Skip to content

Latest commit

 

History

History
169 lines (130 loc) · 6.03 KB

README.md

File metadata and controls

169 lines (130 loc) · 6.03 KB

bert-online

An online version of BERT for AI Network. The source code is originated in github.com/google-research/bert and was modified for our purpose. For the full context of the code, see the original code repository.

How to run on AIN Cloud beta

See AIN.md for a guide to play with the code on AIN Cloud beta, which is a product provided by AI Network.

How to run using commandlines

It can be run in Docker containers using the commandlines below:

Run w/ tensorflow docker image (on CPU machine):

NOTE: You need to train the model first before using the commandline below (See How to train BERT models).

DOCKER_BERT_DIR=/bert
TF_CPP_MIN_LOG_LEVEL=2

docker run -v $PWD:/bert \
  -w /bert \
  --env PYTHONPATH=/bert \
  --rm tensorflow/tensorflow \
  python /bert/bert_online/run_squad_online.py \
  --vocab_file=$DOCKER_BERT_DIR/model_base_cased/vocab.txt \
  --bert_config_file=$DOCKER_BERT_DIR/model_base_cased/bert_config.json \
  --init_checkpoint=$DOCKER_BERT_DIR/squad1.1-output-train_2/model.ckpt-14599 \
  --max_seq_length=320 \
  --doc_stride=128 \
  --n_best_size=3

Run w/ bert-online docker image (on CPU machine):

docker run -v $PWD/bert_online:/bert/bert_online \
  -w /bert \
  --env PYTHONPATH=/bert \
  -t --rm comcomai/bert-online:1.0.0 \
  python /bert/bert_online/run_squad_online.py \
  --vocab_file=/bert/model_base_cased/vocab.txt \
  --bert_config_file=/bert/model_base_cased/bert_config.json \
  --init_checkpoint=/bert/squad1.1-output-train_2/model.ckpt-14599 \
  --max_seq_length=320 \
  --doc_stride=128 \
  --n_best_size=3

Run w/ tensorflow-gpu docker image (on GPU machine):

NOTE: You need to train the model first before using the commandline below (See How to train BERT models).

DOCKER_BERT_DIR=/bert

docker run -v $PWD:/bert \
  -w /bert \
  --env PYTHONPATH=/bert \
  --runtime=nvidia --rm tensorflow/tensorflow:1.12.0-rc2-gpu \
  python /bert/bert_online/run_squad_online.py \
  --vocab_file=$DOCKER_BERT_DIR/model_base_cased/vocab.txt \
  --bert_config_file=$DOCKER_BERT_DIR/model_base_cased/bert_config.json \
  --init_checkpoint=$DOCKER_BERT_DIR/squad1.1-output-train_2/model.ckpt-14599 \

--max_seq_length=320 \
  --doc_stride=128 \
  --n_best_size=3

Run w/ bert-online-gpu docker image (on GPU machine):

docker run -v $PWD/bert_online:/bert/bert_online \
  -w /bert \
  --env PYTHONPATH=/bert \
  --runtime=nvidia -t --rm comcomai/bert-online:1.0.0-gpu \
  python /bert/bert_online/run_squad_online.py \
  --vocab_file=/bert/model_base_cased/vocab.txt \
  --bert_config_file=/bert/model_base_cased/bert_config.json \
  --init_checkpoint=/bert/squad1.1-output-train_2/model.ckpt-14599 \
  --max_seq_length=320 \
  --doc_stride=128 \
  --n_best_size=3

How to train BERT models

BERT models can be trained using the commandlines below.

For more details, please refer to BERT GitHub README.

Download pre-trained model

Download BERT-Base, Cased model files and put them under model_base_cased directory.

Download SQuAD files

Download SQuAD1.1 files and put them under squad1.1 directory:

Download BERT code

Download BERT source code and put them under bert directory.

Train BERT model (on GPU machine):

DOCKER_BERT_BASE_DIR=/bert/model_base_cased
DOCKER_SQUAD_DIR=/bert/squad1.1
DOCKER_OUTPUT_DIR=/bert/squad1.1-output

docker run -v  $PWD:/bert \
  -w /bert \
  --runtime=nvidia --rm tensorflow/tensorflow:latest-gpu \
  python /bert/bert/run_squad.py \
  --vocab_file=$DOCKER_BERT_BASE_DIR/vocab.txt \
  --bert_config_file=$DOCKER_BERT_BASE_DIR/bert_config.json \
  --init_checkpoint=$DOCKER_BERT_BASE_DIR/bert_model.ckpt \
  --do_train=True \
  --train_file=$DOCKER_SQUAD_DIR/train-v1.1.json \
  --do_predict=True \
  --predict_file=$DOCKER_SQUAD_DIR/dev-v1.1.json \
  --train_batch_size=12 \
  --learning_rate=3e-5 \
  --num_train_epochs=2.0 \
  --max_seq_length=320 \
  --doc_stride=128 \
  --output_dir=$DOCKER_OUTPUT_DIR

How to build Docker images

Docker images can be built using the commandlines below:

Build bert-online docker image (for CPU machine):

docker build -t bert-online .
docker tag bert-online:latest comcomai/bert-online:1.0.0
docker push comcomai/bert-online:1.0.0
docker pull comcomai/bert-online:1.0.0

Build bert-online-gpu docker image (for GPU machine):

vi Dockerfile  # Change tensorflow/tensorflow:1.12.0-rc2 to tensorflow/tensorflow:1.12.0-rc2-gpu 
docker build -t bert-online-gpu .
docker tag bert-online:latest comcomai/bert-online:1.0.0-gpu
docker push comcomai/bert-online:1.0.0-gpu
docker pull comcomai/bert-online:1.0.0-gpu

License

Copyright 2018 Common Computer Inc.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

 http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.