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Add high level tests for categorical data. (#6179)

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* Fix unique.
This commit is contained in:
Jiaming Yuan
2020-10-09 09:27:23 +08:00
committed by GitHub
parent 6bc9747df5
commit 70ce5216b5
4 changed files with 78 additions and 21 deletions
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41
src/common/hist_util.cu
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@@ -131,42 +131,50 @@ struct IsCatOp {
void RemoveDuplicatedCategories(
int32_t device, MetaInfo const &info, Span<bst_row_t> d_cuts_ptr,
dh::device_vector<Entry> *p_sorted_entries,
dh::caching_device_vector<size_t> const &column_sizes_scan) {
dh::caching_device_vector<size_t>* p_column_sizes_scan) {
auto d_feature_types = info.feature_types.ConstDeviceSpan();
auto& column_sizes_scan = *p_column_sizes_scan;
if (!info.feature_types.Empty() &&
thrust::any_of(dh::tbegin(d_feature_types), dh::tend(d_feature_types),
IsCatOp{})) {
auto& sorted_entries = *p_sorted_entries;
// Removing duplicated entries in categorical features.
dh::caching_device_vector<size_t> new_column_scan(column_sizes_scan.size());
dh::SegmentedUnique(column_sizes_scan.data().get(),
column_sizes_scan.data().get() +
column_sizes_scan.size(),
sorted_entries.begin(), sorted_entries.end(),
new_column_scan.data().get(), sorted_entries.begin(),
[=] __device__(Entry const &l, Entry const &r) {
if (l.index == r.index) {
if (IsCat(d_feature_types, l.index)) {
return l.fvalue == r.fvalue;
}
}
return false;
});
dh::SegmentedUnique(
column_sizes_scan.data().get(),
column_sizes_scan.data().get() + column_sizes_scan.size(),
sorted_entries.begin(), sorted_entries.end(),
new_column_scan.data().get(), sorted_entries.begin(),
[=] __device__(Entry const &l, Entry const &r) {
if (l.index == r.index) {
if (IsCat(d_feature_types, l.index)) {
return l.fvalue == r.fvalue;
}
}
return false;
});
// Renew the column scan and cut scan based on categorical data.
auto d_old_column_sizes_scan = dh::ToSpan(column_sizes_scan);
dh::caching_device_vector<SketchContainer::OffsetT> new_cuts_size(
info.num_col_ + 1);
auto d_new_cuts_size = dh::ToSpan(new_cuts_size);
auto d_new_columns_ptr = dh::ToSpan(new_column_scan);
CHECK_EQ(new_column_scan.size(), new_cuts_size.size());
dh::LaunchN(device, new_column_scan.size() - 1, [=] __device__(size_t idx) {
dh::LaunchN(device, new_column_scan.size(), [=] __device__(size_t idx) {
d_old_column_sizes_scan[idx] = d_new_columns_ptr[idx];
if (idx == d_new_columns_ptr.size() - 1) {
return;
}
if (IsCat(d_feature_types, idx)) {
// Cut size is the same as number of categories in input.
d_new_cuts_size[idx] =
d_new_columns_ptr[idx + 1] - d_new_columns_ptr[idx];
} else {
d_new_cuts_size[idx] = d_cuts_ptr[idx] - d_cuts_ptr[idx];
}
});
// Turn size into ptr.
thrust::exclusive_scan(thrust::device, new_cuts_size.cbegin(),
new_cuts_size.cend(), d_cuts_ptr.data());
}
@@ -197,7 +205,8 @@ void ProcessBatch(int device, MetaInfo const &info, const SparsePage &page,
&cuts_ptr, &column_sizes_scan);
auto d_cuts_ptr = cuts_ptr.DeviceSpan();
detail::RemoveDuplicatedCategories(device, info, d_cuts_ptr, &sorted_entries,
column_sizes_scan);
&column_sizes_scan);
auto const& h_cuts_ptr = cuts_ptr.ConstHostVector();
CHECK_EQ(d_cuts_ptr.size(), column_sizes_scan.size());