PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network

Related tags

Deep Learning hierarchical-multi-label-text-classification
Overview

hierarchical-multi-label-text-classification-pytorch

Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach

This repository is a PyTorch implementation made with reference to this research project.

The main objective of the project is to solve the hierarchical multi-label text classification (HMTC) problem. Different from the multi-label text classification, HMTC assigns each instance (object) into multiple categories and these categories are stored in a hierarchy structure, is a fundamental but challenging task of numerous applications.

Introduction

Many real-world applications organize data in a hierarchical structure, where classes are specialized into subclasses or grouped into superclasses. For example, an electronic document (e.g. web-pages, digital libraries, patents and e-mails) is associated with multiple categories and all these categories are stored hierarchically in a tree or Direct Acyclic Graph (DAG).

It provides an elegant way to show the characteristics of data and a multi-dimensional perspective to tackle the classification problem via hierarchy structure.

The Figure shows an example of predefined labels in hierarchical multi-label classification of documents in patent texts.

  • Documents are shown as colored rectangles, labels as rounded rectangles.
  • Circles in the rounded rectangles indicate that the corresponding document has been assigned the label.
  • Arrows indicate a hierarchical structure between labels.

Data

See data format in data folder which including the data sample files.

Text Segment

You can use jieba package if you are going to deal with the Chinese text data.

Data Format

This repository can be used in other datasets (text classification) in two ways:

  1. Modify your datasets into the same format of the sample.
  2. Modify the data preprocess code in data_helpers.py, data_loader.py.

Anyway, it should depend on what your data and task are.

Pre-trained Word Vectors

You can pre-training your word vectors(based on your corpus) in many ways:

  • Use gensim package to pre-train data.
  • Use glove tools to pre-train data.
  • Even can use a fasttext network to pre-train data.
  • This implementation used an embedding layer, but the original paper uses word2vec.

Network Structure

Built with

  • Python 3.8
  • Pytorch
  • Numpy
  • Sklearn
Comments
  • IndexError: index out of range in self

    IndexError: index out of range in self

    When I tried to run the code in Linux command, it occured: IndexError: index out of range in self

      File "train.py", line 236, in <module>
    main()
  File "train.py", line 233, in main
    train(args)
  File "train.py", line 87, in train
    _, outputs = net(x_train)
  File "/opt/conda/envs/torch-env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/laihuapeng01/hierarchical-multi-label-text-classification/models/harnn.py", line 70, in forward
    embedded_sentence = self.embedding(input_x)
  File "/opt/conda/envs/torch-env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/opt/conda/envs/torch-env/lib/python3.8/site-packages/torch/nn/modules/sparse.py", line 158, in forward
    return F.embedding(
  File "/opt/conda/envs/torch-env/lib/python3.8/site-packages/torch/nn/functional.py", line 2044, in embedding
    return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)

    Can u explain what problem it is ? THX first!

    opened by hopkin-lai 9
  • The result issue

    The result issue

    Now the code works fine, there is no error any more. But the results of the experiment looks terrible to me. Is it a common issue (algorithm itself) or something wrong with my testing? ( I am also using the original data set in this repository)

    root - INFO - All Validation set: Loss 1.44963 | AUC 0.354399 | AUPRC 0.000575171
root - INFO - Predict by threshold: Precision 0.000449691, Recall 0.242424, F 0.000897716
root - INFO - Predict by topK:
root - INFO - Top1: Precision 0, Recall 0, F 0
root - INFO - Top2: Precision 0, Recall 0, F 0
root - INFO - Top3: Precision 0, Recall 0, F 0
root - INFO - Top4: Precision 0, Recall 0, F 0
root - INFO - Top5: Precision 0, Recall 0, F 0
root - INFO - Finished Training.
    opened by hopkin-lai 5
  • Result looks some strange

    Result looks some strange

    root - INFO - All Validation set: Loss 0.00198838 | AUC 0.97652 | AUPRC 0.338539 root - INFO - Predict by threshold: Precision 0.716505, Recall 0.196933, F 0.30895 root - INFO - Predict by topK: root - INFO - Top1: Precision 0.839844, Recall 0.108801, F 0.192646 root - INFO - Top2: Precision 0.686198, Recall 0.177793, F 0.282414 root - INFO - Top3: Precision 0.591112, Recall 0.229735, F 0.330876 root - INFO - Top4: Precision 0.519005, Recall 0.268948, F 0.354299 root - INFO - Top5: Precision 0.463862, Recall 0.300466, F 0.364699

    I use all dataset (from google drive) to train, But it result shows F1 score is too low. Can any suggestions give me?

    opened by gumanchang 4
  • core dumped

    core dumped

    Hi, I encountered some CUDA errors, can you help on this?

    reproducing command: CUDA_VISIBLE_DEVICES=0 python train.py pytorch version: 1.8.0+cu111 CUDA Version: 11.2 error details: /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [96,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [97,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [98,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [99,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [100,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [101,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [102,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [103,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [104,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [105,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [106,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [107,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [108,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [109,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [110,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [111,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [64,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [65,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [66,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [67,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [68,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [69,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [70,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [71,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [72,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [73,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [74,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [75,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [76,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [77,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [78,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [79,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [80,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [81,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [82,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [83,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [84,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [85,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [86,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [87,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [88,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [89,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [90,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [91,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [92,0,0] Assertion srcIndex < srcSelectDimSize failed. terminate called after throwing an instance of 'c10::Error' /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [93,0,0 what(): CUDA error: device-side assert triggered Exception raised from record at /pytorch/aten/src/ATen/cuda/CUDAEvent.h:116 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x42 (0x7f9cf4eb92f2 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libc10.so) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x5b (0x7f9cf4eb667b in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libc10.so) frame #2: + 0x25fdc6b5 (0x7f9a1aa336b5 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cuda_cpp.so) frame #3: + 0x25bb613a (0x7f9a1a60d13a in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cuda_cpp.so) frame #4: + 0x25fd1d03 (0x7f9a1aa28d03 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cuda_cpp.so) frame #5: + 0x10c4ee8 (0x7f9a6a999ee8 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so) frame #6: at::native::lstm(at::Tensor const&, c10::ArrayRefat::Tensor, c10::ArrayRefat::Tensor, bool, long, double, bool, bool, bool) + 0x23b (0x7f9a6a9838bb in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so) frame #7: + 0x17c31f7 (0x7f9a6b0981f7 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so) frame #8: + 0x17c327c (0x7f9a6b09827c in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so) frame #9: at::lstm(at::Tensor const&, c10::ArrayRefat::Tensor, c10::ArrayRefat::Tensor, bool, long, double, bool, bool, bool) + 0x24b (0x7f9a6ae10e8b in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so) frame #10: + 0x40d0b3 (0x7f9b64abd0b3 in /data/shaoqing.tan/anaconda3/envs/albef_py/lib/python3.7/site-packages/torch/lib/libtorch_python.so) frame #46: __libc_start_main + 0xf0 (0x7f9cf9d77840 in /lib/x86_64-linux-gnu/libc.so.6)

    ] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [94,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [95,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [32,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [33,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [34,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [35,0,0] Assertion srcIndex < srcSelectDimSize failed. /pytorch/aten/src/ATen/native/cuda/Indexing.cu:662: indexSelectLargeIndex: block: [156,0,0], thread: [36,0,0] Assertion srcIndex < srcSelectDimSize failed. Aborted (core dumped)

    opened by cultivater 2
  • The reason for low performance, vocabs in train_dataset and test_dataset are not the same

    The reason for low performance, vocabs in train_dataset and test_dataset are not the same

    Maybe I found the reason for low performance, vocabs in train_dataset and test_dataset are not the same, that means the same token may have different index. Can help check if right?

    opened by zhanxlin 3
Owner
Mingu Kang
SW Engineering / ML / DL / Blockchain Dept. of Software Engineering, Jeonbuk National University
Mingu Kang
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