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Fix external memory with gpu_hist and subsampling combination bug. (#7481)

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Instead of accessing data from the `original_page_`, access the data from the first page of the available batch.

fix #7476

Co-authored-by: jiamingy <jm.yuan@outlook.com>
This commit is contained in:
Ginko Balboa
2021-12-24 04:15:35 +01:00
committed by GitHub
parent 7f399eac8b
commit 29bfa94bb6
4 changed files with 61 additions and 33 deletions
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32
src/tree/gpu_hist/gradient_based_sampler.cu
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@@ -185,12 +185,10 @@ GradientBasedSample UniformSampling::Sample(common::Span<GradientPair> gpair, DM
return {dmat->Info().num_row_, page_, gpair};
}
ExternalMemoryUniformSampling::ExternalMemoryUniformSampling(EllpackPageImpl const* page,
size_t n_rows,
ExternalMemoryUniformSampling::ExternalMemoryUniformSampling(size_t n_rows,
BatchParam batch_param,
float subsample)
: original_page_(page),
batch_param_(std::move(batch_param)),
: batch_param_(std::move(batch_param)),
subsample_(subsample),
sample_row_index_(n_rows) {}
@@ -218,15 +216,17 @@ GradientBasedSample ExternalMemoryUniformSampling::Sample(common::Span<GradientP
sample_row_index_.begin(),
ClearEmptyRows());
auto batch_iterator = dmat->GetBatches<EllpackPage>(batch_param_);
auto first_page = (*batch_iterator.begin()).Impl();
// Create a new ELLPACK page with empty rows.
page_.reset(); // Release the device memory first before reallocating
page_.reset(new EllpackPageImpl(
batch_param_.gpu_id, original_page_->Cuts(), original_page_->is_dense,
original_page_->row_stride, sample_rows));
batch_param_.gpu_id, first_page->Cuts(), first_page->is_dense,
first_page->row_stride, sample_rows));
// Compact the ELLPACK pages into the single sample page.
thrust::fill(dh::tbegin(page_->gidx_buffer), dh::tend(page_->gidx_buffer), 0);
for (auto& batch : dmat->GetBatches<EllpackPage>(batch_param_)) {
for (auto& batch : batch_iterator) {
page_->Compact(batch_param_.gpu_id, batch.Impl(), dh::ToSpan(sample_row_index_));
}
@@ -259,12 +259,10 @@ GradientBasedSample GradientBasedSampling::Sample(common::Span<GradientPair> gpa
}
ExternalMemoryGradientBasedSampling::ExternalMemoryGradientBasedSampling(
EllpackPageImpl const* page,
size_t n_rows,
BatchParam batch_param,
float subsample)
: original_page_(page),
batch_param_(std::move(batch_param)),
: batch_param_(std::move(batch_param)),
subsample_(subsample),
threshold_(n_rows + 1, 0.0f),
grad_sum_(n_rows, 0.0f),
@@ -300,15 +298,17 @@ GradientBasedSample ExternalMemoryGradientBasedSampling::Sample(common::Span<Gra
sample_row_index_.begin(),
ClearEmptyRows());
auto batch_iterator = dmat->GetBatches<EllpackPage>(batch_param_);
auto first_page = (*batch_iterator.begin()).Impl();
// Create a new ELLPACK page with empty rows.
page_.reset(); // Release the device memory first before reallocating
page_.reset(new EllpackPageImpl(batch_param_.gpu_id, original_page_->Cuts(),
original_page_->is_dense,
original_page_->row_stride, sample_rows));
page_.reset(new EllpackPageImpl(batch_param_.gpu_id, first_page->Cuts(),
first_page->is_dense,
first_page->row_stride, sample_rows));
// Compact the ELLPACK pages into the single sample page.
thrust::fill(dh::tbegin(page_->gidx_buffer), dh::tend(page_->gidx_buffer), 0);
for (auto& batch : dmat->GetBatches<EllpackPage>(batch_param_)) {
for (auto& batch : batch_iterator) {
page_->Compact(batch_param_.gpu_id, batch.Impl(), dh::ToSpan(sample_row_index_));
}
@@ -329,7 +329,7 @@ GradientBasedSampler::GradientBasedSampler(EllpackPageImpl const* page,
switch (sampling_method) {
case TrainParam::kUniform:
if (is_external_memory) {
strategy_.reset(new ExternalMemoryUniformSampling(page, n_rows, batch_param, subsample));
strategy_.reset(new ExternalMemoryUniformSampling(n_rows, batch_param, subsample));
} else {
strategy_.reset(new UniformSampling(page, subsample));
}
@@ -337,7 +337,7 @@ GradientBasedSampler::GradientBasedSampler(EllpackPageImpl const* page,
case TrainParam::kGradientBased:
if (is_external_memory) {
strategy_.reset(
new ExternalMemoryGradientBasedSampling(page, n_rows, batch_param, subsample));
new ExternalMemoryGradientBasedSampling(n_rows, batch_param, subsample));
} else {
strategy_.reset(new GradientBasedSampling(page, n_rows, batch_param, subsample));
}