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| author |  Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-03-07 14:31:27 -0800 |
|---|---|---|
| committer | Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-03-07 14:31:27 -0800 |
| commit | 7f87cc3a3b397ad5b940289bfd8369eff517efae (patch) | |
| tree | 5b4dbd3c66d99365e48909295ea3b9277481cdec /unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h | |
| parent | e5f25622e20563d35d51de356379bdfd257f1d67 (diff) | |
Fix a couple of typos in the code.
Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h')
| -rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h b/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h index df15c6204..fd9919829 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h @@ -220,7 +220,7 @@ EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, false>::run( if (needs_assign) { const int block_size = device.maxCudaThreadsPerBlock(); - const int max_blocks = numext::maxi<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size); + const int max_blocks = numext::mini<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size); const Index size = array_prod(evaluator.dimensions()); // Create a least one block to ensure we won't crash if we're called with tensors of size 0. const int num_blocks = numext::maxi<int>(numext::mini<int>(max_blocks, (size + block_size - 1) / block_size), 1); @@ -239,7 +239,7 @@ EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, true>::run(c if (needs_assign) { const int block_size = device.maxCudaThreadsPerBlock(); - const int max_blocks = numext::maxi<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size); + const int max_blocks = numext::mini<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size); const Index size = array_prod(evaluator.dimensions()); // Create a least one block to ensure we won't crash if we're called with tensors of size 0. const int num_blocks = numext::maxi<int>(numext::mini<int>(max_blocks, (size + block_size - 1) / block_size), 1); |