[Bug] Can anyone else run new localization model TCANet with HACS dataset successfully?

[Li-XYi]

Branch

main branch (1.x version, such as v1.0.0, or dev-1.x branch)

Prerequisite

• [X] I have searched Issues and Discussions but cannot get the expected help.
• [X] I have read the documentation but cannot get the expected help.
• [X] The bug has not been fixed in the latest version.

Environment

sys.platform: linux Python: 3.8.16 (default, Mar 2 2023, 03:21:46) [GCC 11.2.0] CUDA available: True numpy_random_seed: 2147483648 GPU 0: NVIDIA GeForce RTX 3080 Ti CUDA_HOME: /usr/local/cuda-11.7 NVCC: Cuda compilation tools, release 11.7, V11.7.99 GCC: gcc (Ubuntu 7.5.0-6ubuntu2) 7.5.0 PyTorch: 2.0.0+cu117 PyTorch compiling details: PyTorch built with:

GCC 9.3 C++ Version: 201703 Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e) OpenMP 201511 (a.k.a. OpenMP 4.5) LAPACK is enabled (usually provided by MKL) NNPACK is enabled CPU capability usage: AVX2 CUDA Runtime 11.7 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_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 CuDNN 8.8 (built against CUDA 11.8) Built with CuDNN 8.5 Magma 2.6.1 Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -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 -fdiagnostics-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_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.15.1+cu117 OpenCV: 4.7.0 MMEngine: 0.7.1 MMAction2: 1.1.0+f2637ee MMCV: 2.0.0 MMDetection: 3.0.0 MMPose: 1.0.0

Describe the bug

At the model file mmaction2/mmaction/models/localizers/tcanet.py line 459:

        proposals_ = [
            sample.proposals['proposals'] for sample in batch_data_samples
        ]

it does require attribute proposals, when the model executes the predict process. But the HACS dataset actually doesn't contain 'proposals' attribute, after following the dataset processing.

so, I truely doubt that the model TCANet can actually work with HACS dataset.

Reproduces the problem - code sample

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Reproduces the problem - command or script

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Reproduces the problem - error message

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Additional information

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