Struct2Tensor is a package for parsing and manipulating structured data for TensorFlow

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Project description

Struct2Tensor

Introduction

struct2tensor is a library for parsing structured data inside of tensorflow. In particular, it makes it easy to manipulate structured data, e.g., slicing, flattening, copying substructures, and so on, as part of a TensorFlow model graph. The notebook in 'examples/prensor_playground.ipynb' provides a few examples of struct2tensor in action and an introduction to the main concepts. You can run the notebook in your browser through Google's colab environment, or download the file to run it in your own Jupyter environment.

There are two main use cases of this repo:

To create a PIP package. The PIP package contains plug-ins (OpKernels) to an existing tensorflow installation.
To staticlly link with tensorflow-serving.

As these processes are independent, one can follow either set of directions below.

Use a pre-built Linux PIP package.

From a virtual environment, run:

pip install struct2tensor

Nightly Packages

Struct2Tensor also hosts nightly packages at https://pypi-nightly.tensorflow.org on Google Cloud. To install the latest nightly package, please use the following command:

pip install -i https://pypi-nightly.tensorflow.org/simple struct2tensor

This will install the nightly packages for the major dependencies of Fairness Indicators such as TensorFlow Metadata (TFMD).

Creating a PIP package.

The struct2tensor PIP package is useful for creating models. It works with tensorflow 2.x.

In order to unify the process, we recommend compiling struct2tensor inside a docker container.

Downloading the Code

Go to your home directory.

Download the source code.

git clone https://github.com/google/struct2tensor.git
cd ~/struct2tensor

Use docker-compose

Install docker-compose.

Use it to build a pip wheel for Python 3.6 with tensorflow version 2:

docker-compose build manylinux2010
docker-compose run -e PYTHON_VERSION=36 -e TF_VERSION=RELEASED_TF_2 manylinux2010

Or build a pip wheel for Python 3.7 with tensorflow version 2 (note that if you run one of these docker-compose commands after the other, the second will erase the result from the first):

docker-compose build manylinux2010
docker-compose run -e PYTHON_VERSION=37 -e TF_VERSION=RELEASED_TF_2 manylinux2010

This will create a manylinux package in the ~/struct2tensor/dist directory.

Creating a static library.

In order to construct a static library for tensorflow-serving, we run:

bazel build -c opt struct2tensor:prensor_kernels_and_ops

This can also be linked into another library.

Compatibility

struct2tensor	tensorflow
0.22.0	2.2.0
0.21.1	2.1.0
0.21.0	2.1.0
0.0.1.dev*	1.15

Project details

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0.47.0

Oct 10, 2024

0.46.0

Apr 24, 2024

0.45.0

Aug 10, 2023

0.44.0

Apr 13, 2023

0.43.0

Dec 7, 2022

0.42.0

Nov 14, 2022

0.41.0

Aug 23, 2022

0.40.0

Jun 27, 2022

0.39.0

May 11, 2022

0.38.0

Mar 1, 2022

0.37.0

Jan 19, 2022

0.36.0

Nov 30, 2021

0.35.0

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0.34.0

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0.32.0

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0.31.0

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0.30.0

Apr 20, 2021

0.29.0

Mar 23, 2021

0.28.0

Feb 23, 2021

0.27.0

Jan 27, 2021

0.26.0

Dec 10, 2020

This version

0.25.0

Nov 3, 2020

0.24.0

Sep 14, 2020

0.23.0

Aug 10, 2020

0.22.0

May 14, 2020

0.21.1

Apr 10, 2020

0.21.0

Apr 2, 2020

0.0.1.dev6 pre-release

Nov 4, 2019

0.0.1.dev5 pre-release

Oct 23, 2019

0.0.1.dev4 pre-release

Oct 23, 2019

0.0.1.dev3 pre-release

Oct 23, 2019

0.0.1.dev2 pre-release

Oct 22, 2019

0.0.1.dev1 pre-release

Oct 18, 2019

0.0.1.dev0 pre-release

Jul 10, 2019

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