Run training with empty DMatrix. (#4990)
This makes GPU Hist robust in distributed environment as some workers might not be associated with any data in either training or evaluation. * Disable rabit mock test for now: See #5012 . * Disable dask-cudf test at prediction for now: See #5003 * Launch dask job for all workers despite they might not have any data. * Check 0 rows in elementwise evaluation metrics. Using AUC and AUC-PR still throws an error. See #4663 for a robust fix. * Add tests for edge cases. * Add `LaunchKernel` wrapper handling zero sized grid. * Move some parts of allreducer into a cu file. * Don't validate feature names when the booster is empty. * Sync number of columns in DMatrix. As num_feature is required to be the same across all workers in data split mode. * Filtering in dask interface now by default syncs all booster that's not empty, instead of using rank 0. * Fix Jenkins' GPU tests. * Install dask-cuda from source in Jenkins' test. Now all tests are actually running. * Restore GPU Hist tree synchronization test. * Check UUID of running devices. The check is only performed on CUDA version >= 10.x, as 9.x doesn't have UUID field. * Fix CMake policy and project variables. Use xgboost_SOURCE_DIR uniformly, add policy for CMake >= 3.13. * Fix copying data to CPU * Fix race condition in cpu predictor. * Fix duplicated DMatrix construction. * Don't download extra nccl in CI script.
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@@ -133,9 +133,12 @@ class Transform {
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size_t shard_size = range_size;
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Range shard_range {0, static_cast<Range::DifferenceType>(shard_size)};
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dh::safe_cuda(cudaSetDevice(device_));
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const int GRID_SIZE =
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const int kGrids =
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static_cast<int>(DivRoundUp(*(range_.end()), kBlockThreads));
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detail::LaunchCUDAKernel<<<GRID_SIZE, kBlockThreads>>>(
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if (kGrids == 0) {
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return;
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}
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detail::LaunchCUDAKernel<<<kGrids, kBlockThreads>>>( // NOLINT
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_func, shard_range, UnpackHDVOnDevice(_vectors)...);
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}
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#else
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