File "/home/nvidia/caffe/python/caffe/pycaffe.py", line 13, in <module> from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \ ImportError: dynamic module does not define module export function (PyInit__caffe)

Hi, I tried to solve that error but I can not, it seems to be all right but I do not find that it is failing, you could help me thanks.

Traceback (most recent call last):
File “tegra-cam-caffe.py”, line 22, in
import caffe
File “/home/nvidia/caffe/python/caffe/init.py”, line 1, in
from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver, NCCL, Timer
File “/home/nvidia/caffe/python/caffe/pycaffe.py”, line 13, in
from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver,
ImportError: dynamic module does not define module export function (PyInit__caffe)


Here is the Makefile.config

Refer to Caffe | Installation

Contributions simplifying and improving our build system are welcome!

cuDNN acceleration switch (uncomment to build with cuDNN).

USE_CUDNN := 1

CPU-only switch (uncomment to build without GPU support).

CPU_ONLY := 1

uncomment to disable IO dependencies and corresponding data layers

USE_OPENCV := 0

USE_LEVELDB := 0

USE_LMDB := 0

This code is taken from GitHub - sh1r0/caffe-android-lib: Porting caffe to android platform

USE_HDF5 := 0

uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)

You should not set this flag if you will be reading LMDBs with any

possibility of simultaneous read and write

ALLOW_LMDB_NOLOCK := 1

Uncomment if you’re using OpenCV 3

OPENCV_VERSION := 3

To customize your choice of compiler, uncomment and set the following.

N.B. the default for Linux is g++ and the default for OSX is clang++

CUSTOM_CXX := g++

CUDA directory contains bin/ and lib/ directories that we need.

CUDA_DIR := /usr/local/cuda

On Ubuntu 14.04, if cuda tools are installed via

“sudo apt-get install nvidia-cuda-toolkit” then use this instead:

CUDA_DIR := /usr

CUDA architecture setting: going with all of them.

For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.

For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.

For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.

CUDA_ARCH := -gencode arch=compute_20,code=sm_20
-gencode arch=compute_20,code=sm_21
-gencode arch=compute_30,code=sm_30
-gencode arch=compute_35,code=sm_35
-gencode arch=compute_50,code=sm_50
-gencode arch=compute_52,code=sm_52
-gencode arch=compute_60,code=sm_60
-gencode arch=compute_61,code=sm_61
-gencode arch=compute_61,code=compute_61

BLAS choice:

atlas for ATLAS (default)

mkl for MKL

open for OpenBlas

BLAS := atlas

Custom (MKL/ATLAS/OpenBLAS) include and lib directories.

Leave commented to accept the defaults for your choice of BLAS

(which should work)!

BLAS_INCLUDE := /path/to/your/blas

BLAS_LIB := /path/to/your/blas

Homebrew puts openblas in a directory that is not on the standard search path

BLAS_INCLUDE := $(shell brew --prefix openblas)/include

BLAS_LIB := $(shell brew --prefix openblas)/lib

This is required only if you will compile the matlab interface.

MATLAB directory should contain the mex binary in /bin.

MATLAB_DIR := /usr/local

MATLAB_DIR := /Applications/MATLAB_R2012b.app

NOTE: this is required only if you will compile the python interface.

We need to be able to find Python.h and numpy/arrayobject.h.

#PYTHON_INCLUDE := /usr/include/python2.7 \

/usr/lib/python2.7/dist-packages/numpy/core/include

Anaconda Python distribution is quite popular. Include path:

Verify anaconda location, sometimes it’s in root.

ANACONDA_HOME := $(HOME)/anaconda
PYTHON_INCLUDE := $(ANACONDA_HOME)/include
$(ANACONDA_HOME)/include/python2.7
$(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include

Uncomment to use Python 3 (default is Python 2)

PYTHON_LIBRARIES := boost_python3 python3.5m

PYTHON_INCLUDE := /usr/include/python3.5m \

/usr/lib/python3.5/dist-packages/numpy/core/include

We need to be able to find libpythonX.X.so or .dylib.

#PYTHON_LIB := /usr/lib
PYTHON_LIB := $(ANACONDA_HOME)/lib

Homebrew installs numpy in a non standard path (keg only)

PYTHON_INCLUDE += $(dir $(shell python -c ‘import numpy.core; print(numpy.core.file)’))/include

PYTHON_LIB += $(shell brew --prefix numpy)/lib

Uncomment to support layers written in Python (will link against Python libs)

WITH_PYTHON_LAYER := 1

Whatever else you find you need goes here.

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies

INCLUDE_DIRS += $(shell brew --prefix)/include

LIBRARY_DIRS += $(shell brew --prefix)/lib

NCCL acceleration switch (uncomment to build with NCCL)

GitHub - NVIDIA/nccl: Optimized primitives for collective multi-GPU communication (last tested version: v1.2.3-1+cuda8.0)

USE_NCCL := 1

Uncomment to use pkg-config to specify OpenCV library paths.

(Usually not necessary – OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)

USE_PKG_CONFIG := 1

N.B. both build and distribute dirs are cleared on make clean

BUILD_DIR := build
DISTRIBUTE_DIR := distribute

Uncomment for debugging. Does not work on OSX due to Removing -DNDEBUG from COMMON_FLAGS in Makefile breaks OS X build · Issue #171 · BVLC/caffe · GitHub

DEBUG := 1

The ID of the GPU that ‘make runtest’ will use to run unit tests.

TEST_GPUID := 0

enable pretty build (comment to see full commands)

Q ?= @


python3
Python 3.5.2 (default, Nov 23 2017, 16:37:01)
[GCC 5.4.0 20160609] on linux
Type “help”, “copyright”, “credits” or “license” for more information.


General configuration for OpenCV 3.4.0 =====================================
– Version control: unknown

– Platform:
– Timestamp: 2018-09-14T03:55:30Z
– Host: Linux 4.4.38-tegra aarch64
– CMake: 3.5.1
– CMake generator: Unix Makefiles
– CMake build tool: /usr/bin/make
– Configuration: RELEASE

– CPU/HW features:
– Baseline: NEON FP16
– required: NEON
– disabled: VFPV3

– C/C++:
– Built as dynamic libs?: YES
– C++ Compiler: /usr/bin/c++ (ver 5.4.0)
– C++ flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG -DNDEBUG
– C++ flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -fvisibility-inlines-hidden -g -O0 -DDEBUG -D_DEBUG
– C Compiler: /usr/bin/cc
– C flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -DNDEBUG -DNDEBUG
– C flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -fdiagnostics-show-option -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -g -O0 -DDEBUG -D_DEBUG
– Linker flags (Release):
– Linker flags (Debug):
– ccache: NO
– Precompiled headers: YES
– Extra dependencies: dl m pthread rt /usr/lib/aarch64-linux-gnu/libGLU.so /usr/lib/aarch64-linux-gnu/libGL.so cudart nppc nppial nppicc nppicom nppidei nppif nppig nppim nppist nppisu nppitc npps cublas cufft -L/usr/local/cuda-9.0/lib64
– 3rdparty dependencies:

– OpenCV modules:
– To be built: calib3d core cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev dnn features2d flann highgui imgcodecs imgproc ml objdetect photo python2 python3 python_bindings_generator shape stitching superres video videoio videostab
– Disabled: js world
– Disabled by dependency: -
– Unavailable: java ts viz
– Applications: apps
– Documentation: NO
– Non-free algorithms: NO

– GUI:
– QT: YES (ver 5.5.1)
– QT OpenGL support: YES (Qt5::OpenGL 5.5.1)
– GTK+: NO
– OpenGL support: YES (/usr/lib/aarch64-linux-gnu/libGLU.so /usr/lib/aarch64-linux-gnu/libGL.so)
– VTK support: NO

– Media I/O:
– ZLib: /usr/lib/aarch64-linux-gnu/libz.so (ver 1.2.8)
– JPEG: /usr/lib/aarch64-linux-gnu/libjpeg.so (ver )
– WEBP: build (ver encoder: 0x020e)
– PNG: /usr/lib/aarch64-linux-gnu/libpng.so (ver 1.2.54)
– TIFF: /usr/lib/aarch64-linux-gnu/libtiff.so (ver 42 / 4.0.6)
– JPEG 2000: /usr/lib/aarch64-linux-gnu/libjasper.so (ver 1.900.1)
– OpenEXR: build (ver 1.7.1)

– Video I/O:
– DC1394: YES (ver 2.2.4)
– FFMPEG: YES
– avcodec: YES (ver 56.60.100)
– avformat: YES (ver 56.40.101)
– avutil: YES (ver 54.31.100)
– swscale: YES (ver 3.1.101)
– avresample: NO
– GStreamer:
– base: YES (ver 1.8.3)
– video: YES (ver 1.8.3)
– app: YES (ver 1.8.3)
– riff: YES (ver 1.8.3)
– pbutils: YES (ver 1.8.3)
– libv4l/libv4l2: 1.10.0 / 1.10.0
– v4l/v4l2: linux/videodev2.h
– gPhoto2: NO

– Parallel framework: pthreads

– Trace: YES (built-in)

– Other third-party libraries:
– Lapack: YES (/usr/lib/liblapack.so /usr/lib/libcblas.so /usr/lib/libatlas.so)
– Eigen: YES (ver 3.2.92)
– Custom HAL: YES (carotene (ver 0.0.1))

– NVIDIA CUDA: YES (ver 9.0, CUFFT CUBLAS FAST_MATH)
– NVIDIA GPU arch: 62
– NVIDIA PTX archs:

– OpenCL: YES (no extra features)
– Include path: /home/nvidia/src/opencv-3.4.0/3rdparty/include/opencl/1.2
– Link libraries: Dynamic load

– Python 2:
– Interpreter: /usr/bin/python2.7 (ver 2.7.12)
– Libraries: /usr/lib/aarch64-linux-gnu/libpython2.7.so (ver 2.7.12)
– numpy: /usr/local/lib/python2.7/dist-packages/numpy/core/include (ver 1.15.1)
– packages path: lib/python2.7/dist-packages

– Python 3:
– Interpreter: /usr/bin/python3 (ver 3.5.2)
– Libraries: /usr/lib/aarch64-linux-gnu/libpython3.5m.so (ver 3.5.2)
– numpy: /usr/local/lib/python3.5/dist-packages/numpy/core/include (ver 1.15.1)
– packages path: lib/python3.5/dist-packages

– Python (for build): /usr/bin/python2.7

– Java:
– ant: NO
– JNI: NO
– Java wrappers: NO
– Java tests: NO

– Matlab: NO

– Install to: /usr/local



– Configuring done
– Generating done
– Build files have been written to: /home/nvidia/src/opencv-3.4.0/build


Hi,

Have you added the Caffe folder into python path?
Ex.

export PYTHONPATH=$HOME/caffe/python:$PYTHONPATH

Thanks.