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Fix a couple of typos in the code.
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@ -220,7 +220,7 @@ EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, false>::run(
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if (needs_assign)
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{
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const int block_size = device.maxCudaThreadsPerBlock();
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const int max_blocks = numext::maxi<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size);
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const int max_blocks = numext::mini<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size);
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const Index size = array_prod(evaluator.dimensions());
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// Create a least one block to ensure we won't crash if we're called with tensors of size 0.
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const int num_blocks = numext::maxi<int>(numext::mini<int>(max_blocks, (size + block_size - 1) / block_size), 1);
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@ -239,7 +239,7 @@ EIGEN_DEVICE_FUNC inline void TensorExecutor<Expression, GpuDevice, true>::run(c
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if (needs_assign)
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{
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const int block_size = device.maxCudaThreadsPerBlock();
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const int max_blocks = numext::maxi<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size);
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const int max_blocks = numext::mini<int>(device.maxBlocks(), device.getNumCudaMultiProcessors() * device.maxCudaThreadsPerMultiProcessor() / block_size);
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const Index size = array_prod(evaluator.dimensions());
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// Create a least one block to ensure we won't crash if we're called with tensors of size 0.
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const int num_blocks = numext::maxi<int>(numext::mini<int>(max_blocks, (size + block_size - 1) / block_size), 1);
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