["data"] = std::vector<Json>{
Json(Integer(reinterpret_cast<Integer::Int>(mask_storage.data().get()))),
Json(Boolean(false))};
j_mask["shape"] = Array(std::vector<Json>{Json(Integer(static_cast<Integer::Int>(16)))});
j_mask["typestr"] = String("|i1");
}
Json column_arr {Array(v_columns)};
std::stringstream ss;
Json::Dump(column_arr, &ss);
std::string str = ss.str();
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), false);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
ASSERT_EQ(offset.size(), kRows + 1);
for (size_t i = 1; i < offset.size(); ++i) {
for (size_t j = offset[i-1]; j < offset[i]; ++j) {
ASSERT_EQ(data[j].index, j % kCols);
ASSERT_NEAR(data[j].fvalue, i - 1, kRtEps);
}
}
ASSERT_EQ(source->info.num_row_, kRows);
}
TEST(SimpleCSRSource, FromColumnarSparse) {
constexpr size_t kRows = 32;
constexpr size_t kCols = 2;
unsigned char constexpr kUCOne = 1;
std::vector<dh::device_vector<float>> columns_data(kCols);
std::vector<dh::device_vector<unsigned char>> column_bitfields(kCols);
{
// column 0
auto& mask = column_bitfields[0];
mask.resize(8);
for (size_t j = 0; j < mask.size(); ++j) {
mask[j] = ~0;
}
// the 2^th entry of first column is invalid
// [0 0 0 0 0 1 0 0]
mask[0] = ~(kUCOne << 2);
}
{
// column 1
auto& mask = column_bitfields[1];
mask.resize(8);
for (size_t j = 0; j < mask.size(); ++j) {
mask[j] = ~0;
}
// the 19^th entry of second column is invalid
// [~0~], [~0~], [0 0 0 0 1 0 0 0]
mask[2] = ~(kUCOne << 3);
}
for (size_t c = 0; c < kCols; ++c) {
columns_data[c].resize(kRows);
thrust::sequence(columns_data[c].begin(), columns_data[c].end(), 0);
}
std::vector<Json> j_columns(kCols);
for (size_t c = 0; c < kCols; ++c) {
auto& column = j_columns[c];
column = Object();
column["version"] = Integer(static_cast<Integer::Int>(1));
column["typestr"] = String("<f4");
auto p_d_data = raw_pointer_cast(columns_data[c].data());
std::vector<Json> j_data {
Json(Integer(reinterpret_cast<Integer::Int>(p_d_data))),
Json(Boolean(false))};
column["data"] = j_data;
std::vector<Json> j_shape {Json(Integer(static_cast<Integer::Int>(kRows)))};
column["shape"] = Array(j_shape);
column["version"] = Integer(static_cast<Integer::Int>(1));
column["typestr"] = String("<f4");
column["mask"] = Object();
auto& j_mask = column["mask"];
j_mask["version"] = Integer(static_cast<Integer::Int>(1));
j_mask["data"] = std::vector<Json>{
Json(Integer(reinterpret_cast<Integer::Int>(column_bitfields[c].data().get()))),
Json(Boolean(false))};
j_mask["shape"] = Array(std::vector<Json>{Json(Integer(static_cast<Integer::Int>(8)))});
j_mask["typestr"] = String("|i1");
}
Json column_arr {Array(j_columns)};
std::stringstream ss;
Json::Dump(column_arr, &ss);
std::string str = ss.str();
{
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), false);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
ASSERT_EQ(offset.size(), kRows + 1);
ASSERT_EQ(data[4].index, 1);
ASSERT_EQ(data[4].fvalue, 2);
ASSERT_EQ(data[37].index, 0);
ASSERT_EQ(data[37].fvalue, 19);
}
{
// with missing value
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), true, /*missing=*/2.0);
auto const& data = source->page_.data.HostVector();
ASSERT_NE(data[4].fvalue, 2.0);
}
{
// no missing value, but has NaN
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
columns_data[0][4] = std::numeric_limits<float>::quiet_NaN(); // 0^th column 4^th row
ASSERT_TRUE(std::isnan(columns_data[0][4]));
source->CopyFrom(str.c_str(), false);
auto const& data = source->page_.data.HostVector();
auto const& offset = source->page_.offset.HostVector();
// Two invalid entries and one NaN, in CSC
// 0^th column: 0, 1, 4, 5, 6, ..., kRows
// 1^th column: 0, 1, 2, 3, ..., 19, 21, ..., kRows
// Turning it into CSR:
// | 0, 0 | 1, 1 | 2 | 3, 3 | 4 | ...
ASSERT_EQ(data.size(), kRows * kCols - 3);
ASSERT_EQ(data[4].index, 1); // from 1^th column
ASSERT_EQ(data[5].fvalue, 3.0);
ASSERT_EQ(data[7].index, 1); // from 1^th column
ASSERT_EQ(data[7].fvalue, 4.0);
ASSERT_EQ(data[offset[2]].fvalue, 2.0);
ASSERT_EQ(data[offset[4]].fvalue, 4.0);
}
{
// with NaN as missing value
// NaN is already set up by above test
std::unique_ptr<data::SimpleCSRSource> source (new data::SimpleCSRSource());
source->CopyFrom(str.c_str(), true,
/*missing=*/std::numeric_limits<float>::quiet_NaN());
auto const& data = source->page_.data.HostVector();
ASSERT_EQ(data.size(), kRows * kCols - 1);
ASSERT_EQ(data[8].fvalue, 4.0);
}
}
} // namespace xgboost
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