steven12356789 opened a new issue #20134: URL: https://github.com/apache/incubator-mxnet/issues/20134
HI, I use ResNeSt model to train my own dataset. from this following link : https://github.com/zhanghang1989/ResNeSt#transfer-learning-models. Now I can transform model to ONNX without any error. But when I want to use tensorRT to speed up inference and use C++ to export onnx to int8. My terminal shows like these: WARN TRT: No implementation of layer (Unnamed Layer* 69) [Shuffle] + Transpose_52 obeys the requested constraints in strict mode. No conforming implementation was found i.e. requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_68 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_103 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer (Unnamed Layer* 158) [Shuffle] obeys the requested constraints in strict mode. No conforming implementa WARN TRT: No implementation of layer Softmax_116 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer (Unnamed Layer* 160) [Shuffle] + Transpose_117 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_133 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_166 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer (Unnamed Layer* 247) [Shuffle] obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer Softmax_179 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer (Unnamed Layer* 249) [Shuffle] + Transpose_180 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_196 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 WARN TRT: No implementation of layer ReduceSum_229 obeys the requested constraints in strict mode. No conforming implementation was found i.e requested layer computation precision and output precision types are ignored, using the fastest implementation. trt_utils.cpp:253 So, **Does that mean that I can not use INT8?** ## Environment onnx 1.7.0 onnxruntime 1.5.2 tensorrt 7.2.1.4 cuda version 11.1 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
