Extend simple lib example to support GPU inputs / outputs #579
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deadeyegoodwin
suggested changes
Aug 23, 2019
src/servers/simple.cc
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| *buffer = (byte_size == 0) ? nullptr : malloc(byte_size); | ||
| // need to do any other book-keeping. | ||
| if (byte_size == 0) { | ||
| *buffer = nullptr; | ||
| *buffer_userp = new std::string(tensor_name); |
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*buffer_userp = nullptr when byte_size is 0. Release won't be called (will it?) and buffer_userp is just passed to release.
src/servers/simple.cc
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| @@ -24,6 +24,7 @@ | |||
| // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | |||
| // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | |||
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| #include <cuda_runtime_api.h> | |||
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Need some ifdef GPU
src/servers/simple.cc
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| LOG_INFO << "Releasing buffer " << buffer << " of size " << byte_size | ||
| << " for result '" << *name << "'"; | ||
| free(buffer); | ||
| std::string memory_type_str = |
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Make this global and use it in the logging in the alloc function as well.
src/servers/simple.cc
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| @@ -48,6 +69,7 @@ Usage(char** argv, const std::string& msg = std::string()) | |||
| } | |||
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| LOG_ERROR << "Usage: " << argv[0] << " [options]"; | |||
| LOG_ERROR << "\t-g store input data in GPU"; | |||
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"Use GPU memory for input and output tensors"
src/servers/simple.cc
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| void* allocated_ptr = nullptr; | ||
| if (memory_type == TRTSERVER_MEMORY_CPU) { | ||
| allocated_ptr = malloc(byte_size); | ||
| } else { |
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Only use GPU if -g flag was specified
src/servers/simple.cc
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| @@ -118,11 +167,15 @@ int | |||
| main(int argc, char** argv) | |||
| { | |||
| std::string model_repository_path; | |||
| bool gpu_input = false; | |||
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gpu_input implies only using for input. How about "use_gpu_memory"
deadeyegoodwin
approved these changes
Aug 26, 2019
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