Aim:

Use Tensorflow Serving to serve a TF2.0 NLP model

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Table of Contents

• Usage
• Files
• Code style
• Prerequisites
• Reference
• License

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Usage

1. Clone the repo

git clone git@github.com:dujm/kaggle_quora.git

# Remove my git directory
cd kaggle_quora
rm -r .git/

2. Install packages

pip install -r requirements.txt

3. Download the Kaggle Quora dataset

• Download from Kaggle Website

• Or install Kaggle API and run:

  bash src/data/download-dataset.sh
  unzip src/data/embeddings.zip
  

4. Build tensorflow serving locally

bash src/models/00build-tfserve.sh

5. Train a test NLP model and save the model as a Tensorflow saved model

python src/models/01train-saved-model.py

6. Serve the model locally using Tensorflow Serving

bash src/models/02tf-serve-model.sh

TBC

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Files

 ├── LICENSE
 ├── README.md
 ├── src
 ├── test_environment.py
 │   ├── data
 │   │   ├── download-dataset.sh
 │   │   ├── embeddings
 │   │   │   ├── embeddings_index.npy
 │   │   │   ├── glove.840B.300d
 │   │   │   │   └── glove.840B.300d.txt
 │   │   │   ├── Other two embedding files (Not used here)
 │   │   ├── input
 │   │   │   ├── test.csv
 │   │   │   └── train.csv
 │   ├── models
 │   │   ├── 00build-tfserve.sh
 │   │   ├── 01train-saved-model.py
 │   │   ├── 02tf-serve-model.sh
 │   │   ├── sincere
 │   │   │   └── 1
 │   │   │       ├── assets
 │   │   │       ├── saved_model.pb
 │   │   │       └── variables
 │   │   │           ├── variables.data-00000-of-00001
 │   │   │           └── variables.index
 │   │   └── utils.py
 └──test_environment.py

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Code style

The information about code style in python is documented in this two links python-developer-guide and python-style-guide.

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Prerequisites

Python 3

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Reference

• Quora Insincere Questions Classification
• Using the SavedModel format
• tf.saved_model.save
• TensorFlow Serving

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License

The MIT License (MIT)