[Bug] OSError: Can't load tokenizer for 'roberta-base'.

mrsempress commented 3 months ago

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version (dev-1.x) or latest version (dev-1.0).

Task

I'm using the official example scripts/configs for the officially supported tasks/models/datasets.

Branch

main branch https://github.com/open-mmlab/mmdetection3d

Environment

System environment: [1085/1460] sys.platform: linux Python: 3.8.17 (default, Jul 5 2023, 21:04:15) [GCC 11.2.0] CUDA available: True MUSA available: False numpy_random_seed: 1551893665 GPU 0,1: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/lustre/share/cuda-11.0 NVCC: Cuda compilation tools, release 11.0, V11.0.221 GCC: gcc (GCC) 5.4.0 PyTorch: 1.12.1 PyTorch compiling details: PyTorch built with:

GCC 9.3
C++ Version: 201402
Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815)
OpenMP 201511 (a.k.a. OpenMP 4.5)
LAPACK is enabled (usually provided by MKL)
NNPACK is enabled
CPU capability usage: AVX2
CUDA Runtime 11.3
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code= sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37
CuDNN 8.3.2 (built against CUDA 11.5)
Magma 2.5.2
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSEKINETO -DUSE$ BGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unuse$ -parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostic$ -color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.$ , USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.13.1 OpenCV: 4.9.0 MMEngine: 0.10.3

Reproduces the problem - code sample

In embodiedscan/models/detectors/sparse_featfusion_grounder.py line 100: self.tokenizer = RobertaTokenizerFast.from_pretrained(t_type)

Reproduces the problem - command or script

sh tools/mv-grounding.sh

Reproduces the problem - error message

Traceback (most recent call last): File "tools/train.py", line 133, in Traceback (most recent call last): File "tools/train.py", line 133, in main() File "tools/train.py", line 122, in main main() File "tools/train.py", line 122, in main runner = Runner.from_cfg(cfg) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 462, in from_cfg runner = Runner.from_cfg(cfg) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 462, in from_cfg runner = cls( File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 429, in init runner = cls( File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 429, in init self.model = self.build_model(model) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 836, in build_model self.model = self.build_model(model) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/runner/runner.py", line 836, in build_model model = MODELS.build(model) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/registry.py", line 570, in build model = MODELS.build(model) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/registry.py", line 570, in build return self.build_func(cfg, *args, *kwargs, registry=self) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 232, in build_model_from_cfg return self.build_func(cfg, args, kwargs, registry=self) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 232, in build_model_from_cfg return build_from_cfg(cfg, registry, default_args) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg return build_from_cfg(cfg, registry, default_args) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg obj = obj_cls(args) # type: ignore File "/mnt/petrelfs/huangchenxi/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 94, in init obj = obj_cls(**args) # type: ignore File "/mnt/petrelfs/huangchenxi/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 94, in init self._init_layers() File "/mnt/petrelfs/huangchenxi/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 100, in _init_layers self._init_layers() File "/mnt/petrelfs/huangchenxi/EmbodiedScan/embodiedscan/models/detectors/sparse_featfusion_grounder.py", line 100, in _init_layers self.tokenizer = RobertaTokenizerFast.from_pretrained(t_type) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 2070, in from_pretrained self.tokenizer = RobertaTokenizerFast.from_pretrained(t_type) File "/mnt/lustre/huangchenxi/anaconda3/envs/visual/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 2070, in from_pretrained raise EnvironmentError( OSError: Can't load tokenizer for 'roberta-base'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'roberta-base' is the correct path to a directory containing all relevant files for a RobertaTokenizerFast tokenizer.

Additional information

No response

zhanghm1995 commented 3 months ago

@mrsempress , have you solved this problem? I have tried to log in to the Hugging Face, however, the network is not available to connect to HF.

mrsempress commented 3 months ago

I solved this problem. I logged in to the huggingface, and used vpn.

zhanghm1995 commented 3 months ago

Ok, I see. It seems we must use the VPN. Thanks a lot.

OpenRobotLab / EmbodiedScan