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[c++][fix] Support Quantized Training with Categorical Features on CPU #6301

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merged 13 commits into from
Feb 23, 2024
Merged

[c++][fix] Support Quantized Training with Categorical Features on CPU #6301

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431f967
support quantized training with categorical features on cpu
shiyu1994 Feb 5, 2024
b07caf2
remove white spaces
shiyu1994 Feb 5, 2024
cf60467
add tests for quantized training with categorical features
shiyu1994 Feb 5, 2024
bf2f649
skip tests for cuda version
shiyu1994 Feb 5, 2024
2fc9525
fix cases when only 1 data block in row-wise quantized histogram cons…
shiyu1994 Feb 6, 2024
dce770c
remove useless capture
shiyu1994 Feb 6, 2024
6d090b2
Merge branch 'master' into fix-6257
shiyu1994 Feb 20, 2024
ffead81
merge master
shiyu1994 Feb 22, 2024
f4e389f
fix compilation warnings
shiyu1994 Feb 22, 2024
73fb576
revert useless change
shiyu1994 Feb 22, 2024
c4a7798
separate functions in feature histogram into cpp file
shiyu1994 Feb 22, 2024
fbb1c90
add feature_histogram.o in Makevars
shiyu1994 Feb 22, 2024
ebe382a
Merge branch 'master' into fix-6257
shiyu1994 Feb 22, 2024
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1 change: 1 addition & 0 deletions R-package/src/Makevars.in
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,7 @@ OBJECTS = \
network/linkers_socket.o \
network/network.o \
treelearner/data_parallel_tree_learner.o \
treelearner/feature_histogram.o \
treelearner/feature_parallel_tree_learner.o \
treelearner/gpu_tree_learner.o \
treelearner/gradient_discretizer.o \
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1 change: 1 addition & 0 deletions R-package/src/Makevars.win.in
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Expand Up @@ -47,6 +47,7 @@ OBJECTS = \
network/linkers_socket.o \
network/network.o \
treelearner/data_parallel_tree_learner.o \
treelearner/feature_histogram.o \
treelearner/feature_parallel_tree_learner.o \
treelearner/gpu_tree_learner.o \
treelearner/gradient_discretizer.o \
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8 changes: 5 additions & 3 deletions src/io/train_share_states.cpp
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Expand Up @@ -62,15 +62,17 @@ void MultiValBinWrapper::HistMove(const std::vector<hist_t,
reinterpret_cast<int64_t*>(origin_hist_data_) + hist_move_dest_[i] / 2);
}
} else if (HIST_BITS == 16) {
const int32_t* src = reinterpret_cast<const int32_t*>(hist_buf.data()) + hist_buf.size() / 2 -
static_cast<size_t>(num_bin_aligned_);
if (is_use_subcol_) {
const int32_t* src = reinterpret_cast<const int32_t*>(hist_buf.data()) + hist_buf.size() / 2 -
static_cast<size_t>(num_bin_aligned_);
#pragma omp parallel for schedule(static) num_threads(num_threads_)
for (int i = 0; i < static_cast<int>(hist_move_src_.size()); ++i) {
std::copy_n(src + hist_move_src_[i] / 2, hist_move_size_[i] / 2,
reinterpret_cast<int32_t*>(origin_hist_data_) + hist_move_dest_[i] / 2);
}
} else {
CHECK_EQ(INNER_HIST_BITS, 8);
const int32_t* src = reinterpret_cast<const int32_t*>(hist_buf.data()) + hist_buf.size() / 2;
int32_t* orig_ptr = reinterpret_cast<int32_t*>(origin_hist_data_);
#pragma omp parallel for schedule(static) num_threads(num_threads_)
for (int i = 0; i < num_bin_; ++i) {
Expand Down Expand Up @@ -148,7 +150,7 @@ void MultiValBinWrapper::HistMerge(std::vector<hist_t,
}
}
} else if (HIST_BITS == 16 && INNER_HIST_BITS == 8) {
int32_t* dst = reinterpret_cast<int32_t*>(hist_buf->data()) + hist_buf->size() / 2 - static_cast<size_t>(num_bin_aligned_);
int32_t* dst = reinterpret_cast<int32_t*>(hist_buf->data()) + hist_buf->size() / 2;
std::memset(reinterpret_cast<void*>(dst), 0, num_bin_ * kInt16HistBufferEntrySize);
#pragma omp parallel for schedule(static, 1) num_threads(num_threads_)
for (int t = 0; t < n_bin_block; ++t) {
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