Comments (7)
@Tramac you're missing the onnx
library. pip install onnx
should install it for you. For more details see https://github.com/onnx/onnx#installation
from code-samples.
@mk-nvidia Thanks for your reply!
pip list is as follows:
Package Version
----------------- --------
appdirs 1.4.4
dataclasses 0.8
decorator 5.0.9
graphsurgeon 0.4.1
Mako 1.1.4
MarkupSafe 2.0.1
numpy 1.19.5
onnx 1.9.0
onnx-tensorrt 0.1.0
pip 21.1.2
protobuf 3.17.3
pycuda 2020.1
pytools 2021.2.7
setuptools 57.0.0
six 1.16.0
tensorrt 7.0.0.11
torch 1.4.0
typing-extensions 3.10.0.0
uff 0.6.5
wheel 0.36.2
where the onnx
, onnx-tensorrt
and tensorrt
have been installed successfully.
from code-samples.
@mk-nvidia yeah this definitely isn't just a library installation problem. The errors are in one of the files in the present repo, saying onnx
is not declared, so I suspect a header has changed between versions.
from code-samples.
@harrism how can I fix this problem, I have no idea about it.
Looking forward to reply!
from code-samples.
@harrism The new error:
ioHelper.o: In function `nvinfer1::readTensorProto(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, float*)':
ioHelper.cpp:(.text+0x16b): undefined reference to `onnx::TensorProto::TensorProto()'
ioHelper.cpp:(.text+0x184): undefined reference to `google::protobuf::MessageLite::ParseFromString(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)'
ioHelper.cpp:(.text+0x27b): undefined reference to `onnx::TensorProto::~TensorProto()'
ioHelper.cpp:(.text+0x2b0): undefined reference to `onnx::TensorProto::~TensorProto()'
collect2: error: ld returned 1 exit status
make: *** [<builtin>: simpleOnnx_1] Error 1
where Makefile
as follows:
CXXFLAGS=-std=c++11 -DONNX_ML=1 -Wall -I$(CUDA_INSTALL_DIR)/include -I$(TENSORRT_LIBRARY_DIR)/include
LDFLAGS=-L$(CUDA_INSTALL_DIR)/lib64 -L$(CUDA_INSTALL_DIR)/lib64/stubs -L/usr/local/lib
LDLIBS=-Wl,--start-group -L$(ONNX_TENSORRT_DIR)/build/third_party/onnx -L$(PROTOBUF_DIR) -lnvonnxparser -lnvinfer -lcudart_static -lonnx -lonnx_proto -lprotobuf -lstdc++ -lm -lrt -ldl -lpthread -Wl,--end-group
HEADERS=${wildcard *.h}
TARGET_SRCS=$(wildcard simpleOnnx*.cpp)
TARGET_OBJS=${TARGET_SRCS:.cpp=.o}
TARGETS=${TARGET_OBJS:.o=}
This error is same as #34 , but it hasn't been resolved yet.
from code-samples.
I don't know, or I would have already told you. :) This is why I asked @mk-nvidia for help.
from code-samples.
@harrism Thanks for your reply, I will try to change a version. Update again if it is resolved.
from code-samples.
Related Issues (20)
- submodule is broken
- bandwidthtest.cu shows GB/s, but the math looks like MB/s HOT 1
- ERRORS: in simpleOnnx_*.cpp HOT 3
- simpleTensorCoreGEMM has errors in output when compiled with CUDA10 for Turing GPUs HOT 2
- CUDA-aware runtime error HOT 1
- CUDA-aware MPI example complains about CUDA runtime version HOT 2
- memtype_cache.c:137 UCX WARN destroying inuse address HOT 1
- Getting errors running tensor-cores example HOT 4
- CUDA aware Jacobi examples fail using PGI HOT 1
- [grCUDA] vulnerabiliy issues in packackage dependencies HOT 1
- fatal error: cuda_runtime.h HOT 3
- compile "TensorRT-introduction" HOT 3
- Error in simpleOnnx_1.cpp while running on jetson Nano 4 gb
- error by using cuda-aware-mpi-example, bandwidth was wrong HOT 10
- some questions about unified-memory,dataElem.cu file HOT 1
- Verification Failed on sample for cufft_callbacks
- Can't Detecting CUDA compiler ABI HOT 3
- Cannot reproduce the results on parallel reduce with shfl HOT 7
- tensor core example result mismatch with that of cublas
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