5d7cdf2e36
The role of ProxyDMatrix is going beyond what it was designed. Now it's used by both QuantileDeviceDMatrix and inplace prediction. After the refactoring of sparse DMatrix it will also be used for external memory. Renaming the C API to extract it from QuantileDeviceDMatrix.
44 lines
1.4 KiB
Plaintext
44 lines
1.4 KiB
Plaintext
#include <xgboost/c_api.h>
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#include "helpers.h"
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#include "../../src/data/device_adapter.cuh"
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#include "../../src/data/iterative_device_dmatrix.h"
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namespace xgboost {
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CudaArrayIterForTest::CudaArrayIterForTest(float sparsity, size_t rows,
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size_t cols, size_t batches)
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: rows_{rows}, cols_{cols}, n_batches_{batches} {
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XGProxyDMatrixCreate(&proxy_);
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rng_.reset(new RandomDataGenerator{rows_, cols_, sparsity});
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rng_->Device(0);
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std::tie(batches_, interface_) =
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rng_->GenerateArrayInterfaceBatch(&data_, n_batches_);
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this->Reset();
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}
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CudaArrayIterForTest::~CudaArrayIterForTest() { XGDMatrixFree(proxy_); }
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int CudaArrayIterForTest::Next() {
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if (iter_ == n_batches_) {
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return 0;
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}
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XGProxyDMatrixSetDataCudaArrayInterface(proxy_, batches_[iter_].c_str());
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iter_++;
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return 1;
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}
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size_t constexpr CudaArrayIterForTest::kRows;
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size_t constexpr CudaArrayIterForTest::kCols;
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std::shared_ptr<DMatrix> RandomDataGenerator::GenerateDeviceDMatrix(bool with_label,
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bool float_label,
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size_t classes) {
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CudaArrayIterForTest iter{this->sparsity_, this->rows_, this->cols_, 1};
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auto m = std::make_shared<data::IterativeDeviceDMatrix>(
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&iter, iter.Proxy(), Reset, Next, std::numeric_limits<float>::quiet_NaN(),
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0, bins_);
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return m;
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}
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} // namespace xgboost
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