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https://github.com/Young1993/ffa

A Context-aware Feature Fusion Framework for Punctuation Restoration
https://github.com/Young1993/ffa
Last synced: 28 days ago
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A Context-aware Feature Fusion Framework for Punctuation Restoration
Host: GitHub
URL: https://github.com/Young1993/ffa
Owner: Young1993
Created: 2022-02-28T03:15:41.000Z (almost 3 years ago)
Default Branch: master
Last Pushed: 2022-03-19T08:15:59.000Z (over 2 years ago)
Last Synced: 2024-08-04T00:11:01.500Z (4 months ago)
Language: Python
Size: 9.14 MB
Stars: 4
Watchers: 2
Forks: 3
Open Issues: 1
Metadata Files:
- Readme: README.md
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README

        # FFA-for-Punctuation-Restoration

Source code for A Context-aware Feature Fusion Framework for Punctuation Restoration. We would appreciate it if you cite our paper as following:

```

```

## Methods

+ parallel_enc_dec.py

+ modeling_funnel.py(talk_matrix)

## Pre-trained Language Models

+ facebook/bart-large

+ funnel-transformer/xlarge

## Directory

+ **main** - Source Code

+ **main/train.py** - Training Process

+ **main/config.py** - Training Configurations

+ **main/res/data/raw** - IWSLT Source Data

+ **main/src/models** - Models

+ **main/src/utils** - Helper Function

## Dependencies

+ python >= 3.8.5

+ jupyterlab >= 3.1.4

+ flair >= 0.8.

+ scikit_learn >= 0.24.1

+ torch >= 1.7.1

+ tqdm >= 4.57.0

+ transformers >= 4.3.2

+ ipywidgets >= 7.6.3

## Setup

Please ensure required packages are already installed. A virtual environment is recommended.

```

$ cd FFA_punc_restore

$ cd main

$ pip install pip --upgrade

$ pip install -r requirements.txt

Looking in indexes: http://mirrors.cloud.aliyuncs.com/pypi/simple/

Collecting flair==0.8

  Downloading http://mirrors.cloud.aliyuncs.com/pypi/packages/16/a9/02ab3594958a89c5477f2820a19158187e095763ab6d5d6c0aa5a896087c/flair-0.8-py3-none-any.whl (277 kB)

     |████████████████████████████████| 277 kB 23.4 MB/s

...

...

...

Installing collected packages: urllib3, numpy, idna, chardet, zipp, tqdm, smart-open, six, scipy, requests, regex, PySocks, pyparsing, joblib, decorator, click, wrapt, wcwidth, typing-extensions, tokenizers, threadpoolctl, sentencepiece, sacremoses, python-dateutil, pillow, packaging, overrides, networkx, kiwisolver, importlib-metadata, gensim, future, filelock, cycler, cloudpickle, transformers, torch, tabulate, sqlitedict, segtok, scikit-learn, mpld3, matplotlib, lxml, langdetect, konoha, janome, hyperopt, huggingface-hub, gdown, ftfy, deprecated, bpemb, flair

Successfully installed PySocks-1.7.1 bpemb-0.3.2 chardet-4.0.0 click-7.1.2 cloudpickle-1.6.0 cycler-0.10.0 decorator-4.4.2 deprecated-1.2.12 filelock-3.0.12 flair-0.8 ftfy-5.9 future-0.18.2 gdown-3.12.2 gensim-3.8.3 huggingface-hub-0.0.7 hyperopt-0.2.5 idna-2.10 importlib-metadata-3.7.3 janome-0.4.1 joblib-1.0.1 kiwisolver-1.3.1 konoha-4.6.4 langdetect-1.0.8 lxml-4.6.3 matplotlib-3.4.0 mpld3-0.3 networkx-2.5 numpy-1.19.5 overrides-3.1.0 packaging-20.9 pillow-8.1.2 pyparsing-2.4.7 python-dateutil-2.8.1 regex-2021.3.17 requests-2.25.1 sacremoses-0.0.43 scikit-learn-0.24.1 scipy-1.6.2 segtok-1.5.10 sentencepiece-0.1.95 six-1.15.0 smart-open-4.2.0 sqlitedict-1.7.0 tabulate-0.8.9 threadpoolctl-2.1.0 tokenizers-0.10.1 torch-1.7.1 tqdm-4.57.0 transformers-4.3.2 typing-extensions-3.7.4.3 urllib3-1.26.4 wcwidth-0.2.5 wrapt-1.12.1 zipp-3.4.1

```

## Run

Before training, please take a look at the **config.py** to ensure training configurations.

```

$ cd main

$ vim config.py

$ python train.py

```

## Output

If everything goes well, you should see a similar progressing shown as below.

```

*Configuration*

*Configuration*

model: parallelendecoder

language model: funnel-transformer/xlarge

freeze language model: False

sequence boundary sampling: random

mask loss: False

trainable parameters: 907,906,052

model:

encode_layer.embeddings.word_embeddings.weight	torch.Size([30522, 1024])

encode_layer.embeddings.layer_norm.weight	torch.Size([1024])

encode_layer.embeddings.layer_norm.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.attention.r_w_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.0.0.attention.r_r_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.0.0.attention.r_kernel	torch.Size([1024, 16, 64])

encode_layer.encoder.blocks.0.0.attention.r_s_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.0.0.attention.seg_embed	torch.Size([2, 16, 64])

encode_layer.encoder.blocks.0.0.attention.talk_matrix	torch.Size([16, 16])

encode_layer.encoder.blocks.0.0.attention.q_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.0.0.attention.k_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.0.0.attention.k_head.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.attention.v_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.0.0.attention.v_head.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.attention.post_proj.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.0.0.attention.post_proj.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.attention.layer_norm.weight	torch.Size([1024])

encode_layer.encoder.blocks.0.0.attention.layer_norm.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.ffn.linear_1.weight	torch.Size([4096, 1024])

encode_layer.encoder.blocks.0.0.ffn.linear_1.bias	torch.Size([4096])

encode_layer.encoder.blocks.0.0.ffn.linear_2.weight	torch.Size([1024, 4096])

encode_layer.encoder.blocks.0.0.ffn.linear_2.bias	torch.Size([1024])

encode_layer.encoder.blocks.0.0.ffn.layer_norm.weight	torch.Size([1024])

encode_layer.encoder.blocks.0.0.ffn.layer_norm.bias	torch.Size([1024])

...

...

...

encode_layer.encoder.blocks.2.9.attention.r_w_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.2.9.attention.r_r_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.2.9.attention.r_kernel	torch.Size([1024, 16, 64])

encode_layer.encoder.blocks.2.9.attention.r_s_bias	torch.Size([16, 64])

encode_layer.encoder.blocks.2.9.attention.seg_embed	torch.Size([2, 16, 64])

encode_layer.encoder.blocks.2.9.attention.talk_matrix	torch.Size([16, 16])

encode_layer.encoder.blocks.2.9.attention.q_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.2.9.attention.k_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.2.9.attention.k_head.bias	torch.Size([1024])

encode_layer.encoder.blocks.2.9.attention.v_head.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.2.9.attention.v_head.bias	torch.Size([1024])

encode_layer.encoder.blocks.2.9.attention.post_proj.weight	torch.Size([1024, 1024])

encode_layer.encoder.blocks.2.9.attention.post_proj.bias	torch.Size([1024])

encode_layer.encoder.blocks.2.9.attention.layer_norm.weight	torch.Size([1024])

encode_layer.encoder.blocks.2.9.attention.layer_norm.bias	torch.Size([1024])

encode_layer.encoder.blocks.2.9.ffn.linear_1.weight	torch.Size([4096, 1024])

encode_layer.encoder.blocks.2.9.ffn.linear_1.bias	torch.Size([4096])

encode_layer.encoder.blocks.2.9.ffn.linear_2.weight	torch.Size([1024, 4096])

encode_layer.encoder.blocks.2.9.ffn.linear_2.bias	torch.Size([1024])

encode_layer.encoder.blocks.2.9.ffn.layer_norm.weight	torch.Size([1024])

encode_layer.encoder.blocks.2.9.ffn.layer_norm.bias	torch.Size([1024])

encode_layer.decoder.layers.0.attention.r_w_bias	torch.Size([16, 64])

encode_layer.decoder.layers.0.attention.r_r_bias	torch.Size([16, 64])

encode_layer.decoder.layers.0.attention.r_kernel	torch.Size([1024, 16, 64])

encode_layer.decoder.layers.0.attention.r_s_bias	torch.Size([16, 64])

encode_layer.decoder.layers.0.attention.seg_embed	torch.Size([2, 16, 64])

encode_layer.decoder.layers.0.attention.talk_matrix	torch.Size([16, 16])

encode_layer.decoder.layers.0.attention.q_head.weight	torch.Size([1024, 1024])

encode_layer.decoder.layers.0.attention.k_head.weight	torch.Size([1024, 1024])

encode_layer.decoder.layers.0.attention.k_head.bias	torch.Size([1024])

encode_layer.decoder.layers.0.attention.v_head.weight	torch.Size([1024, 1024])

encode_layer.decoder.layers.0.attention.v_head.bias	torch.Size([1024])

encode_layer.decoder.layers.0.attention.post_proj.weight	torch.Size([1024, 1024])

encode_layer.decoder.layers.0.attention.post_proj.bias	torch.Size([1024])

encode_layer.decoder.layers.0.attention.layer_norm.weight	torch.Size([1024])

encode_layer.decoder.layers.0.attention.layer_norm.bias	torch.Size([1024])

encode_layer.decoder.layers.0.ffn.linear_1.weight	torch.Size([4096, 1024])

encode_layer.decoder.layers.0.ffn.linear_1.bias	torch.Size([4096])

encode_layer.decoder.layers.0.ffn.linear_2.weight	torch.Size([1024, 4096])

encode_layer.decoder.layers.0.ffn.linear_2.bias	torch.Size([1024])

encode_layer.decoder.layers.0.ffn.layer_norm.weight	torch.Size([1024])

encode_layer.decoder.layers.0.ffn.layer_norm.bias	torch.Size([1024])

...

...

...

decode_layer.encoder.layers.11.self_attn.k_proj.weight	torch.Size([1024, 1024])

decode_layer.encoder.layers.11.self_attn.k_proj.bias	torch.Size([1024])

decode_layer.encoder.layers.11.self_attn.v_proj.weight	torch.Size([1024, 1024])

decode_layer.encoder.layers.11.self_attn.v_proj.bias	torch.Size([1024])

decode_layer.encoder.layers.11.self_attn.q_proj.weight	torch.Size([1024, 1024])

decode_layer.encoder.layers.11.self_attn.q_proj.bias	torch.Size([1024])

decode_layer.encoder.layers.11.self_attn.out_proj.weight	torch.Size([1024, 1024])

decode_layer.encoder.layers.11.self_attn.out_proj.bias	torch.Size([1024])

decode_layer.encoder.layers.11.self_attn_layer_norm.weight	torch.Size([1024])

decode_layer.encoder.layers.11.self_attn_layer_norm.bias	torch.Size([1024])

decode_layer.encoder.layers.11.fc1.weight	torch.Size([4096, 1024])

decode_layer.encoder.layers.11.fc1.bias	torch.Size([4096])

decode_layer.encoder.layers.11.fc2.weight	torch.Size([1024, 4096])

decode_layer.encoder.layers.11.fc2.bias	torch.Size([1024])

decode_layer.encoder.layers.11.final_layer_norm.weight	torch.Size([1024])

decode_layer.encoder.layers.11.final_layer_norm.bias	torch.Size([1024])

decode_layer.encoder.layernorm_embedding.weight	torch.Size([1024])

decode_layer.encoder.layernorm_embedding.bias	torch.Size([1024])

decode_layer.decoder.embed_tokens.weight	torch.Size([50265, 1024])

decode_layer.decoder.embed_positions.weight	torch.Size([1026, 1024])

decode_layer.decoder.layers.0.self_attn.k_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.self_attn.k_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.self_attn.v_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.self_attn.v_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.self_attn.q_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.self_attn.q_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.self_attn.out_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.self_attn.out_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.self_attn_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.0.self_attn_layer_norm.bias	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn.k_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.encoder_attn.k_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn.v_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.encoder_attn.v_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn.q_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.encoder_attn.q_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn.out_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.0.encoder_attn.out_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.0.encoder_attn_layer_norm.bias	torch.Size([1024])

decode_layer.decoder.layers.0.fc1.weight	torch.Size([4096, 1024])

decode_layer.decoder.layers.0.fc1.bias	torch.Size([4096])

decode_layer.decoder.layers.0.fc2.weight	torch.Size([1024, 4096])

decode_layer.decoder.layers.0.fc2.bias	torch.Size([1024])

decode_layer.decoder.layers.0.final_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.0.final_layer_norm.bias	torch.Size([1024])

...

...

...

decode_layer.decoder.layers.11.self_attn.k_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.self_attn.k_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.self_attn.v_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.self_attn.v_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.self_attn.q_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.self_attn.q_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.self_attn.out_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.self_attn.out_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.self_attn_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.11.self_attn_layer_norm.bias	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn.k_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.encoder_attn.k_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn.v_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.encoder_attn.v_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn.q_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.encoder_attn.q_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn.out_proj.weight	torch.Size([1024, 1024])

decode_layer.decoder.layers.11.encoder_attn.out_proj.bias	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.11.encoder_attn_layer_norm.bias	torch.Size([1024])

decode_layer.decoder.layers.11.fc1.weight	torch.Size([4096, 1024])

decode_layer.decoder.layers.11.fc1.bias	torch.Size([4096])

decode_layer.decoder.layers.11.fc2.weight	torch.Size([1024, 4096])

decode_layer.decoder.layers.11.fc2.bias	torch.Size([1024])

decode_layer.decoder.layers.11.final_layer_norm.weight	torch.Size([1024])

decode_layer.decoder.layers.11.final_layer_norm.bias	torch.Size([1024])

decode_layer.decoder.layernorm_embedding.weight	torch.Size([1024])

decode_layer.decoder.layernorm_embedding.bias	torch.Size([1024])

fusion_layer.self_attn.in_proj_weight	torch.Size([6144, 2048])

fusion_layer.self_attn.in_proj_bias	torch.Size([6144])

fusion_layer.self_attn.out_proj.weight	torch.Size([2048, 2048])

fusion_layer.self_attn.out_proj.bias	torch.Size([2048])

fusion_layer.linear1.weight	torch.Size([4096, 2048])

fusion_layer.linear1.bias	torch.Size([4096])

fusion_layer.linear2.weight	torch.Size([2048, 4096])

fusion_layer.linear2.bias	torch.Size([2048])

fusion_layer.norm1.weight	torch.Size([2048])

fusion_layer.norm1.bias	torch.Size([2048])

fusion_layer.norm2.weight	torch.Size([2048])

fusion_layer.norm2.bias	torch.Size([2048])

out_layer.weight	torch.Size([4, 2048])

out_layer.bias	torch.Size([4])

device: cuda

train size: 8950

val size: 1273

ref test size: 54

asr test size: 54

batch size: 8

train batch: 1118

val batch: 160

ref test batch: 7

asr test batch: 7

valid win size: 8

if load check point: False

Training...

Loss:0.9846:   1%|█▊                                                                                                                                                                                                    | 5/559 [00:02<03:30,  2.63it/s]

```

## Note

1. 可以在 ./main/src/modes/parallel_enc_dec.py 修改预训练模型

## Authors

If you have any question, please email to Kebin.

* **Kebin Fang** [email protected]