train.py导入parl时报错怎么解决

[Pingpongdragon]

Traceback (most recent call last):
File "train.py", line 18, in
import parl
File "/home/ljy/.local/lib/python3.8/site-packages/parl/init.py", line 54, in
from parl.remote import remote_class, connect
File "/home/ljy/.local/lib/python3.8/site-packages/parl/remote/init.py", line 19, in
from parl.remote.remote_decorator import *
File "/home/ljy/.local/lib/python3.8/site-packages/parl/remote/remote_decorator.py", line 20, in
from parl.remote.remote_wrapper import RemoteWrapper
File "/home/ljy/.local/lib/python3.8/site-packages/parl/remote/remote_wrapper.py", line 22, in
from parl.remote.communication import loads_argument, loads_return,
File "/home/ljy/.local/lib/python3.8/site-packages/parl/remote/communication.py", line 38, in
context = pyarrow.default_serialization_context()
File "/home/ljy/.local/lib/python3.8/site-packages/pyarrow/init.py", line 316, in getattr
raise AttributeError(
AttributeError: module 'pyarrow' has no attribute 'default_serialization_context'

[TomorrowIsAnOtherDay]

hello，请提供你的系统环境信息，python 环境、系统版本、parl版本等

[Pingpongdragon]

ubuntu linux系统,版本号20.04 ，python版本3.8.10，parl导入未成功

[1zeryu]

我也是这个问题：
系统环境：HOSTNAME=464884fd017f
NOTVISIBLE=in users profile
NV_LIBNPP_VERSION=11.7.3.21-1
NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-7=11.7.50-1
NVIDIA_VISIBLE_DEVICES=all
NV_NVPROF_VERSION=11.7.50-1
NV_LIBCUSPARSE_VERSION=11.7.3.50-1
NVIDIA_PRODUCT_NAME=CUDA
NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-7=11.10.1.25-1
NCCL_VERSION=2.13.4-1
PWD=/home/ysocr
NVARCH=x86_64
HOME=/root
NV_LIBCUSPARSE_DEV_VERSION=11.7.3.50-1
NVIDIA_CUDA_END_OF_LIFE=1
NV_LIBNCCL_PACKAGE_VERSION=2.13.4-1
NV_LIBNCCL_PACKAGE=libnccl2=2.13.4-1+cuda11.7
NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
NV_CUDA_LIB_VERSION=11.7.0-1
NV_LIBNPP_PACKAGE=libnpp-11-7=11.7.3.21-1
NV_LIBNCCL_PACKAGE_NAME=libnccl2
LIBRARY_PATH=/usr/local/cuda/lib64/stubs
NV_NVTX_VERSION=11.7.50-1
NV_LIBCUBLAS_VERSION=11.10.1.25-1
NV_LIBCUBLAS_PACKAGE=libcublas-11-7=11.10.1.25-1
NV_CUDNN_VERSION=8.5.0.96
NV_CUDA_CUDART_DEV_VERSION=11.7.60-1
TERM=xterm
NV_NVML_DEV_VERSION=11.7.50-1
CUDA_VERSION=11.7.0
NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-7
NVIDIA_DRIVER_CAPABILITIES=compute,utility
SHLVL=1
NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-7
NVIDIA_REQUIRE_CUDA=cuda>=11.7 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511
NV_LIBNPP_DEV_VERSION=11.7.3.21-1
NV_CUDA_CUDART_VERSION=11.7.60-1
NV_CUDNN_PACKAGE_NAME=libcudnn8
PATH=/home/venv/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
NV_LIBNCCL_DEV_PACKAGE_VERSION=2.13.4-1
NV_CUDNN_PACKAGE=libcudnn8=8.5.0.96-1+cuda11.7
Python: 3.8.0
parl版本：2.2.1

[natureLanguageQing]

我也遇到了这个问题 default_serialization_context

[natureLanguageQing]

pip install -U pyarrow==8.0.0

[natureLanguageQing]

建议官方修改为

  context = pyarrow.default_serialization_context()