https://github.com/applifier/go-tensorflow

Tools and libraries for using Tensorflow (and Tensorflow Serving) in go
https://github.com/applifier/go-tensorflow

go golang grpc ml tensorflow tensorflow-serving

Last synced: 13 days ago
JSON representation

Tools and libraries for using Tensorflow (and Tensorflow Serving) in go

• Host: GitHub
• URL: https://github.com/applifier/go-tensorflow
• Owner: Applifier
• License: mit
• Created: 2018-05-30T06:31:42.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-04-07T13:59:29.000Z (over 3 years ago)
• Last Synced: 2024-11-16T03:40:28.275Z (about 2 months ago)
• Topics: go, golang, grpc, ml, tensorflow, tensorflow-serving
• Language: Go
• Homepage:
• Size: 6.49 MB
• Stars: 30
• Watchers: 6
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
[![GoDoc](https://godoc.org/github.com/Applifier/go-tensorflow?status.svg)](http://godoc.org/github.com/Applifier/go-tensorflow)

[![Build Status](https://travis-ci.org/Applifier/go-tensorflow.svg?branch=master)](https://travis-ci.org/Applifier/go-tensorflow)

# go-tensorflow

Unified interface for TensorFlow prediction for both embedded models and calls to Tensorflow Serving. Implementations automatically convert go types into matching TensorFlow Tensors.

Models should be exported in the SavedModel format.

### Example

Example uses pre-trained model found under testdata/models [wide_deep](https://github.com/tensorflow/models/tree/master/official/wide_deep)

```go

import "github.com/Applifier/go-tensorflow/savedmodel"

// import "github.com/Applifier/go-tensorflow/serving"

```

```go

// Uncomment line below to switch implementation

// predictor := serving.NewPredictor(servingModelClient)

predictor, _ := savedmodel.NewPredictor("testdata/models", "wide_deep", 1527087570, "serving_default")

m := map[string]interface{}{

    "age":            35.0,

    "capital_gain":   0.0,

    "capital_loss":   0.0,

    "education":      "Masters",

    "education_num":  14.0,

    "gender":         "Female",

    "hours_per_week": 29.0,

    "native_country": "United-States",

    "occupation":     "Prof-specialty",

    "relationship":   "Husband",

    "workclass":      "Private",

}

res, modelInfo, _ := predictor.Predict(

    context.Background(),

    map[string]interface{}{

        "inputs": m,

    },

    nil,

)

scores := res["scores"].Value().([][]float32)

fmt.Printf("scores %+v\n", scores[0])

// Output: scores [0.54612064 0.45387936]

fmt.Printf("model name %s, version %s", modelInfo.Name, modelInfo.Version)

// Output: model name wide_deep, version 1527087570

```

## License

[MIT](https://github.com/Applifier/go-tensorflow/blob/master/LICENSE)