huangfaan
commented
3 years ago Thank you for opensourcing the great work. My environment is Ubuntu 18.04, RTX 2070. Now I can successfully make and install DIRT. But when I run test, I got
WARNING: failed to load librasterise.so; rasterisation functions will be unavailable: /home/rayu/Projects/HOnnotate/dirt/dirt/librasterise.so: undefined symbol: _ZN10tensorflow7strings8internal9CatPiecesB5cxx11ESt16initializer_listIN4absl11string_viewEE WARNING:tensorflow:From tests/square_test.py:43: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead. 2021-01-23 12:28:30.777188: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2021-01-23 12:28:30.819102: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.819712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: GeForce RTX 2070 with Max-Q Design major: 7 minor: 5 memoryClockRate(GHz): 1.125 pciBusID: 0000:01:00.0 2021-01-23 12:28:30.827329: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-01-23 12:28:30.840414: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-01-23 12:28:30.846988: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-01-23 12:28:30.849245: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-01-23 12:28:30.863268: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-01-23 12:28:30.873064: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-01-23 12:28:30.897700: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-01-23 12:28:30.897806: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.898216: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.898548: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-01-23 12:28:30.921198: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2021-01-23 12:28:30.925201: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2299965000 Hz 2021-01-23 12:28:30.925575: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55e07c53c080 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2021-01-23 12:28:30.925588: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2021-01-23 12:28:30.973652: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.974148: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55e07c53bb70 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2021-01-23 12:28:30.974162: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce RTX 2070 with Max-Q Design, Compute Capability 7.5 2021-01-23 12:28:30.974264: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.974581: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: GeForce RTX 2070 with Max-Q Design major: 7 minor: 5 memoryClockRate(GHz): 1.125 pciBusID: 0000:01:00.0 2021-01-23 12:28:30.974602: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-01-23 12:28:30.974609: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0 2021-01-23 12:28:30.974615: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0 2021-01-23 12:28:30.974621: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0 2021-01-23 12:28:30.974629: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0 2021-01-23 12:28:30.974636: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0 2021-01-23 12:28:30.974643: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-01-23 12:28:30.974669: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.974985: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.975285: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2021-01-23 12:28:30.975304: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0 2021-01-23 12:28:30.979038: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-01-23 12:28:30.979050: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2021-01-23 12:28:30.979055: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2021-01-23 12:28:30.979112: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.979442: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-01-23 12:28:30.979763: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7264 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 7.5) Traceback (most recent call last): File "tests/square_test.py", line 61, in <module> main() File "tests/square_test.py", line 47, in main dirt_pixels = get_dirt_pixels().eval() File "tests/square_test.py", line 35, in get_dirt_pixels height=canvas_height, width=canvas_width, channels=1 File "/home/rayu/Projects/HOnnotate/dirt/dirt/rasterise_ops.py", line 48, in rasterise return rasterise_batch(background[None], vertices[None], vertex_colors[None], faces[None], height, width, channels, name)[0] File "/home/rayu/Projects/HOnnotate/dirt/dirt/rasterise_ops.py", line 81, in rasterise_batch return _rasterise_module.rasterise( AttributeError: 'NoneType' object has no attribute 'rasterise'I'm using conda to set the python environment.
# packages in environment at /home/rayu/miniconda3/envs/hon: # # Name Version Build Channel _libgcc_mutex 0.1 main https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main _tflow_select 2.1.0 gpu https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main absl-py 0.11.0 pyhd3eb1b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main astor 0.8.1 py37_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main c-ares 1.17.1 h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main ca-certificates 2021.1.19 h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main certifi 2020.12.5 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main cudatoolkit 10.0.130 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main cudnn 7.6.5 cuda10.0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main cupti 10.0.130 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main dirt 0.3.0 dev_0 <develop> gast 0.2.2 py37_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main google-pasta 0.2.0 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main grpcio 1.31.0 py37hf8bcb03_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main h5py 2.10.0 py37hd6299e0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main hdf5 1.10.6 hb1b8bf9_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main importlib-metadata 2.0.0 py_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main intel-openmp 2020.2 254 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main keras-applications 1.0.8 py_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main keras-preprocessing 1.1.0 py_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main ld_impl_linux-64 2.33.1 h53a641e_7 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libedit 3.1.20191231 h14c3975_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libffi 3.3 he6710b0_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libgcc-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libgfortran-ng 7.3.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libprotobuf 3.13.0.1 hd408876_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main libstdcxx-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main markdown 3.3.3 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main mkl 2020.2 256 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main mkl-service 2.3.0 py37he8ac12f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main mkl_fft 1.2.0 py37h23d657b_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main mkl_random 1.1.1 py37h0573a6f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main ncurses 6.2 he6710b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main numpy 1.19.2 py37h54aff64_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main numpy-base 1.19.2 py37hfa32c7d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main openssl 1.1.1i h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main opt_einsum 3.1.0 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main pip 20.3.3 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main protobuf 3.13.0.1 py37he6710b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main python 3.7.9 h7579374_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main readline 8.0 h7b6447c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main scipy 1.5.2 py37h0b6359f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main setuptools 51.3.3 py37h06a4308_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main six 1.15.0 py37h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main sqlite 3.33.0 h62c20be_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorboard 1.15.0 pyhb230dea_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorflow 1.15.0 gpu_py37h0f0df58_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorflow-base 1.15.0 gpu_py37h9dcbed7_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorflow-estimator 1.15.1 pyh2649769_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tensorflow-gpu 1.15.0 pypi_0 pypi termcolor 1.1.0 py37_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main tk 8.6.10 hbc83047_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main webencodings 0.5.1 py37_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main werkzeug 0.16.1 py_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main wheel 0.36.2 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main wrapt 1.12.1 py37h7b6447c_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main xz 5.2.5 h7b6447c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main zipp 3.4.0 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main zlib 1.2.11 h7b6447c_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
I have encountered the same problem, how to resolve it, please？
sahil-syze
Thank you for opensourcing the great work. My environment is Ubuntu 18.04, RTX 2070. Now I can successfully make and install DIRT. But when I run test, I got
I'm using conda to set the python environment.